diff --git a/verticapy/__init__.py b/verticapy/__init__.py index f69a37277..d44efb209 100755 --- a/verticapy/__init__.py +++ b/verticapy/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_config/__init__.py b/verticapy/_config/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/_config/__init__.py +++ b/verticapy/_config/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_config/config.py b/verticapy/_config/config.py index 08a1a3dcf..8f5f71e79 100755 --- a/verticapy/_config/config.py +++ b/verticapy/_config/config.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -86,96 +86,78 @@ def set_option(key: str, value: Any = None) -> None: key: str Option to set, one of the following: - **cache**: bool + - cache: bool If set to True, vDataFrames save the computed aggregations in-memory. - - **colors**: list + - colors: list List of colors used to draw the graphics. - - **color_style**: str + - color_style: str Style used to color the graphics, one of the following: "rgb", "sunset", "retro", "shimbg", "swamp", "med", "orchid", "magenta", "orange", "vintage", "vivid", "berries", "refreshing", "summer", "tropical", "india", "default". - - **count_on**: bool + - count_on: bool If set to True, the total number of rows in vDataFrames and TableSamples is computed and - displayed in the footer (if footer_on is True). - - **footer_on**: bool + displayed in the footer (if ``footer_on is True``). + - footer_on: bool If set to True, vDataFrames and TableSamples show a footer that includes information about the displayed rows and columns. - - **interactive**: bool + - interactive: bool If set to True, VerticaPy outputs are displayed in interactive tables. - - **label_separator**: str + - label_separator: str Separator used to separate the query label from - the ``label_suffix``. The default value is '__'. - - **label_suffix**: str + the ``label_suffix``. The default value is ``__``. + - label_suffix: str Label suffix to add to VerticaPy's query labels. It can be useful to track some specific activities. For example: Looking which user runs some specific - VerticaPy functions. The default value is None. - - **max_columns**: int + VerticaPy functions. The default value is ``None``. + - max_columns: int Maximum number of columns to display. If the - specified value is invalid, max_columns is + specified value is invalid, ``max_columns`` is not changed. - - **max_rows**: int + - max_rows: int Maximum number of rows to display. If the - specified value is invalid, max_row is not - changed. - - **mode**: str + specified value is invalid, ``max_row`` is + not changed. + - mode: str Display mode for VerticaPy outputs, either: - **full** : - VerticaPy regular display mode. - - **light** : - Minimalist display mode. + **full**: + VerticaPy regular display mode. - **percent_bar**: bool + **light**: + Minimalist display mode. + - percent_bar: bool If set to True, the percent of non-missing values is displayed. - - **print_info**: bool + - print_info: bool If set to True, information is printed each time the vDataFrame is modified. - - **random_state**: int + - random_state: int Integer used to seed random number generation in VerticaPy. - - **save_query_profile**: bool + - save_query_profile: bool If set to True, all function calls are stored in the query profile table. This makes it possible to differentiate the VerticaPy logs from the Vertica logs. If set to False, this functionality is deactivated. - - **sql_on**: bool + - sql_on: bool If set to True, displays all SQL queries. - - **temp_schema**: str + - temp_schema: str Specifies the temporary schema that certain methods/functions use to create intermediate objects, if needed. - - **time_on**: bool + - time_on: bool If set to True, displays the elasped time for all SQL queries. - - **tqdm**: bool + - tqdm: bool If set to True, a loading bar is displayed when using iterative functions. diff --git a/verticapy/_config/validators.py b/verticapy/_config/validators.py index bb6ba57dd..96f81c822 100755 --- a/verticapy/_config/validators.py +++ b/verticapy/_config/validators.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_help.py b/verticapy/_help.py index 596a1b0fc..77d6ab483 100755 --- a/verticapy/_help.py +++ b/verticapy/_help.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_typing.py b/verticapy/_typing.py index ca2fbd867..2dbb16cf7 100755 --- a/verticapy/_typing.py +++ b/verticapy/_typing.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_utils/__init__.py b/verticapy/_utils/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/_utils/__init__.py +++ b/verticapy/_utils/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_utils/_display.py b/verticapy/_utils/_display.py index 58d90a290..34c6d21da 100755 --- a/verticapy/_utils/_display.py +++ b/verticapy/_utils/_display.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_utils/_gen.py b/verticapy/_utils/_gen.py index 17ee53332..a2190da74 100755 --- a/verticapy/_utils/_gen.py +++ b/verticapy/_utils/_gen.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_utils/_logo.py b/verticapy/_utils/_logo.py index 7d34fdd0c..6a49ce080 100755 --- a/verticapy/_utils/_logo.py +++ b/verticapy/_utils/_logo.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_utils/_map.py b/verticapy/_utils/_map.py index 4101cefac..f78f57038 100755 --- a/verticapy/_utils/_map.py +++ b/verticapy/_utils/_map.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_utils/_object.py b/verticapy/_utils/_object.py index d4b0ab54b..7b0aa37df 100755 --- a/verticapy/_utils/_object.py +++ b/verticapy/_utils/_object.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_utils/_parsers.py b/verticapy/_utils/_parsers.py index 68ef4f744..bfeff41a6 100755 --- a/verticapy/_utils/_parsers.py +++ b/verticapy/_utils/_parsers.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_utils/_sql/__init__.py b/verticapy/_utils/_sql/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/_utils/_sql/__init__.py +++ b/verticapy/_utils/_sql/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_utils/_sql/_cast.py b/verticapy/_utils/_sql/_cast.py index ed028570e..504d5ebaf 100755 --- a/verticapy/_utils/_sql/_cast.py +++ b/verticapy/_utils/_sql/_cast.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_utils/_sql/_check.py b/verticapy/_utils/_sql/_check.py index fd8be2d19..47d07a08b 100755 --- a/verticapy/_utils/_sql/_check.py +++ b/verticapy/_utils/_sql/_check.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_utils/_sql/_collect.py b/verticapy/_utils/_sql/_collect.py index b2e22dca9..0747e24ba 100755 --- a/verticapy/_utils/_sql/_collect.py +++ b/verticapy/_utils/_sql/_collect.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_utils/_sql/_dblink.py b/verticapy/_utils/_sql/_dblink.py index 4022ffd9c..eb31e61cc 100755 --- a/verticapy/_utils/_sql/_dblink.py +++ b/verticapy/_utils/_sql/_dblink.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_utils/_sql/_display.py b/verticapy/_utils/_sql/_display.py index 99772faa2..76f3843e9 100755 --- a/verticapy/_utils/_sql/_display.py +++ b/verticapy/_utils/_sql/_display.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_utils/_sql/_format.py b/verticapy/_utils/_sql/_format.py index 7cf0bb2ae..7304632a8 100755 --- a/verticapy/_utils/_sql/_format.py +++ b/verticapy/_utils/_sql/_format.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_utils/_sql/_merge.py b/verticapy/_utils/_sql/_merge.py index 505b3275f..ba29448cf 100755 --- a/verticapy/_utils/_sql/_merge.py +++ b/verticapy/_utils/_sql/_merge.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_utils/_sql/_random.py b/verticapy/_utils/_sql/_random.py index 1b545e289..beecba192 100755 --- a/verticapy/_utils/_sql/_random.py +++ b/verticapy/_utils/_sql/_random.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_utils/_sql/_sys.py b/verticapy/_utils/_sql/_sys.py index 86eccd3af..88d088c92 100755 --- a/verticapy/_utils/_sql/_sys.py +++ b/verticapy/_utils/_sql/_sys.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/_utils/_sql/_vertica_version.py b/verticapy/_utils/_sql/_vertica_version.py index 562dbb592..31f8fc5d6 100755 --- a/verticapy/_utils/_sql/_vertica_version.py +++ b/verticapy/_utils/_sql/_vertica_version.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/chart/__init__.py b/verticapy/chart/__init__.py index c10a86462..f887fb76a 100755 --- a/verticapy/chart/__init__.py +++ b/verticapy/chart/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/connection/__init__.py b/verticapy/connection/__init__.py index a620d8fbc..671179a01 100755 --- a/verticapy/connection/__init__.py +++ b/verticapy/connection/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/connection/connect.py b/verticapy/connection/connect.py index 7d9b85625..8c7bd4df1 100755 --- a/verticapy/connection/connect.py +++ b/verticapy/connection/connect.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/connection/external.py b/verticapy/connection/external.py index b12fb5132..791354727 100755 --- a/verticapy/connection/external.py +++ b/verticapy/connection/external.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/connection/global_connection.py b/verticapy/connection/global_connection.py index 891bf4ab5..4d99d6073 100755 --- a/verticapy/connection/global_connection.py +++ b/verticapy/connection/global_connection.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/connection/read.py b/verticapy/connection/read.py index 0ffa029b8..36b501fbf 100755 --- a/verticapy/connection/read.py +++ b/verticapy/connection/read.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/connection/utils.py b/verticapy/connection/utils.py index 1b0bfb319..fd49ce525 100755 --- a/verticapy/connection/utils.py +++ b/verticapy/connection/utils.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/connection/write.py b/verticapy/connection/write.py index 59d02b7e4..8d54a968e 100755 --- a/verticapy/connection/write.py +++ b/verticapy/connection/write.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -38,14 +38,17 @@ def change_auto_connection(name: str) -> None: from verticapy.connection import new_connection, change_auto_connection - new_connection({ - "host": "10.211.55.14", - "port": "5433", - "database": "testdb", - "password": "XxX", - "user": "dbadmin"}, + new_connection( + { + "host": "10.211.55.14", + "port": "5433", + "database": "testdb", + "password": "XxX", + "user": "dbadmin", + }, name = "my_auto_connection", - auto = False) + auto = False, + ) Change the auto connection to "my_auto_connection": diff --git a/verticapy/core/__init__.py b/verticapy/core/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/core/__init__.py +++ b/verticapy/core/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/parsers/__init__.py b/verticapy/core/parsers/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/core/parsers/__init__.py +++ b/verticapy/core/parsers/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/parsers/_utils.py b/verticapy/core/parsers/_utils.py index dfadc7ea2..e22972c0b 100755 --- a/verticapy/core/parsers/_utils.py +++ b/verticapy/core/parsers/_utils.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/parsers/all.py b/verticapy/core/parsers/all.py index 7843b84e4..2118a3d2a 100755 --- a/verticapy/core/parsers/all.py +++ b/verticapy/core/parsers/all.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/parsers/avro.py b/verticapy/core/parsers/avro.py index b14629ffa..8380e0d0f 100755 --- a/verticapy/core/parsers/avro.py +++ b/verticapy/core/parsers/avro.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/parsers/csv.py b/verticapy/core/parsers/csv.py index 06824cbf1..0ff363784 100755 --- a/verticapy/core/parsers/csv.py +++ b/verticapy/core/parsers/csv.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/parsers/json.py b/verticapy/core/parsers/json.py index 20aeceb54..f1eaeea43 100755 --- a/verticapy/core/parsers/json.py +++ b/verticapy/core/parsers/json.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/parsers/pandas.py b/verticapy/core/parsers/pandas.py index c7264b9af..dceb87617 100755 --- a/verticapy/core/parsers/pandas.py +++ b/verticapy/core/parsers/pandas.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/parsers/shp.py b/verticapy/core/parsers/shp.py index 45983cdea..92ed6f42c 100755 --- a/verticapy/core/parsers/shp.py +++ b/verticapy/core/parsers/shp.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/string_sql/__init__.py b/verticapy/core/string_sql/__init__.py index d21dc414e..6974c4dfc 100755 --- a/verticapy/core/string_sql/__init__.py +++ b/verticapy/core/string_sql/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/string_sql/base.py b/verticapy/core/string_sql/base.py index 471f8c59e..a8c6b4a2d 100755 --- a/verticapy/core/string_sql/base.py +++ b/verticapy/core/string_sql/base.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/tablesample/__init__.py b/verticapy/core/tablesample/__init__.py index fb47847ff..b02843af0 100755 --- a/verticapy/core/tablesample/__init__.py +++ b/verticapy/core/tablesample/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/tablesample/base.py b/verticapy/core/tablesample/base.py index 91259ca79..71030b0f1 100644 --- a/verticapy/core/tablesample/base.py +++ b/verticapy/core/tablesample/base.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/vdataframe/__init__.py b/verticapy/core/vdataframe/__init__.py index d8ff921ed..1ec71b687 100755 --- a/verticapy/core/vdataframe/__init__.py +++ b/verticapy/core/vdataframe/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/vdataframe/_aggregate.py b/verticapy/core/vdataframe/_aggregate.py index 534a6cdb0..4e34a134c 100755 --- a/verticapy/core/vdataframe/_aggregate.py +++ b/verticapy/core/vdataframe/_aggregate.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -79,42 +79,71 @@ def aggregate( Parameters ---------- func: SQLExpression - | List of the different aggregations: - - | **aad**: average absolute deviation - | **approx_median**: approximate median - | **approx_q%**: approximate q quantile - (ex: approx_50% for the - approximate median) - | **approx_unique**: approximative cardinality - | **count**: number of non-missing elements - | **cvar**: conditional value at risk - | **dtype**: virtual column type - | **iqr**: interquartile range - | **kurtosis**: kurtosis - | **jb**: Jarque-Bera index - | **mad**: median absolute deviation - | **max**: maximum - | **mean**: average - | **median**: median - | **min**: minimum - | **mode**: most occurent element - | **percent**: percent of non-missing elements - | **q%**: q quantile (ex: 50% for the median) - Use the ``approx_q%`` (approximate quantile) - aggregation to get better performance. - | **prod**: product - | **range**: difference between the max and the min - | **sem**: standard error of the mean - | **skewness**: skewness - | **sum**: sum - | **std**: standard deviation - | **topk**: kth most occurent element (ex: top1 for the mode) - | **topk_percent**: kth most occurent element density - | **unique**: cardinality (count distinct) - | **var**: variance - | Other aggregations will work if supported by your database - version. + List of the different aggregations: + + - aad: + average absolute deviation. + - approx_median: + approximate median. + - approx_q%: + approximate q quantile (ex: approx_50% + for the approximate median). + - approx_unique: + approximative cardinality. + - count: + number of non-missing elements. + - cvar: + conditional value at risk. + - dtype: + virtual column type. + - iqr: + interquartile range. + - kurtosis: + kurtosis. + - jb: + Jarque-Bera index. + - mad: + median absolute deviation. + - max: + maximum. + - mean: + average. + - median: + median. + - min: + minimum. + - mode: + most occurent element. + - percent: + percent of non-missing elements. + - q%: + q quantile (ex: 50% for the median) + Use the ``approx_q%`` (approximate quantile) + aggregation to get better performance. + - prod: + product. + - range: + difference between the max and the min. + - sem: + standard error of the mean. + - skewness: + skewness. + - sum: + sum. + - std: + standard deviation. + - topk: + kth most occurent element (ex: top1 for the mode) + - topk_percent: + kth most occurent element density. + - unique: + cardinality (count distinct). + - var: + variance. + + Other aggregations will work if supported by your database + version. + columns: SQLColumns, optional List of the vDataColumn's names. If empty, depending on the aggregations, all or only numerical vDataColumns are used. @@ -144,11 +173,13 @@ def aggregate( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) With the ``aggregate`` method, you have the flexibility to select specific aggregates and the columns you wish to include in the query. This @@ -166,11 +197,13 @@ def aggregate( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data.aggregate( func = ["min", "approx_10%", "approx_50%", "approx_90%", "max"], columns = ["x", "y", "z"], @@ -195,11 +228,11 @@ def aggregate( ones, and the results are combined at the end. .. seealso:: - | :py:mod:`verticapy.vDataColumn.aggregate` : + | :py:meth:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. - | :py:mod:`verticapy.vDataColumn.describe` : + | :py:meth:`verticapy.vDataColumn.describe` : Summarizes the information within the column. - | :py:mod:`verticapy.vDataFrame.describe` : + | :py:meth:`verticapy.vDataFrame.describe` : Summarizes the information for specific columns. """ columns, func = format_type(columns, func, dtype=list) @@ -727,33 +760,41 @@ def describe( .. note:: This function can offer faster performance compared to the - :py:mod:`verticapy.vDataFrame.aggregate` method, as it + :py:meth:`verticapy.vDataFrame.aggregate` method, as it leverages specialized and optimized backend functions. Parameters ---------- method: str, optional - | The describe method. - - | **all**: Aggregates all statistics for all vDataColumns. - The exact method depends on the vDataColumn type - (numerical dtype: numerical; timestamp dtype: - range; categorical dtype: length) - | **auto**: Sets the method to ``numerical`` if at least - one vDataColumn of the vDataFrame is numerical, - ``categorical`` otherwise. - | **categorical**: Uses only categorical aggregations. - | **length**: Aggregates the vDataFrame using numerical - aggregation on the length of all selected - vDataColumns. - | **numerical**: Uses only numerical descriptive statistics, - which are computed faster than the `aggregate` - method. - | **range**: Aggregates the vDataFrame using multiple - statistical aggregations - min, max, range... - | **statistics**: Aggregates the vDataFrame using multiple - statistical aggregations - kurtosis, skewness, - min, max... + The describe method. + + - all: + Aggregates all statistics for all vDataColumns. + The exact method depends on the vDataColumn type + (numerical dtype: numerical; timestamp dtype: + range; categorical dtype: length) + - auto: + Sets the method to ``numerical`` if at least + one vDataColumn of the vDataFrame is numerical, + ``categorical`` otherwise. + - categorical: + Uses only categorical aggregations. + - length: + Aggregates the vDataFrame using numerical + aggregation on the length of all selected + vDataColumns. + - numerical: + Uses only numerical descriptive statistics, + which are computed faster than the `aggregate` + method. + - range: + Aggregates the vDataFrame using multiple + statistical aggregations - min, max, range... + - statistics: + Aggregates the vDataFrame using multiple + statistical aggregations - kurtosis, skewness, + min, max... + columns: SQLColumns, optional List of the vDataColumns names. If empty, the vDataColumns are selected depending on the parameter ``method``. @@ -785,12 +826,14 @@ def describe( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - "c": ['A', 'A', 'A', 'A', 'B', 'B', 'C', 'D'], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + "c": ['A', 'A', 'A', 'A', 'B', 'B', 'C', 'D'], + } + ) The ``describe`` method provides you with a variety of statistical methods. @@ -809,12 +852,14 @@ def describe( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - "c": ['A', 'A', 'A', 'A', 'B', 'B', 'C', 'D'], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + "c": ['A', 'A', 'A', 'A', 'B', 'B', 'C', 'D'], + } + ) result = data.describe( columns = ["x", "y", "z"], method = "numerical", @@ -840,12 +885,14 @@ def describe( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - "c": ['A', 'A', 'A', 'A', 'B', 'B', 'C', 'D'], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + "c": ['A', 'A', 'A', 'A', 'B', 'B', 'C', 'D'], + } + ) result = data.describe( columns = ["x", "y", "z", "c"], method = "categorical", @@ -871,12 +918,14 @@ def describe( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - "c": ['A', 'A', 'A', 'A', 'B', 'B', 'C', 'D'], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + "c": ['A', 'A', 'A', 'A', 'B', 'B', 'C', 'D'], + } + ) result = data.describe( columns = ["x", "y", "z", "c"], method = "all", @@ -895,9 +944,9 @@ def describe( .. note:: All the calculations are pushed to the database. .. seealso:: - | :py:mod:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. - | :py:mod:`verticapy.vDataFrame.aggregate` : Aggregations for specific columns. - | :py:mod:`verticapy.vDataColumn.describe` : + | :py:meth:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. + | :py:meth:`verticapy.vDataFrame.aggregate` : Aggregations for specific columns. + | :py:meth:`verticapy.vDataColumn.describe` : Summarizes the information within the column. """ if method == "auto": @@ -1301,11 +1350,13 @@ def groupby( import verticapy as vp - data = vp.vDataFrame({ - "x": ['A', 'A', 'A', 'B', 'B', 'B', 'C', 'C'], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": ['A', 'A', 'A', 'B', 'B', 'B', 'C', 'C'], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) You can perform grouping using a direct SQL statement. @@ -1320,11 +1371,13 @@ def groupby( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": ['A', 'A', 'A', 'B', 'B', 'B', 'C', 'C'], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": ['A', 'A', 'A', 'B', 'B', 'B', 'C', 'C'], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data.groupby( columns = ["x"], expr = ["AVG(y) AS avg_y", "MIN(z) AS min_z"], @@ -1391,8 +1444,8 @@ def groupby( .. hint:: For additional aggregation options, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. - | :py:mod:`verticapy.vDataFrame.aggregate` : Aggregates for particular columns. + | :py:meth:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. + | :py:meth:`verticapy.vDataFrame.aggregate` : Aggregates for particular columns. """ columns, expr = format_type(columns, expr, dtype=list) assert not isinstance(rollup, list) or len(rollup) == len(columns), ValueError( @@ -1538,11 +1591,13 @@ def aad( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let's calculate the average absolute deviation for specific columns. @@ -1557,11 +1612,13 @@ def aad( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data.aad( columns = ["x", "y", "z"], ) @@ -1577,9 +1634,9 @@ def aad( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.aad` : + | :py:meth:`verticapy.vDataColumn.aad` : Average Absolute Deviation for a specific column. - | :py:mod:`verticapy.vDataFrame.std` : + | :py:meth:`verticapy.vDataFrame.std` : Standard Deviation for particular columns. """ return self.aggregate(func=["aad"], columns=columns, **agg_kwargs) @@ -1621,11 +1678,13 @@ def all( import verticapy as vp - data = vp.vDataFrame({ - "x": [True, False, False], - "y": [False, False, False], - "z": [True, True, True], - }) + data = vp.vDataFrame( + { + "x": [True, False, False], + "y": [False, False, False], + "z": [True, True, True], + } + ) Now, let's use the ``all`` aggregator for specific columns. @@ -1639,11 +1698,13 @@ def all( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [True, False, False], - "y": [False, False, False], - "z": [True, True, True], - }) + data = vp.vDataFrame( + { + "x": [True, False, False], + "y": [False, False, False], + "z": [True, True, True], + } + ) result = data.all( columns = ["x", "y", "z"], ) @@ -1659,7 +1720,7 @@ def all( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataFrame.any` : Boolean OR Aggregation. + | :py:meth:`verticapy.vDataFrame.any` : Boolean OR Aggregation. """ return self.aggregate(func=["bool_and"], columns=columns, **agg_kwargs) @@ -1698,11 +1759,13 @@ def any( import verticapy as vp - data = vp.vDataFrame({ - "x": [True, False, False], - "y": [False, False, False], - "z": [True, True, True], - }) + data = vp.vDataFrame( + { + "x": [True, False, False], + "y": [False, False, False], + "z": [True, True, True], + } + ) Now, let's use the ``any`` aggregator for specific columns. @@ -1716,11 +1779,13 @@ def any( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [True, False, False], - "y": [False, False, False], - "z": [True, True, True], - }) + data = vp.vDataFrame( + { + "x": [True, False, False], + "y": [False, False, False], + "z": [True, True, True], + } + ) result = data.any( columns = ["x", "y", "z"], ) @@ -1736,7 +1801,7 @@ def any( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataFrame.all` : Boolean AND Aggregation. + | :py:meth:`verticapy.vDataFrame.all` : Boolean AND Aggregation. """ return self.aggregate(func=["bool_or"], columns=columns, **agg_kwargs) @@ -1775,11 +1840,13 @@ def avg( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let's calculate the averages for specific columns. @@ -1793,11 +1860,13 @@ def avg( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data.avg( columns = ["x", "y", "z"], ) @@ -1813,9 +1882,9 @@ def avg( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.avg` : Aggregations for a specific column. - | :py:mod:`verticapy.vDataFrame.max` : Maximum for particular columns. - | :py:mod:`verticapy.vDataFrame.min` : Minimum for particular columns. + | :py:meth:`verticapy.vDataColumn.avg` : Aggregations for a specific column. + | :py:meth:`verticapy.vDataFrame.max` : Maximum for particular columns. + | :py:meth:`verticapy.vDataFrame.min` : Minimum for particular columns. """ return self.aggregate(func=["avg"], columns=columns, **agg_kwargs) @@ -1855,11 +1924,13 @@ def count( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let`s calculate the count for specific columns. @@ -1873,11 +1944,13 @@ def count( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data.count( columns = ["x", "y", "z"], ) @@ -1893,8 +1966,8 @@ def count( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.count` : Count for a specific column. - | :py:mod:`verticapy.vDataFrame.count_percent` : Count Percent for particular columns. + | :py:meth:`verticapy.vDataColumn.count` : Count for a specific column. + | :py:meth:`verticapy.vDataFrame.count_percent` : Count Percent for particular columns. """ return self.aggregate(func=["count"], columns=columns, **agg_kwargs) @@ -1943,11 +2016,13 @@ def kurtosis( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let's calculate the kurtosis for specific columns. @@ -1961,11 +2036,13 @@ def kurtosis( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data.kurtosis( columns = ["x", "y", "z"], ) @@ -1981,9 +2058,9 @@ def kurtosis( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.kurtosis` : Kurtosis for a specific column. - | :py:mod:`verticapy.vDataFrame.skewness` : Skewness for particular columns. - | :py:mod:`verticapy.vDataFrame.std` : Standard Deviation for particular columns. + | :py:meth:`verticapy.vDataColumn.kurtosis` : Kurtosis for a specific column. + | :py:meth:`verticapy.vDataFrame.skewness` : Skewness for particular columns. + | :py:meth:`verticapy.vDataFrame.std` : Standard Deviation for particular columns. """ return self.aggregate(func=["kurtosis"], columns=columns, **agg_kwargs) @@ -2039,11 +2116,13 @@ def mad( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let's calculate the median absolute deviation for specific columns. @@ -2058,11 +2137,13 @@ def mad( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data.mad( columns = ["x", "y", "z"], ) @@ -2078,8 +2159,8 @@ def mad( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataFrame.std` : Mean Absolute Deviation for particular columns. - | :py:mod:`verticapy.vDataColumn.mad` : Standard Deviation for a specific column. + | :py:meth:`verticapy.vDataFrame.std` : Mean Absolute Deviation for particular columns. + | :py:meth:`verticapy.vDataColumn.mad` : Standard Deviation for a specific column. """ return self.aggregate(func=["mad"], columns=columns, **agg_kwargs) @@ -2117,11 +2198,13 @@ def max( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let's calculate the maximum for specific columns. @@ -2135,11 +2218,13 @@ def max( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data.max( columns = ["x", "y", "z"], ) @@ -2155,8 +2240,8 @@ def max( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataFrame.min` : Minimum for particular columns. - | :py:mod:`verticapy.vDataColumn.max` : Maximum for a specific column. + | :py:meth:`verticapy.vDataFrame.min` : Minimum for particular columns. + | :py:meth:`verticapy.vDataColumn.max` : Maximum for a specific column. """ return self.aggregate(func=["max"], columns=columns, **agg_kwargs) @@ -2205,11 +2290,13 @@ def median( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let's calculate the median for specific columns. @@ -2224,11 +2311,13 @@ def median( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data.median( columns = ["x", "y", "z"], approx = True, @@ -2245,9 +2334,9 @@ def median( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataFrame.max` : Maximum for particular columns. - | :py:mod:`verticapy.vDataFrame.min` : Maximum for particular columns. - | :py:mod:`verticapy.vDataColumn.mean` : Mean for a specific column. + | :py:meth:`verticapy.vDataFrame.max` : Maximum for particular columns. + | :py:meth:`verticapy.vDataFrame.min` : Maximum for particular columns. + | :py:meth:`verticapy.vDataColumn.mean` : Mean for a specific column. """ return self.quantile( 0.5, @@ -2290,11 +2379,13 @@ def min( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let's calculate the minimum for specific columns. @@ -2308,11 +2399,13 @@ def min( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data.min( columns = ["x", "y", "z"], ) @@ -2328,8 +2421,8 @@ def min( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.min` : Minimum for a specific column. - | :py:mod:`verticapy.vDataFrame.max` : Maximum for particular columns. + | :py:meth:`verticapy.vDataColumn.min` : Minimum for a specific column. + | :py:meth:`verticapy.vDataFrame.max` : Maximum for particular columns. """ return self.aggregate(func=["min"], columns=columns, **agg_kwargs) @@ -2386,11 +2479,13 @@ def product( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let's calculate the product for specific columns. @@ -2404,11 +2499,13 @@ def product( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data.product( columns = ["x", "y", "z"], ) @@ -2424,8 +2521,8 @@ def product( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataFrame.aggregate` : Aggregates for particular columns. - | :py:mod:`verticapy.vDataFrame.quantile` : Quantile Aggregates for particular columns. + | :py:meth:`verticapy.vDataFrame.aggregate` : Aggregates for particular columns. + | :py:meth:`verticapy.vDataFrame.quantile` : Quantile Aggregates for particular columns. """ return self.aggregate(func=["prod"], columns=columns, **agg_kwargs) @@ -2494,11 +2591,13 @@ def quantile( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let's calculate some approximate quantiles for specific columns. @@ -2515,11 +2614,13 @@ def quantile( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data.quantile( q = [0.1, 0.2, 0.5, 0.9], columns = ["x", "y", "z"], @@ -2537,8 +2638,8 @@ def quantile( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. - | :py:mod:`verticapy.vDataFrame.aggregate` : Aggregates for particular columns. + | :py:meth:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. + | :py:meth:`verticapy.vDataFrame.aggregate` : Aggregates for particular columns. """ if isinstance(q, (int, float)): q = [q] @@ -2602,11 +2703,13 @@ def sem( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let's calculate the standard error of the mean for specific columns. @@ -2621,11 +2724,13 @@ def sem( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data.sem( columns = ["x", "y", "z"], ) @@ -2641,8 +2746,8 @@ def sem( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.sem` : Standard Error of Mean for a specific column. - | :py:mod:`verticapy.vDataFrame.mad` : Mean Absolute Deviation for particular columns. + | :py:meth:`verticapy.vDataColumn.sem` : Standard Error of Mean for a specific column. + | :py:meth:`verticapy.vDataFrame.mad` : Mean Absolute Deviation for particular columns. """ return self.aggregate(func=["sem"], columns=columns, **agg_kwargs) @@ -2691,11 +2796,13 @@ def skewness( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let's calculate the skewness for specific columns. @@ -2709,11 +2816,13 @@ def skewness( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data.skewness( columns = ["x", "y", "z"], ) @@ -2729,9 +2838,9 @@ def skewness( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.kurtosis` : Kurtosis for a specific column. - | :py:mod:`verticapy.vDataColumn.skewness` : Skewness for a specific column. - | :py:mod:`verticapy.vDataFrame.std` : Standard Deviation for particular columns. + | :py:meth:`verticapy.vDataColumn.kurtosis` : Kurtosis for a specific column. + | :py:meth:`verticapy.vDataColumn.skewness` : Skewness for a specific column. + | :py:meth:`verticapy.vDataFrame.std` : Standard Deviation for particular columns. """ return self.aggregate(func=["skewness"], columns=columns, **agg_kwargs) @@ -2773,11 +2882,13 @@ def std( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let's calculate the standard deviation for specific columns. @@ -2791,11 +2902,13 @@ def std( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data.std( columns = ["x", "y", "z"], ) @@ -2811,9 +2924,9 @@ def std( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.kurtosis` : Kurtosis for a specific column. - | :py:mod:`verticapy.vDataFrame.skewness` : Skewness for particular columns. - | :py:mod:`verticapy.vDataColumn.std` : Standard Deviation for a specific column. + | :py:meth:`verticapy.vDataColumn.kurtosis` : Kurtosis for a specific column. + | :py:meth:`verticapy.vDataFrame.skewness` : Skewness for particular columns. + | :py:meth:`verticapy.vDataColumn.std` : Standard Deviation for a specific column. """ return self.aggregate(func=["stddev"], columns=columns, **agg_kwargs) @@ -2852,11 +2965,13 @@ def sum( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let's calculate the sum for specific columns. @@ -2870,11 +2985,13 @@ def sum( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data.sum( columns = ["x", "y", "z"], ) @@ -2890,8 +3007,8 @@ def sum( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.sum` : Sum for a specific column. - | :py:mod:`verticapy.vDataFrame.max` : Maximum for particular columns. + | :py:meth:`verticapy.vDataColumn.sum` : Sum for a specific column. + | :py:meth:`verticapy.vDataFrame.max` : Maximum for particular columns. """ return self.aggregate(func=["sum"], columns=columns, **agg_kwargs) @@ -2931,11 +3048,13 @@ def var( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let's calculate the variance for specific columns. @@ -2949,11 +3068,13 @@ def var( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data.var( columns = ["x", "y", "z"], ) @@ -2969,9 +3090,9 @@ def var( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.kurtosis` : Kurtosis for a specific column. - | :py:mod:`verticapy.vDataColumn.skewness` : Skewness for a specific column. - | :py:mod:`verticapy.vDataFrame.std` : Standard Deviation for particular columns. + | :py:meth:`verticapy.vDataColumn.kurtosis` : Kurtosis for a specific column. + | :py:meth:`verticapy.vDataColumn.skewness` : Skewness for a specific column. + | :py:meth:`verticapy.vDataFrame.std` : Standard Deviation for particular columns. """ return self.aggregate(func=["variance"], columns=columns, **agg_kwargs) @@ -3026,11 +3147,13 @@ def count_percent( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let's calculate the count percentage for specific columns. @@ -3044,11 +3167,13 @@ def count_percent( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [None, None, 4, 9, None, 15, None, 22], - "y": [1, 2, 1, 2, None, 1, 2, 1], - "z": [10, None, 2, 1, 9, 8, None, 3], - }) + data = vp.vDataFrame( + { + "x": [None, None, 4, 9, None, 15, None, 22], + "y": [1, 2, 1, 2, None, 1, 2, 1], + "z": [10, None, 2, 1, 9, 8, None, 3], + } + ) result = data.count_percent( columns = ["x", "y", "z"], ) @@ -3064,8 +3189,8 @@ def count_percent( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.count` : Count for a specific column. - | :py:mod:`verticapy.vDataFrame.count` : Count for particular columns. + | :py:meth:`verticapy.vDataColumn.count` : Count for a specific column. + | :py:meth:`verticapy.vDataFrame.count` : Count for particular columns. """ result = self.aggregate( func=["count", "percent"], @@ -3133,11 +3258,13 @@ def nunique( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let's calculate the cardinality for specific columns. @@ -3151,11 +3278,13 @@ def nunique( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data.nunique( columns = ["x", "y", "z"], ) @@ -3171,8 +3300,8 @@ def nunique( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataFrame.duplicated` : Duplicate Values for particular columns. - | :py:mod:`verticapy.vDataColumn.nunique` : Cardinaility for a specific column. + | :py:meth:`verticapy.vDataFrame.duplicated` : Duplicate Values for particular columns. + | :py:meth:`verticapy.vDataColumn.nunique` : Cardinaility for a specific column. """ func = ["approx_unique"] if approx else ["unique"] return self.aggregate(func=func, columns=columns, **agg_kwargs) @@ -3228,11 +3357,13 @@ def duplicated( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 15, 1, 15, 20, 1], - "y": [1, 2, 1, 1, 1, 1, 2, 1], - "z": [10, 12, 9, 10, 9, 8, 1, 10], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 15, 1, 15, 20, 1], + "y": [1, 2, 1, 1, 1, 1, 2, 1], + "z": [10, 12, 9, 10, 9, 8, 1, 10], + } + ) Now, let's find duplicated rows. @@ -3246,11 +3377,13 @@ def duplicated( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 15, 1, 15, 20, 1], - "y": [1, 2, 1, 1, 1, 1, 2, 1], - "z": [10, 12, 9, 10, 9, 8, 1, 10], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 15, 1, 15, 20, 1], + "y": [1, 2, 1, 1, 1, 1, 2, 1], + "z": [10, 12, 9, 10, 9, 8, 1, 10], + } + ) result = data.duplicated( columns = ["x", "y", "z"], ) @@ -3266,8 +3399,8 @@ def duplicated( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.nunique` : Cardinality for a specific column. - | :py:mod:`verticapy.vDataFrame.nunique` : Cardinality for particular columns. + | :py:meth:`verticapy.vDataColumn.nunique` : Cardinality for a specific column. + | :py:meth:`verticapy.vDataFrame.nunique` : Cardinality for particular columns. """ columns = format_type(columns, dtype=list) if len(columns) == 0: @@ -3332,42 +3465,70 @@ def aggregate(self, func: list) -> TableSample: Parameters ---------- func: SQLExpression - | List of the different aggregations: - - | **aad**: average absolute deviation - | **approx_median**: approximate median - | **approx_q%**: approximate q quantile - (ex: approx_50% for the - approximate median) - | **approx_unique**: approximative cardinality - | **count**: number of non-missing elements - | **cvar**: conditional value at risk - | **dtype**: virtual column type - | **iqr**: interquartile range - | **kurtosis**: kurtosis - | **jb**: Jarque-Bera index - | **mad**: median absolute deviation - | **max**: maximum - | **mean**: average - | **median**: median - | **min**: minimum - | **mode**: most occurent element - | **percent**: percent of non-missing elements - | **q%**: q quantile (ex: 50% for the median) - Use the ``approx_q%`` (approximate quantile) - aggregation to get better performance. - | **prod**: product - | **range**: difference between the max and the min - | **sem**: standard error of the mean - | **skewness**: skewness - | **sum**: sum - | **std**: standard deviation - | **topk**: kth most occurent element (ex: top1 for the mode) - | **topk_percent**: kth most occurent element density - | **unique**: cardinality (count distinct) - | **var**: variance - | Other aggregations will work if supported by your database - version. + List of the different aggregations: + + - aad: + average absolute deviation. + - approx_median: + approximate median. + - approx_q%: + approximate q quantile (ex: approx_50% + for the approximate median). + - approx_unique: + approximative cardinality. + - count: + number of non-missing elements. + - cvar: + conditional value at risk. + - dtype: + virtual column type. + - iqr: + interquartile range. + - kurtosis: + kurtosis. + - jb: + Jarque-Bera index. + - mad: + median absolute deviation. + - max: + maximum. + - mean: + average. + - median: + median. + - min: + minimum. + - mode: + most occurent element. + - percent: + percent of non-missing elements. + - q%: + q quantile (ex: 50% for the median) + Use the ``approx_q%`` (approximate quantile) + aggregation to get better performance. + - prod: + product. + - range: + difference between the max and the min. + - sem: + standard error of the mean. + - skewness: + skewness. + - sum: + sum. + - std: + standard deviation. + - topk: + kth most occurent element (ex: top1 for the mode). + - topk_percent: + kth most occurent element density. + - unique: + cardinality (count distinct). + - var: + variance. + + Other aggregations will work if supported by your database + version. columns: SQLColumns, optional List of the vDataColumn's names. If empty, depending on the aggregations, all or only numerical vDataColumns are used. @@ -3397,11 +3558,13 @@ def aggregate(self, func: list) -> TableSample: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) With the ``aggregate`` method, you have the flexibility to select specific aggregates you wish to include in the query. This allows for more precise @@ -3418,11 +3581,13 @@ def aggregate(self, func: list) -> TableSample: :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data["x"].aggregate( func = ["min", "approx_10%", "approx_50%", "approx_90%", "max"], ) @@ -3436,10 +3601,10 @@ def aggregate(self, func: list) -> TableSample: .. note:: All the calculations are pushed to the database. .. seealso:: - | :py:mod:`verticapy.vDataFrame.aggregate` : Aggregations for specific columns. - | :py:mod:`verticapy.vDataColumn.describe` : + | :py:meth:`verticapy.vDataFrame.aggregate` : Aggregations for specific columns. + | :py:meth:`verticapy.vDataColumn.describe` : Summarizes the information within the column. - | :py:mod:`verticapy.vDataFrame.describe` : + | :py:meth:`verticapy.vDataFrame.describe` : Summarizes the information for specific columns. """ return self._parent.aggregate(func=func, columns=[self._alias]).transpose() @@ -3467,19 +3632,24 @@ def describe( Parameters ---------- method: str, optional - | The describe method. - - | **auto**: Sets the method to ``numerical`` if - the vDataColumn is numerical, - ``categorical`` otherwise. - | **categorical**: Uses only categorical aggregations - during the computation. - | **cat_stats**: Computes statistics of a numerical - column for each vDataColumn category. - In this case, the parameter ``numcol`` - must be defined. - | **numerical**: Uses popular numerical aggregations - during the computation. + The describe method. + + - auto: + Sets the method to ``numerical`` if + the vDataColumn is numerical, + ``categorical`` otherwise. + - categorical: + Uses only categorical aggregations + during the computation. + - cat_stats: + Computes statistics of a numerical + column for each vDataColumn category. + In this case, the parameter ``numcol`` + must be defined. + - numerical: + Uses popular numerical aggregations + during the computation. + max_cardinality: int, optional Cardinality threshold to use to determine if the vDataColumn is considered as categorical. @@ -3500,12 +3670,14 @@ def describe( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - "c": ['A', 'A', 'A', 'A', 'B', 'B', 'C', 'D'], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + "c": ['A', 'A', 'A', 'A', 'B', 'B', 'C', 'D'], + } + ) The ``describe`` method provides you with a variety of statistical methods. @@ -3521,12 +3693,14 @@ def describe( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - "c": ['A', 'A', 'A', 'A', 'B', 'B', 'C', 'D'], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + "c": ['A', 'A', 'A', 'A', 'B', 'B', 'C', 'D'], + } + ) result = data["x"].describe(method = "numerical") html_file = open("SPHINX_DIRECTORY/figures/core_vDataFrame_vDCAgg_describe_num_table.html", "w") html_file.write(result._repr_html_()) @@ -3546,12 +3720,14 @@ def describe( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - "c": ['A', 'A', 'A', 'A', 'B', 'B', 'C', 'D'], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + "c": ['A', 'A', 'A', 'A', 'B', 'B', 'C', 'D'], + } + ) result = data["x"].describe(method = "categorical") html_file = open("SPHINX_DIRECTORY/figures/core_vDataFrame_vDCAgg_describe_cat_table.html", "w") html_file.write(result._repr_html_()) @@ -3574,15 +3750,17 @@ def describe( :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - "c": ['A', 'A', 'A', 'A', 'B', 'B', 'C', 'D'], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + "c": ['A', 'A', 'A', 'A', 'B', 'B', 'C', 'D'], + } + ) result = data["c"].describe( method = "cat_stats", - numcol = "x" + numcol = "x", ) html_file = open("SPHINX_DIRECTORY/figures/core_vDataFrame_vDCAgg_describe_stats_table.html", "w") html_file.write(result._repr_html_()) @@ -3594,9 +3772,9 @@ def describe( .. note:: All the calculations are pushed to the database. .. seealso:: - | :py:mod:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. - | :py:mod:`verticapy.vDataFrame.aggregate` : Aggregations for specific columns. - | :py:mod:`verticapy.vDataFrame.describe` : + | :py:meth:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. + | :py:meth:`verticapy.vDataFrame.aggregate` : Aggregations for specific columns. + | :py:meth:`verticapy.vDataFrame.describe` : Summarizes information within the columns. """ assert (method != "cat_stats") or (numcol), ValueError( @@ -3777,11 +3955,13 @@ def aad(self) -> PythonScalar: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data["x"].aad() .. note:: All the calculations are pushed to the database. @@ -3789,9 +3969,9 @@ def aad(self) -> PythonScalar: .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.aad` : + | :py:meth:`verticapy.vDataColumn.aad` : Standard Deviation for a specific column. - | :py:mod:`verticapy.vDataFrame.aad` : + | :py:meth:`verticapy.vDataFrame.aad` : Average Absolute Deviation for particular columns. """ return self.aggregate(["aad"]).values[self._alias][0] @@ -3819,11 +3999,13 @@ def avg(self) -> PythonScalar: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data["x"].avg() .. note:: All the calculations are pushed to the database. @@ -3831,9 +4013,9 @@ def avg(self) -> PythonScalar: .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataFrame.avg` : Aggregations for particular columns. - | :py:mod:`verticapy.vDataFrame.max` : Maximum for particular columns. - | :py:mod:`verticapy.vDataFrame.min` : Minimum for particular columns. + | :py:meth:`verticapy.vDataFrame.avg` : Aggregations for particular columns. + | :py:meth:`verticapy.vDataFrame.max` : Maximum for particular columns. + | :py:meth:`verticapy.vDataFrame.min` : Minimum for particular columns. """ return self.aggregate(["avg"]).values[self._alias][0] @@ -3861,11 +4043,13 @@ def count(self) -> int: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data["x"].count() .. note:: All the calculations are pushed to the database. @@ -3873,8 +4057,8 @@ def count(self) -> int: .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataFrame.count` : Count for particular columns. - | :py:mod:`verticapy.vDataFrame.count_percent` : + | :py:meth:`verticapy.vDataFrame.count` : Count for particular columns. + | :py:meth:`verticapy.vDataFrame.count_percent` : Percentage count for particular columns. """ return self.aggregate(["count"]).values[self._alias][0] @@ -3913,11 +4097,13 @@ def kurtosis(self) -> PythonScalar: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data["x"].kurtosis() .. note:: All the calculations are pushed to the database. @@ -3925,8 +4111,8 @@ def kurtosis(self) -> PythonScalar: .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.std` : Standard Deviation for a specific column. - | :py:mod:`verticapy.vDataFrame.kurtosis` : Kurtosis for particular columns. + | :py:meth:`verticapy.vDataColumn.std` : Standard Deviation for a specific column. + | :py:meth:`verticapy.vDataFrame.kurtosis` : Kurtosis for particular columns. """ return self.aggregate(["kurtosis"]).values[self._alias][0] @@ -3971,11 +4157,13 @@ def mad(self) -> PythonScalar: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data["x"].mad() .. note:: All the calculations are pushed to the database. @@ -3983,8 +4171,8 @@ def mad(self) -> PythonScalar: .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.std` : Standard Deviation for a specific column. - | :py:mod:`verticapy.vDataFrame.mad` : Mean Absolute Deviation for particular columns. + | :py:meth:`verticapy.vDataColumn.std` : Standard Deviation for a specific column. + | :py:meth:`verticapy.vDataFrame.mad` : Mean Absolute Deviation for particular columns. """ return self.aggregate(["mad"]).values[self._alias][0] @@ -4011,11 +4199,13 @@ def max(self) -> PythonScalar: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data["x"].max() .. note:: All the calculations are pushed to the database. @@ -4023,8 +4213,8 @@ def max(self) -> PythonScalar: .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataFrame.max` : Maximum for particular columns. - | :py:mod:`verticapy.vDataColumn.min` : Minimum for a specific column. + | :py:meth:`verticapy.vDataFrame.max` : Maximum for particular columns. + | :py:meth:`verticapy.vDataColumn.min` : Minimum for a specific column. """ return self.aggregate(["max"]).values[self._alias][0] @@ -4068,11 +4258,13 @@ def median( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data["x"].median(approx = True) .. note:: All the calculations are pushed to the database. @@ -4080,8 +4272,8 @@ def median( .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.mean` : Mean for a specific column. - | :py:mod:`verticapy.vDataFrame.median` : Median for particular columns. + | :py:meth:`verticapy.vDataColumn.mean` : Mean for a specific column. + | :py:meth:`verticapy.vDataFrame.median` : Median for particular columns. """ return self.quantile(0.5, approx=approx) @@ -4108,11 +4300,13 @@ def min(self) -> PythonScalar: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data["x"].min() .. note:: All the calculations are pushed to the database. @@ -4120,8 +4314,8 @@ def min(self) -> PythonScalar: .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.max` : Maximum for a specific column. - | :py:mod:`verticapy.vDataFrame.min` : Minimum for particular columns. + | :py:meth:`verticapy.vDataColumn.max` : Maximum for a specific column. + | :py:meth:`verticapy.vDataFrame.min` : Minimum for particular columns. """ return self.aggregate(["min"]).values[self._alias][0] @@ -4166,11 +4360,13 @@ def product(self) -> PythonScalar: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data["x"].product() .. note:: All the calculations are pushed to the database. @@ -4178,8 +4374,8 @@ def product(self) -> PythonScalar: .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. - | :py:mod:`verticapy.vDataColumn.quantile` : Quantile Aggregates for a specific column. + | :py:meth:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. + | :py:meth:`verticapy.vDataColumn.quantile` : Quantile Aggregates for a specific column. """ return self.aggregate(func=["prod"]).values[self._alias][0] @@ -4236,11 +4432,13 @@ def quantile(self, q: PythonNumber, approx: bool = True) -> PythonScalar: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data["x"].quantile(q = 0.5, approx = True) Let's compute the approximate last decile of a column. @@ -4254,8 +4452,8 @@ def quantile(self, q: PythonNumber, approx: bool = True) -> PythonScalar: .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. - | :py:mod:`verticapy.vDataFrame.aggregate` : Aggregates for particular columns. + | :py:meth:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. + | :py:meth:`verticapy.vDataFrame.aggregate` : Aggregates for particular columns. """ prefix = "approx_" if approx else "" return self.aggregate(func=[f"{prefix}{q * 100}%"]).values[self._alias][0] @@ -4301,11 +4499,13 @@ def sem(self) -> PythonScalar: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data["x"].sem() .. note:: All the calculations are pushed to the database. @@ -4313,8 +4513,8 @@ def sem(self) -> PythonScalar: .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.mad` : Mean Absolute Deviation for a specific column. - | :py:mod:`verticapy.vDataFrame.sem` : Standard Error of Mean for particular columns. + | :py:meth:`verticapy.vDataColumn.mad` : Mean Absolute Deviation for a specific column. + | :py:meth:`verticapy.vDataFrame.sem` : Standard Error of Mean for particular columns. """ return self.aggregate(["sem"]).values[self._alias][0] @@ -4351,11 +4551,13 @@ def skewness(self) -> PythonScalar: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data["x"].skewness() .. note:: All the calculations are pushed to the database. @@ -4363,9 +4565,9 @@ def skewness(self) -> PythonScalar: .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.kurtosis` : Kurtosis for a specific column. - | :py:mod:`verticapy.vDataFrame.skewness` : Skewness for particular columns. - | :py:mod:`verticapy.vDataFrame.std` : Standard Deviation for particular columns. + | :py:meth:`verticapy.vDataColumn.kurtosis` : Kurtosis for a specific column. + | :py:meth:`verticapy.vDataFrame.skewness` : Skewness for particular columns. + | :py:meth:`verticapy.vDataFrame.std` : Standard Deviation for particular columns. """ return self.aggregate(["skewness"]).values[self._alias][0] @@ -4395,11 +4597,13 @@ def std(self) -> PythonScalar: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data["x"].std() .. note:: All the calculations are pushed to the database. @@ -4407,9 +4611,9 @@ def std(self) -> PythonScalar: .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.kurtosis` : Kurtosis for a specific column. - | :py:mod:`verticapy.vDataFrame.skewness` : Skewness for particular columns. - | :py:mod:`verticapy.vDataFrame.std` : Standard Deviation for particular columns. + | :py:meth:`verticapy.vDataColumn.kurtosis` : Kurtosis for a specific column. + | :py:meth:`verticapy.vDataFrame.skewness` : Skewness for particular columns. + | :py:meth:`verticapy.vDataFrame.std` : Standard Deviation for particular columns. """ return self.aggregate(["stddev"]).values[self._alias][0] @@ -4436,11 +4640,13 @@ def sum(self) -> PythonScalar: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data["x"].sum() .. note:: All the calculations are pushed to the database. @@ -4448,8 +4654,8 @@ def sum(self) -> PythonScalar: .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataFrame.sum` : Sum for particular columns. - | :py:mod:`verticapy.vDataColumn.max` : Maximum for a specific colum. + | :py:meth:`verticapy.vDataFrame.sum` : Sum for particular columns. + | :py:meth:`verticapy.vDataColumn.max` : Maximum for a specific colum. """ return self.aggregate(["sum"]).values[self._alias][0] @@ -4477,11 +4683,13 @@ def var(self) -> PythonScalar: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data["x"].sum() .. note:: All the calculations are pushed to the database. @@ -4489,8 +4697,8 @@ def var(self) -> PythonScalar: .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. - | :py:mod:`verticapy.vDataFrame.aggregate` : Aggregates for particular columns. + | :py:meth:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. + | :py:meth:`verticapy.vDataFrame.aggregate` : Aggregates for particular columns. """ return self.aggregate(["variance"]).values[self._alias][0] @@ -4539,11 +4747,13 @@ def mode(self, dropna: bool = False, n: int = 1) -> PythonScalar: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data["y"].mode() Let's now return the second most frequent element: @@ -4557,8 +4767,8 @@ def mode(self, dropna: bool = False, n: int = 1) -> PythonScalar: .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.mean` : Mean for a specific column. - | :py:mod:`verticapy.vDataFrame.median` : Median for particular columns. + | :py:meth:`verticapy.vDataColumn.mean` : Mean for a specific column. + | :py:meth:`verticapy.vDataFrame.median` : Median for particular columns. """ if n == 1: pre_comp = self._parent._get_catalog_value(self._alias, "top") @@ -4621,11 +4831,13 @@ def value_counts(self, k: int = 30) -> TableSample: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let's calculate the values and counts for a specific column. @@ -4638,11 +4850,13 @@ def value_counts(self, k: int = 30) -> TableSample: :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data["x"].value_counts(k = 6) html_file = open("SPHINX_DIRECTORY/figures/core_vDataFrame_vDFAgg_value_counts_table.html", "w") html_file.write(result._repr_html_()) @@ -4656,8 +4870,8 @@ def value_counts(self, k: int = 30) -> TableSample: .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.nunique` : Cardinality for a specific column. - | :py:mod:`verticapy.vDataFrame.duplicated` : Duplicated values for particular columns. + | :py:meth:`verticapy.vDataColumn.nunique` : Cardinality for a specific column. + | :py:meth:`verticapy.vDataFrame.duplicated` : Duplicated values for particular columns. """ return self.describe(method="categorical", max_cardinality=k) @@ -4691,11 +4905,13 @@ def topk(self, k: int = -1, dropna: bool = True) -> TableSample: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) Now, let's calculate the top k values for a specific column. @@ -4708,11 +4924,13 @@ def topk(self, k: int = -1, dropna: bool = True) -> TableSample: :suppress: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) result = data["x"].topk() html_file = open("SPHINX_DIRECTORY/figures/core_vDataFrame_vDFAgg_topk_table.html", "w") html_file.write(result._repr_html_()) @@ -4726,8 +4944,8 @@ def topk(self, k: int = -1, dropna: bool = True) -> TableSample: .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.nunique` : Cardinality for a specific column. - | :py:mod:`verticapy.vDataFrame.nunique` : Cardinality for particular columns. + | :py:meth:`verticapy.vDataColumn.nunique` : Cardinality for a specific column. + | :py:meth:`verticapy.vDataFrame.nunique` : Cardinality for particular columns. """ limit, where, topk_cat = "", "", "" if k >= 1: @@ -4783,11 +5001,13 @@ def distinct(self, **kwargs) -> list: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data["y"].distinct() .. note:: All the calculations are pushed to the database. @@ -4795,8 +5015,8 @@ def distinct(self, **kwargs) -> list: .. hint:: For more precise control, please refer to the ``aggregate`` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. - | :py:mod:`verticapy.vDataFrame.aggregate` : Aggregates for particular columns. + | :py:meth:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. + | :py:meth:`verticapy.vDataFrame.aggregate` : Aggregates for particular columns. """ alias_sql_repr = to_varchar(self.category(), self._alias) if "agg" not in kwargs: @@ -4875,11 +5095,13 @@ def nunique(self, approx: bool = True) -> int: import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data["y"].nunique() .. note:: All the calculations are pushed to the database. @@ -4887,8 +5109,8 @@ def nunique(self, approx: bool = True) -> int: .. hint:: For more precise control, please refer to the `aggregate` method. .. seealso:: - | :py:mod:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. - | :py:mod:`verticapy.vDataFrame.aggregate` : Aggregates for particular columns. + | :py:meth:`verticapy.vDataColumn.aggregate` : Aggregations for a specific column. + | :py:meth:`verticapy.vDataFrame.aggregate` : Aggregates for particular columns. """ if approx: return self.aggregate(func=["approx_unique"]).values[self._alias][0] diff --git a/verticapy/core/vdataframe/_corr.py b/verticapy/core/vdataframe/_corr.py index a77e54978..274706174 100755 --- a/verticapy/core/vdataframe/_corr.py +++ b/verticapy/core/vdataframe/_corr.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -772,28 +772,35 @@ def corr( List of the vDataColumns names. If empty, all numerical vDataColumns are used. method: str, optional - | Method to use to compute the correlation. - - | **pearson**: Pearson's correlation coefficient (linear). - | **spearman**: Spearman's correlation coefficient (monotonic - - rank based). - | **spearmanD**: Spearman's correlation coefficient using the - DENSE RANK function instead of the RANK - function. - | **kendall**: Kendall's correlation coefficient (similar - trends). The method computes the Tau-B - coefficient. - - .. warning:: - - This method uses a CROSS JOIN during computation - and is therefore computationally expensive - at O(n * n), where n is the total count of the - ``vDataFrame``. - - | **cramer**: Cramer's V (correlation between categories). - | **biserial**: Biserial Point (correlation between binaries - and a numericals). + Method to use to compute the correlation. + + - pearson: + Pearson's correlation coefficient (linear). + - spearman: + Spearman's correlation coefficient (monotonic + - rank based). + - spearmanD: + Spearman's correlation coefficient using the + DENSE RANK function instead of the RANK + function. + - kendall: + Kendall's correlation coefficient (similar + trends). The method computes the Tau-B + coefficient. + + .. warning:: + + This method uses a CROSS JOIN during computation + and is therefore computationally expensive + at O(n * n), where n is the total count of the + :py:class:`vDataFrame`. + + - cramer: + Cramer's V (correlation between categories). + - biserial: + Biserial Point (correlation between binaries + and a numericals). + mround: int, optional Rounds the coefficient using the input number of digits. This is only used to display the correlation @@ -834,12 +841,14 @@ def corr( N = 30 # Number of records - data = vp.vDataFrame({ - "score1": np.random.normal(5, 1, N), - "score2": np.random.normal(8, 1.5, N), - "score3": np.random.normal(10, 2, N), - "score4": np.random.normal(14, 3, N), - }) + data = vp.vDataFrame( + { + "score1": np.random.normal(5, 1, N), + "score2": np.random.normal(8, 1.5, N), + "score3": np.random.normal(10, 2, N), + "score4": np.random.normal(14, 3, N), + } + ) Draw the Pearson correlation matrix. @@ -854,12 +863,14 @@ def corr( import numpy as np vp.set_option("plotting_lib", "plotly") N = 30 # Number of records - data = vp.vDataFrame({ - "score1": np.random.normal(5, 1, N), - "score2": np.random.normal(8, 1.5, N), - "score3": np.random.normal(10, 2, N), - "score4": np.random.normal(14, 3, N), - }) + data = vp.vDataFrame( + { + "score1": np.random.normal(5, 1, N), + "score2": np.random.normal(8, 1.5, N), + "score3": np.random.normal(10, 2, N), + "score4": np.random.normal(14, 3, N), + } + ) fig = data.corr(method = "pearson") fig.write_html("SPHINX_DIRECTORY/figures/core_vDataFrame_vDFCorr_corr_matrix.html") @@ -888,7 +899,7 @@ def corr( :ref:`chart_gallery`. .. seealso:: - | :py:mod:`verticapy.vDataFrame.corr_pvalue` : Computes correlation and its p-value. + | :py:meth:`verticapy.vDataFrame.corr_pvalue` : Computes correlation and its p-value. """ method = str(method).lower() columns = format_type(columns, dtype=list, na_out=self.numcol()) @@ -939,28 +950,34 @@ def corr_pvalue( column2: str Input vDataColumn. method: str, optional - | Method to use to compute the correlation. - - | **pearson**: Pearson's correlation coefficient (linear). - | **spearman**: Spearman's correlation coefficient (monotonic - - rank based). - | **spearmanD**: Spearman's correlation coefficient using the - DENSE RANK function instead of the RANK - function. - | **kendall**: Kendall's correlation coefficient (similar - trends). The method computes the Tau-B - coefficient. - - .. warning:: - - This method uses a CROSS JOIN during computation - and is therefore computationally expensive - at O(n * n), where n is the total count of the - ``vDataFrame``. - - | **cramer**: Cramer's V (correlation between categories). - | **biserial**: Biserial Point (correlation between binaries - and a numericals). + Method to use to compute the correlation. + + - pearson: + Pearson's correlation coefficient (linear). + - spearman: + Spearman's correlation coefficient (monotonic + - rank based). + - spearmanD: + Spearman's correlation coefficient using the + DENSE RANK function instead of the RANK + function. + - kendall: + Kendall's correlation coefficient (similar + trends). The method computes the Tau-B + coefficient. + + .. warning:: + + This method uses a CROSS JOIN during computation + and is therefore computationally expensive + at O(n * n), where n is the total count of the + :py:class:`vDataFrame`. + - cramer: + Cramer's V (correlation between categories). + - biserial: + Biserial Point (correlation between binaries + and a numericals). + Returns ------- tuple @@ -976,11 +993,13 @@ def corr_pvalue( import verticapy as vp - data = vp.vDataFrame({ - "x": [1, 2, 4, 9, 10, 15, 20, 22], - "y": [1, 2, 1, 2, 1, 1, 2, 1], - "z": [10, 12, 2, 1, 9, 8, 1, 3], - }) + data = vp.vDataFrame( + { + "x": [1, 2, 4, 9, 10, 15, 20, 22], + "y": [1, 2, 1, 2, 1, 1, 2, 1], + "z": [10, 12, 2, 1, 9, 8, 1, 3], + } + ) data.corr_pvalue( column1 = "x", column2 = "y", @@ -988,7 +1007,7 @@ def corr_pvalue( ) .. seealso:: - | :py:mod:`verticapy.vDataFrame.corr` : Computes the correlation matrix. + | :py:meth:`verticapy.vDataFrame.corr` : Computes the correlation matrix. """ method = str(method).lower() column1, column2 = self.format_colnames(column1, column2) @@ -1203,12 +1222,14 @@ def cov( N = 30 # Number of records - data = vp.vDataFrame({ - "score1": np.random.normal(5, 1, N), - "score2": np.random.normal(8, 1.5, N), - "score3": np.random.normal(10, 2, N), - "score4": np.random.normal(14, 3, N), - }) + data = vp.vDataFrame( + { + "score1": np.random.normal(5, 1, N), + "score2": np.random.normal(8, 1.5, N), + "score3": np.random.normal(10, 2, N), + "score4": np.random.normal(14, 3, N), + } + ) Draw the covariance matrix. @@ -1223,12 +1244,14 @@ def cov( import numpy as np vp.set_option("plotting_lib", "plotly") N = 30 # Number of records - data = vp.vDataFrame({ - "score1": np.random.normal(5, 1, N), - "score2": np.random.normal(8, 1.5, N), - "score3": np.random.normal(10, 2, N), - "score4": np.random.normal(14, 3, N), - }) + data = vp.vDataFrame( + { + "score1": np.random.normal(5, 1, N), + "score2": np.random.normal(8, 1.5, N), + "score3": np.random.normal(10, 2, N), + "score4": np.random.normal(14, 3, N), + } + ) fig = data.cov() fig.write_html("SPHINX_DIRECTORY/figures/core_vDataFrame_vDFCorr_cov_matrix.html") @@ -1258,7 +1281,7 @@ def cov( customization stays the same for the covariance matrix. .. seealso:: - | :py:mod:`verticapy.vDataFrame.corr` : Computes the correlation matrix. + | :py:meth:`verticapy.vDataFrame.corr` : Computes the correlation matrix. """ columns = format_type(columns, dtype=list) columns, focus = self.format_colnames(columns, focus) @@ -1314,26 +1337,37 @@ def regr( List of the vDataColumns names. If empty, all numerical vDataColumns are used. method: str, optional - | Method to use to compute the regression matrix. - - | **avgx**: Average of the independent expression in - an expression pair. - | **avgy**: Average of the dependent expression in an - expression pair. - | **count**: Count of all rows in an expression pair. - | **alpha**: Intercept of the regression line determined - by a set of expression pairs. - | **r2**: Square of the correlation coefficient of a set - of expression pairs. - | **beta**: Slope of the regression line, determined by a - set of expression pairs. - | **sxx**: Sum of squares of the independent expression in - an expression pair. - | **sxy**: Sum of products of the independent expression - multiplied by the dependent expression in an - expression pair. - | **syy**: Returns the sum of squares of the dependent - expression in an expression pair. + + Method to use to compute the regression matrix. + + - avgx: + Average of the independent expression in + an expression pair. + - avgy: + Average of the dependent expression in an + expression pair. + - count: + Count of all rows in an expression pair. + - alpha: + Intercept of the regression line determined + by a set of expression pairs. + - r2: + Square of the correlation coefficient of a set + of expression pairs. + - beta: + Slope of the regression line, determined by a + set of expression pairs. + - sxx: + Sum of squares of the independent expression in + an expression pair. + - sxy: + Sum of products of the independent expression + multiplied by the dependent expression in an + expression pair. + - syy: + Returns the sum of squares of the dependent + expression in an expression pair. + show: bool, optional If set to True, the Plotting object is returned. chart: PlottingObject, optional @@ -1366,12 +1400,14 @@ def regr( N = 30 # Number of records - data = vp.vDataFrame({ - "score1": np.random.normal(5, 1, N), - "score2": np.random.normal(8, 1.5, N), - "score3": np.random.normal(10, 2, N), - "score4": np.random.normal(14, 3, N), - }) + data = vp.vDataFrame( + { + "score1": np.random.normal(5, 1, N), + "score2": np.random.normal(8, 1.5, N), + "score3": np.random.normal(10, 2, N), + "score4": np.random.normal(14, 3, N), + } + ) Draw the regression matrix using the Beta coefficient. @@ -1386,12 +1422,14 @@ def regr( import numpy as np vp.set_option("plotting_lib", "plotly") N = 30 # Number of records - data = vp.vDataFrame({ - "score1": np.random.normal(5, 1, N), - "score2": np.random.normal(8, 1.5, N), - "score3": np.random.normal(10, 2, N), - "score4": np.random.normal(14, 3, N), - }) + data = vp.vDataFrame( + { + "score1": np.random.normal(5, 1, N), + "score2": np.random.normal(8, 1.5, N), + "score3": np.random.normal(10, 2, N), + "score4": np.random.normal(14, 3, N), + } + ) fig = data.regr(method = "beta") fig.write_html("SPHINX_DIRECTORY/figures/core_vDataFrame_vDFCorr_regr_beta_matrix.html") @@ -1411,12 +1449,14 @@ def regr( import numpy as np vp.set_option("plotting_lib", "plotly") N = 30 # Number of records - data = vp.vDataFrame({ - "score1": np.random.normal(5, 1, N), - "score2": np.random.normal(8, 1.5, N), - "score3": np.random.normal(10, 2, N), - "score4": np.random.normal(14, 3, N), - }) + data = vp.vDataFrame( + { + "score1": np.random.normal(5, 1, N), + "score2": np.random.normal(8, 1.5, N), + "score3": np.random.normal(10, 2, N), + "score4": np.random.normal(14, 3, N), + } + ) fig = data.regr(method = "alpha") fig.write_html("SPHINX_DIRECTORY/figures/core_vDataFrame_vDFCorr_regr_alpha_matrix.html") @@ -1436,12 +1476,14 @@ def regr( import numpy as np vp.set_option("plotting_lib", "plotly") N = 30 # Number of records - data = vp.vDataFrame({ - "score1": np.random.normal(5, 1, N), - "score2": np.random.normal(8, 1.5, N), - "score3": np.random.normal(10, 2, N), - "score4": np.random.normal(14, 3, N), - }) + data = vp.vDataFrame( + { + "score1": np.random.normal(5, 1, N), + "score2": np.random.normal(8, 1.5, N), + "score3": np.random.normal(10, 2, N), + "score4": np.random.normal(14, 3, N), + } + ) fig = data.regr(method = "r2") fig.write_html("SPHINX_DIRECTORY/figures/core_vDataFrame_vDFCorr_regr_r2_matrix.html") @@ -1453,7 +1495,7 @@ def regr( customization stays the same for the regression matrix. .. seealso:: - | :py:mod:`verticapy.vDataFrame.corr` : Computes the correlation matrix. + | :py:meth:`verticapy.vDataFrame.corr` : Computes the correlation matrix. """ columns = format_type(columns, dtype=list) if method == "beta": @@ -1612,37 +1654,46 @@ def acf( different lags to include during the computation. p must be positive or a list of positive integers. unit: str, optional - | Unit used to compute the lags. + Unit used to compute the lags. + + - rows: + Natural lags. + - else: + Any time unit. For example, you can + write 'hour' to compute the hours + lags or 'day' to compute the days + lags. - | **rows**: Natural lags - | **else**: Any time unit. For example, you can - write 'hour' to compute the hours - lags or 'day' to compute the days - lags. method: str, optional - | Method used to compute the correlation. - - | **pearson**: Pearson's correlation coefficient - (linear). - | **spearman**: Spearman's correlation coefficient - (monotonic - rank based). - | **spearmanD**: Spearman's correlation coefficient - using the DENSE RANK function - instead of the RANK function. - | **kendall**: Kendall's correlation coefficient - (similar trends). The method - computes the Tau-B coefficient. - - .. warning:: - - This method uses a CROSS JOIN during computation - and is therefore computationally expensive - at O(n * n), where n is the total count of the - ``vDataFrame``. - - | **cramer**: Cramer's V (correlation between categories). - | **biserial**: Biserial Point (correlation between binaries - and a numericals). + Method used to compute the correlation. + + - pearson: + Pearson's correlation coefficient + (linear). + - spearman: + Spearman's correlation coefficient + (monotonic - rank based). + - spearmanD: + Spearman's correlation coefficient + using the DENSE RANK function + instead of the RANK function. + - kendall: + Kendall's correlation coefficient + (similar trends). The method + computes the Tau-B coefficient. + + .. warning:: + + This method uses a CROSS JOIN during computation + and is therefore computationally expensive + at O(n * n), where n is the total count of the + :py:class:`vDataFrame`. + - cramer: + Cramer's V (correlation between categories). + - biserial: + Biserial Point (correlation between binaries + and a numericals). + confidence: bool, optional If set to True, the confidence band width is drawn. alpha: float, optional @@ -1652,11 +1703,15 @@ def acf( If set to True, the Plotting object is returned. kind: str, optional - | ACF Type. + ACF Type. + + - bar: + Classical Autocorrelation Plot using bars. + - heatmap: + Draws the ACF heatmap. + - line: + Draws the ACF using a Line Plot. - | **bar**: Classical Autocorrelation Plot using bars. - | **heatmap**: Draws the ACF heatmap. - | **line**: Draws the ACF using a Line Plot. mround: int, optional Round the coefficient using the input number of digits. It is used only to display the ACF Matrix @@ -1722,7 +1777,7 @@ def acf( :ref:`chart_gallery`. .. seealso:: - | :py:mod:`verticapy.vDataFrame.pacf` : Computes the partial autocorrelations. + | :py:meth:`verticapy.vDataFrame.pacf` : Computes the partial autocorrelations. """ method = str(method).lower() by = format_type(by, dtype=list) @@ -1839,50 +1894,62 @@ def pacf( different lags to include during the computation. p must be positive or a list of positive integers. unit: str, optional - | Unit used to compute the lags. + Unit used to compute the lags. + + - rows: + Natural lags. + - else: + Any time unit. For example, you can + write 'hour' to compute the hours + lags or 'day' to compute the days + lags. - | **rows**: Natural lags - | **else**: Any time unit. For example, you can - write 'hour' to compute the hours - lags or 'day' to compute the days - lags. method: str, optional - | Method used to compute the correlation. - - | **pearson**: Pearson's correlation coefficient - (linear). - | **spearman**: Spearman's correlation coefficient - (monotonic - rank based). - | **spearmanD**: Spearman's correlation coefficient - using the DENSE RANK function - instead of the RANK function. - | **kendall**: Kendall's correlation coefficient - (similar trends). The method - computes the Tau-B coefficient. - - .. warning:: - - This method uses a CROSS JOIN during computation - and is therefore computationally expensive - at O(n * n), where n is the total count of the - ``vDataFrame``. - - | **cramer**: Cramer's V (correlation between categories). - | **biserial**: Biserial Point (correlation between binaries - and a numericals). + Method used to compute the correlation. + + - pearson: + Pearson's correlation coefficient + (linear). + - spearman: + Spearman's correlation coefficient + (monotonic - rank based). + - spearmanD: + Spearman's correlation coefficient + using the DENSE RANK function + instead of the RANK function. + - kendall: + Kendall's correlation coefficient + (similar trends). The method computes + the Tau-B coefficient. + + .. warning:: + + This method uses a CROSS JOIN during computation + and is therefore computationally expensive + at O(n * n), where n is the total count of the + :py:class:`vDataFrame`. + - cramer: + Cramer's V (correlation between categories). + - biserial: + Biserial Point (correlation between binaries + and a numericals). + confidence: bool, optional If set to True, the confidence band width is drawn. alpha: float, optional Significance Level. Probability to accept H0. Only used to compute the confidence band width. show: bool, optional - If set to True, the Plotting object is - returned. + If set to True, the Plotting object is + returned. kind: str, optional - | PACF Type. + PACF Type. + + - bar: + Classical Partial Autocorrelation Plot using bars. + - line: + Draws the PACF using a Line Plot. - | **bar**: Classical Partial Autocorrelation Plot using bars. - | **line**: Draws the PACF using a Line Plot. chart: PlottingObject, optional The chart object used to plot. **style_kwargs @@ -1945,7 +2012,7 @@ def pacf( stays the same for the PACF plot. .. seealso:: - | :py:mod:`verticapy.vDataFrame.acf` : Computes the autocorrelations. + | :py:meth:`verticapy.vDataFrame.acf` : Computes the autocorrelations. """ vml = get_vertica_mllib() if isinstance(by, str): @@ -2137,7 +2204,7 @@ def iv_woe( outcomes during the Titanic disaster. .. seealso:: - | :py:mod:`verticapy.vDataColumn.iv_woe` : Computes IV / WOE table. + | :py:meth:`verticapy.vDataColumn.iv_woe` : Computes IV / WOE table. """ columns = format_type(columns, dtype=list) columns, y = self.format_colnames(columns, y) @@ -2240,7 +2307,7 @@ def iv_woe(self, y: str, nbins: int = 10) -> TableSample: -making. .. seealso:: - | :py:mod:`verticapy.vDataFrame.iv_woe` : Draw IV Plot. + | :py:meth:`verticapy.vDataFrame.iv_woe` : Draw IV Plot. """ y = self._parent.format_colnames(y) assert self._parent[y].nunique() == 2, TypeError( diff --git a/verticapy/core/vdataframe/_encoding.py b/verticapy/core/vdataframe/_encoding.py index bb6f7109a..65258880e 100755 --- a/verticapy/core/vdataframe/_encoding.py +++ b/verticapy/core/vdataframe/_encoding.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -67,7 +67,7 @@ def case_when(self, name: str, *args) -> "vDataFrame": Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -75,7 +75,7 @@ def case_when(self, name: str, *args) -> "vDataFrame": .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -146,8 +146,8 @@ def case_when(self, name: str, *args) -> "vDataFrame": .. seealso:: - | :py:meth:`verticapy.vDataFrame.decode` - | :py:meth:`verticapy.vDataFrame.eval` + | :py:meth:`verticapy.vDataFrame.decode` : User Defined Encoding. + | :py:meth:`verticapy.vDataFrame.eval` : Evaluates an expression. """ return self.eval(name=name, expr=case_when(*args)) @@ -193,7 +193,7 @@ def one_hot_encode( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -201,7 +201,7 @@ def one_hot_encode( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -320,10 +320,10 @@ def one_hot_encode( .. seealso:: - | :py:meth:`verticapy.vDataFrame.decode` - | :py:meth:`verticapy.vDataFrame.label_encode` - | :py:meth:`verticapy.vDataFrame.mean_encode` - | :py:meth:`verticapy.vDataFrame.discretize` + | :py:meth:`verticapy.vDataFrame.decode` : User Defined Encoding. + | :py:meth:`verticapy.vDataFrame.label_encode` : Label Encoding. + | :py:meth:`verticapy.vDataFrame.mean_encode` : Mean Encoding. + | :py:meth:`verticapy.vDataFrame.discretize` : Discretization. """ columns = format_type(columns, dtype=list) columns = self.format_colnames(columns) @@ -382,7 +382,7 @@ def cut( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -390,7 +390,7 @@ def cut( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -582,10 +582,10 @@ def cut( .. seealso:: - | :py:meth:`verticapy.vDataFrame.decode` - | :py:meth:`verticapy.vDataFrame.label_encode` - | :py:meth:`verticapy.vDataFrame.mean_encode` - | :py:meth:`verticapy.vDataFrame.one_hot_encode` + | :py:meth:`verticapy.vDataFrame.decode` : User Defined Encoding. + | :py:meth:`verticapy.vDataFrame.label_encode` : Label Encoding. + | :py:meth:`verticapy.vDataFrame.mean_encode` : Mean Encoding. + | :py:meth:`verticapy.vDataFrame.one_hot_encode` : One Hot Encoding. """ labels = format_type(labels, dtype=list) assert self.isnum() or self.isdate(), TypeError( @@ -646,7 +646,7 @@ def decode(self, *args) -> "vDataFrame": Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -654,7 +654,7 @@ def decode(self, *args) -> "vDataFrame": .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -712,10 +712,10 @@ def decode(self, *args) -> "vDataFrame": .. seealso:: - | :py:meth:`verticapy.vDataFrame.case_when` - | :py:meth:`verticapy.vDataFrame.eval` - | :py:meth:`verticapy.vDataFrame.label_encode` - | :py:meth:`verticapy.vDataFrame.mean_encode` + | :py:meth:`verticapy.vDataFrame.case_when` : Conditional Statement. + | :py:meth:`verticapy.vDataFrame.eval` : Evaluates an expression. + | :py:meth:`verticapy.vDataFrame.label_encode` : Label Encoding. + | :py:meth:`verticapy.vDataFrame.mean_encode` : Mean Encoding. """ return self.apply(func=decode(StringSQL("{}"), *args)) @@ -787,7 +787,7 @@ def discretize( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -795,7 +795,7 @@ def discretize( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -988,10 +988,10 @@ def discretize( .. seealso:: - | :py:meth:`verticapy.vDataFrame.decode` - | :py:meth:`verticapy.vDataFrame.label_encode` - | :py:meth:`verticapy.vDataFrame.mean_encode` - | :py:meth:`verticapy.vDataFrame.one_hot_encode` + | :py:meth:`verticapy.vDataFrame.decode` : User Defined Encoding. + | :py:meth:`verticapy.vDataFrame.label_encode` : Label Encoding. + | :py:meth:`verticapy.vDataFrame.mean_encode` : Mean Encoding. + | :py:meth:`verticapy.vDataFrame.one_hot_encode` : One Hot Encoding. """ RFmodel_params = format_type(RFmodel_params, dtype=dict) vml = get_vertica_mllib() @@ -1193,7 +1193,7 @@ def one_hot_encode( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1201,7 +1201,7 @@ def one_hot_encode( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1295,10 +1295,10 @@ def one_hot_encode( .. seealso:: - | :py:meth:`verticapy.vDataFrame.decode` - | :py:meth:`verticapy.vDataFrame.label_encode` - | :py:meth:`verticapy.vDataFrame.mean_encode` - | :py:meth:`verticapy.vDataFrame.discretize` + | :py:meth:`verticapy.vDataFrame.decode` : User Defined Encoding. + | :py:meth:`verticapy.vDataFrame.label_encode` : Label Encoding. + | :py:meth:`verticapy.vDataFrame.mean_encode` : Mean Encoding. + | :py:meth:`verticapy.vDataFrame.discretize` : Discretization. """ distinct_elements = self.distinct() if distinct_elements not in ([0, 1], [1, 0]) or self.isbool(): @@ -1379,7 +1379,7 @@ def label_encode(self) -> "vDataFrame": Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1387,7 +1387,7 @@ def label_encode(self) -> "vDataFrame": .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1444,10 +1444,10 @@ def label_encode(self) -> "vDataFrame": .. seealso:: - | :py:meth:`verticapy.vDataFrame.decode` - | :py:meth:`verticapy.vDataFrame.mean_encode` - | :py:meth:`verticapy.vDataFrame.discretize` - | :py:meth:`verticapy.vDataFrame.one_hot_encode` + | :py:meth:`verticapy.vDataFrame.decode` : User Defined Encoding. + | :py:meth:`verticapy.vDataFrame.mean_encode` : Mean Encoding. + | :py:meth:`verticapy.vDataFrame.discretize` : Discretization. + | :py:meth:`verticapy.vDataFrame.one_hot_encode` : One Hot Encoding. """ if self.category() in ["date", "float"]: warning_message = ( @@ -1492,7 +1492,7 @@ def mean_encode(self, response: str) -> "vDataFrame": Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1500,7 +1500,7 @@ def mean_encode(self, response: str) -> "vDataFrame": .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1575,10 +1575,10 @@ def mean_encode(self, response: str) -> "vDataFrame": .. seealso:: - | :py:meth:`verticapy.vDataFrame.decode` - | :py:meth:`verticapy.vDataFrame.label_encode` - | :py:meth:`verticapy.vDataFrame.discretize` - | :py:meth:`verticapy.vDataFrame.one_hot_encode` + | :py:meth:`verticapy.vDataFrame.decode` : User Defined Encoding. + | :py:meth:`verticapy.vDataFrame.label_encode` : Label Encoding. + | :py:meth:`verticapy.vDataFrame.discretize` : Discretization. + | :py:meth:`verticapy.vDataFrame.one_hot_encode` : One Hot Encoding. """ response = self._parent.format_colnames(response) assert self._parent[response].isnum(), TypeError( diff --git a/verticapy/core/vdataframe/_eval.py b/verticapy/core/vdataframe/_eval.py index d66ea07ab..6329ce611 100755 --- a/verticapy/core/vdataframe/_eval.py +++ b/verticapy/core/vdataframe/_eval.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -84,7 +84,7 @@ def eval(self, name: str, expr: Union[str, StringSQL]) -> "vDataFrame": Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -92,7 +92,7 @@ def eval(self, name: str, expr: Union[str, StringSQL]) -> "vDataFrame": .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -220,7 +220,7 @@ def eval(self, name: str, expr: Union[str, StringSQL]) -> "vDataFrame": .. seealso:: - | :py:meth:`verticapy.vDataFrame.analytic` + | :py:meth:`verticapy.vDataFrame.analytic` : Advanced analytical function. """ if isinstance(expr, StringSQL): expr = str(expr) diff --git a/verticapy/core/vdataframe/_fill.py b/verticapy/core/vdataframe/_fill.py index e38952d93..b103cf4dc 100755 --- a/verticapy/core/vdataframe/_fill.py +++ b/verticapy/core/vdataframe/_fill.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -94,7 +94,7 @@ def fillna( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -102,7 +102,7 @@ def fillna( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -188,8 +188,8 @@ def fillna( .. seealso:: - | :py:meth:`verticapy.vDataFrame.interpolate` - | :py:meth:`verticapy.vDataColumn.fill_outliers` + | :py:meth:`verticapy.vDataFrame.interpolate` : Fill missing values by interpolating. + | :py:meth:`verticapy.vDataColumn.fill_outliers` : Fill the outliers using the input method. """ val, method = format_type(val, method, dtype=dict) print_info = conf.get_option("print_info") @@ -260,7 +260,7 @@ def interpolate( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -268,7 +268,7 @@ def interpolate( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -350,8 +350,8 @@ def interpolate( .. seealso:: - | :py:meth:`verticapy.vDataFrame.fillna` - | :py:meth:`verticapy.vDataColumn.fill_outliers` + | :py:meth:`verticapy.vDataFrame.fillna` : Fill the missing values using the input method. + | :py:meth:`verticapy.vDataColumn.fill_outliers` : Fill the outliers using the input method. """ method = format_type(method, dtype=dict) by = format_type(by, dtype=list) @@ -419,7 +419,7 @@ def clip( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -427,7 +427,7 @@ def clip( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -483,8 +483,8 @@ def clip( .. seealso:: - | :py:meth:`verticapy.vDataFrame.fillna` - | :py:meth:`verticapy.vDataColumn.fill_outliers` + | :py:meth:`verticapy.vDataFrame.fillna` : Fill the missing values using the input method. + | :py:meth:`verticapy.vDataColumn.fill_outliers` : Fill the outliers using the input method. """ assert (not isinstance(lower, NoneType)) or ( not isinstance(upper, NoneType) @@ -548,7 +548,7 @@ def fill_outliers( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -556,7 +556,7 @@ def fill_outliers( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -618,8 +618,8 @@ def fill_outliers( .. seealso:: - | :py:meth:`verticapy.vDataFrame.fillna` - | :py:meth:`verticapy.vDataColumn.fill_outliers` + | :py:meth:`verticapy.vDataFrame.fillna` : Fill the missing values using the input method. + | :py:meth:`verticapy.vDataColumn.fill_outliers` : Fill the outliers using the input method. """ if use_threshold: result = self.aggregate(func=["std", "avg"]).transpose().values @@ -749,7 +749,7 @@ def fillna( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -757,7 +757,7 @@ def fillna( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -828,8 +828,8 @@ def fillna( .. seealso:: - | :py:meth:`verticapy.vDataFrame.interpolate` - | :py:meth:`verticapy.vDataColumn.fill_outliers` + | :py:meth:`verticapy.vDataFrame.interpolate` : Fill missing values by interpolating. + | :py:meth:`verticapy.vDataColumn.fill_outliers` : Fill the outliers using the input method. """ method = method.lower() by, order_by = format_type(by, order_by, dtype=list) diff --git a/verticapy/core/vdataframe/_filter.py b/verticapy/core/vdataframe/_filter.py index 524999577..8beba1e8b 100755 --- a/verticapy/core/vdataframe/_filter.py +++ b/verticapy/core/vdataframe/_filter.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -68,7 +68,7 @@ def at_time(self, ts: str, time: TimeInterval) -> "vDataFrame": Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -76,7 +76,7 @@ def at_time(self, ts: str, time: TimeInterval) -> "vDataFrame": .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -143,8 +143,8 @@ def at_time(self, ts: str, time: TimeInterval) -> "vDataFrame": .. seealso:: - | :py:meth:`verticapy.vDataFrame.balance` - | :py:meth:`verticapy.vDataFrame.between` + | :py:meth:`verticapy.vDataFrame.balance` : Balances the vDataFrame. + | :py:meth:`verticapy.vDataFrame.between` : Filters between two conditions. """ self.filter(f"{self.format_colnames(ts)}::time = '{time}'") return self @@ -191,7 +191,7 @@ def balance( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -199,7 +199,7 @@ def balance( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -300,8 +300,8 @@ def balance( .. seealso:: - | :py:meth:`verticapy.vDataFrame.balance` - | :py:meth:`verticapy.vDataFrame.between` + | :py:meth:`verticapy.vDataFrame.balance` : Balances the vDataFrame. + | :py:meth:`verticapy.vDataFrame.between` : Filters between two conditions. """ if not 0 <= x <= 1: raise ValueError("Parameter 'x' must be between 0 and 1") @@ -371,7 +371,7 @@ def between( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -379,7 +379,7 @@ def between( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -445,8 +445,8 @@ def between( .. seealso:: - | :py:meth:`verticapy.vDataFrame.balance` - | :py:meth:`verticapy.vDataFrame.at_time` + | :py:meth:`verticapy.vDataFrame.balance` : Balances the vDataFrame. + | :py:meth:`verticapy.vDataFrame.at_time` : Filters the vDataFrame at a specific time. """ if not isinstance(start, NoneType) and not isinstance(end, NoneType): condition = f"BETWEEN '{start}' AND '{end}'" @@ -496,7 +496,7 @@ def between_time( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -504,7 +504,7 @@ def between_time( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -577,8 +577,8 @@ def between_time( .. seealso:: - | :py:meth:`verticapy.vDataFrame.between` - | :py:meth:`verticapy.vDataFrame.at_time` + | :py:meth:`verticapy.vDataFrame.between` : Filters between two conditions. + | :py:meth:`verticapy.vDataFrame.at_time` : Filters the vDataFrame at a specific time. """ if not isinstance(start_time, NoneType) and not ( isinstance(end_time, NoneType) @@ -623,7 +623,7 @@ def drop(self, columns: Optional[SQLColumns] = None) -> "vDataFrame": Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -631,7 +631,7 @@ def drop(self, columns: Optional[SQLColumns] = None) -> "vDataFrame": .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -693,8 +693,8 @@ def drop(self, columns: Optional[SQLColumns] = None) -> "vDataFrame": .. seealso:: - | :py:meth:`verticapy.vDataFrame.balance` - | :py:meth:`verticapy.vDataFrame.drop_duplicates` + | :py:meth:`verticapy.vDataFrame.balance` : Balances the vDataFrame. + | :py:meth:`verticapy.vDataFrame.drop_duplicates` : Drops the vDataFrame duplicates. """ columns = format_type(columns, dtype=list) columns = self.format_colnames(columns) @@ -731,7 +731,7 @@ def drop_duplicates(self, columns: Optional[SQLColumns] = None) -> "vDataFrame": Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -739,7 +739,7 @@ def drop_duplicates(self, columns: Optional[SQLColumns] = None) -> "vDataFrame": .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -803,8 +803,8 @@ def drop_duplicates(self, columns: Optional[SQLColumns] = None) -> "vDataFrame": .. seealso:: - | :py:meth:`verticapy.vDataFrame.balance` - | :py:meth:`verticapy.vDataFrame.drop` + | :py:meth:`verticapy.vDataFrame.balance` : Balances the vDataFrame. + | :py:meth:`verticapy.vDataFrame.drop` : Drops the vDataFrame input columns. """ columns = format_type(columns, dtype=list) count = self.duplicated(columns=columns, count=True) @@ -847,7 +847,7 @@ def dropna(self, columns: Optional[SQLColumns] = None) -> "vDataFrame": Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -855,7 +855,7 @@ def dropna(self, columns: Optional[SQLColumns] = None) -> "vDataFrame": .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -946,8 +946,8 @@ def dropna(self, columns: Optional[SQLColumns] = None) -> "vDataFrame": .. seealso:: - | :py:meth:`verticapy.vDataFrame.balance` - | :py:meth:`verticapy.vDataFrame.drop` + | :py:meth:`verticapy.vDataFrame.balance` : Balances the vDataFrame. + | :py:meth:`verticapy.vDataFrame.drop` : Drops the vDataFrame input columns. """ columns = format_type(columns, dtype=list) columns = self.format_colnames(columns) @@ -1001,7 +1001,7 @@ def filter( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1009,7 +1009,7 @@ def filter( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1077,8 +1077,8 @@ def filter( .. seealso:: - | :py:meth:`verticapy.vDataFrame.balance` - | :py:meth:`verticapy.vDataFrame.drop` + | :py:meth:`verticapy.vDataFrame.balance` : Balances the vDataFrame. + | :py:meth:`verticapy.vDataFrame.drop` : Drops the vDataFrame input columns. """ force_filter = True if "force_filter" in kwargs: @@ -1185,7 +1185,7 @@ def first(self, ts: str, offset: str) -> "vDataFrame": Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1193,7 +1193,7 @@ def first(self, ts: str, offset: str) -> "vDataFrame": .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1265,8 +1265,8 @@ def first(self, ts: str, offset: str) -> "vDataFrame": .. seealso:: - | :py:meth:`verticapy.vDataFrame.balance` - | :py:meth:`verticapy.vDataFrame.at_time` + | :py:meth:`verticapy.vDataFrame.balance` : Balances the vDataFrame. + | :py:meth:`verticapy.vDataFrame.at_time` : Filters the vDataFrame at a specific time. """ ts = self.format_colnames(ts) first_date = _executeSQL( @@ -1306,7 +1306,7 @@ def isin(self, val: dict) -> "vDataFrame": Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1314,7 +1314,7 @@ def isin(self, val: dict) -> "vDataFrame": .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1374,8 +1374,8 @@ def isin(self, val: dict) -> "vDataFrame": .. seealso:: - | :py:meth:`verticapy.vDataFrame.balance` - | :py:meth:`verticapy.vDataFrame.at_time` + | :py:meth:`verticapy.vDataFrame.balance` : Balances the vDataFrame. + | :py:meth:`verticapy.vDataFrame.at_time` : Filters the vDataFrame at a specific time. """ val = self.format_colnames(val) n = len(val[list(val.keys())[0]]) @@ -1415,7 +1415,7 @@ def last(self, ts: str, offset: str) -> "vDataFrame": Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1423,7 +1423,7 @@ def last(self, ts: str, offset: str) -> "vDataFrame": .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1495,8 +1495,8 @@ def last(self, ts: str, offset: str) -> "vDataFrame": .. seealso:: - | :py:meth:`verticapy.vDataFrame.first` - | :py:meth:`verticapy.vDataFrame.at_time` + | :py:meth:`verticapy.vDataFrame.first` : Filters the vDataFrame by only keeping the first records. + | :py:meth:`verticapy.vDataFrame.at_time` : Filters the vDataFrame at a specific time. """ ts = self.format_colnames(ts) last_date = _executeSQL( @@ -1559,7 +1559,7 @@ def sample( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1567,7 +1567,7 @@ def sample( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1671,8 +1671,8 @@ def sample( .. seealso:: - | :py:meth:`verticapy.vDataFrame.balance` - | :py:meth:`verticapy.vDataFrame.isin` + | :py:meth:`verticapy.vDataFrame.balance` : Balances the vDataFrame. + | :py:meth:`verticapy.vDataFrame.isin` : Checks whether specific records are in the vDataFrame. """ if x == 1: return self.copy() @@ -1772,7 +1772,7 @@ def search( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1780,7 +1780,7 @@ def search( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1854,8 +1854,8 @@ def search( .. seealso:: - | :py:meth:`verticapy.vDataFrame.balance` - | :py:meth:`verticapy.vDataFrame.isin` + | :py:meth:`verticapy.vDataFrame.balance` : Balances the vDataFrame. + | :py:meth:`verticapy.vDataFrame.isin` : Checks whether specific records are in the vDataFrame. """ order_by, usecols, expr = format_type(order_by, usecols, expr, dtype=list) if isinstance(conditions, Iterable) and not isinstance(conditions, str): @@ -1898,7 +1898,7 @@ def drop(self, add_history: bool = True) -> "vDataFrame": Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1906,7 +1906,7 @@ def drop(self, add_history: bool = True) -> "vDataFrame": .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1968,8 +1968,8 @@ def drop(self, add_history: bool = True) -> "vDataFrame": .. seealso:: - | :py:meth:`verticapy.vDataColumn.drop` - | :py:meth:`verticapy.vDataFrame.drop_duplicates` + | :py:meth:`verticapy.vDataColumn.drop` : Drops the input vDataColumn. + | :py:meth:`verticapy.vDataFrame.drop_duplicates` : Drops the vDataFrame duplicates. """ try: parent = self._parent @@ -2027,7 +2027,7 @@ def drop_outliers( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -2035,7 +2035,7 @@ def drop_outliers( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly knowvDC_dropn function names like "average" and "median", which can potentially lead to naming @@ -2095,8 +2095,8 @@ def drop_outliers( .. seealso:: - | :py:meth:`verticapy.vDataColumn.drop` - | :py:meth:`verticapy.vDataFrame.drop_duplicates` + | :py:meth:`verticapy.vDataColumn.drop` : Drops the input vDataColumn. + | :py:meth:`verticapy.vDataFrame.drop_duplicates` : Drops the vDataFrame duplicates. """ if use_threshold: result = self.aggregate(func=["std", "avg"]).transpose().values @@ -2127,7 +2127,7 @@ def dropna(self) -> "vDataFrame": Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -2135,7 +2135,7 @@ def dropna(self) -> "vDataFrame": .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -2228,8 +2228,8 @@ def dropna(self) -> "vDataFrame": .. seealso:: - | :py:meth:`verticapy.vDataFrame.dropna` - | :py:meth:`verticapy.vDataFrame.drop` + | :py:meth:`verticapy.vDataFrame.dropna` : Drops the vDataFrame missing values. + | :py:meth:`verticapy.vDataFrame.drop` : Drops the vDataFrame input columns. """ self._parent.filter(f"{self} IS NOT NULL") return self._parent @@ -2259,7 +2259,7 @@ def isin( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -2267,7 +2267,7 @@ def isin( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -2327,8 +2327,8 @@ def isin( .. seealso:: - | :py:meth:`verticapy.vDataFrame.balance` - | :py:meth:`verticapy.vDataFrame.at_time` + | :py:meth:`verticapy.vDataFrame.balance` : Balances the vDataFrame. + | :py:meth:`verticapy.vDataFrame.at_time` : Filters the vDataFrame at a specific time. """ if isinstance(val, str) or not isinstance(val, Iterable): val = [val] diff --git a/verticapy/core/vdataframe/_io.py b/verticapy/core/vdataframe/_io.py index b915f84f8..7d19028c2 100755 --- a/verticapy/core/vdataframe/_io.py +++ b/verticapy/core/vdataframe/_io.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/vdataframe/_join_union_sort.py b/verticapy/core/vdataframe/_join_union_sort.py index ea3731cba..1303860f5 100755 --- a/verticapy/core/vdataframe/_join_union_sort.py +++ b/verticapy/core/vdataframe/_join_union_sort.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/vdataframe/_machine_learning.py b/verticapy/core/vdataframe/_machine_learning.py index 690b348f5..0d1292f61 100755 --- a/verticapy/core/vdataframe/_machine_learning.py +++ b/verticapy/core/vdataframe/_machine_learning.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/vdataframe/_math.py b/verticapy/core/vdataframe/_math.py index 73d2fcda3..2dfe58744 100755 --- a/verticapy/core/vdataframe/_math.py +++ b/verticapy/core/vdataframe/_math.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/vdataframe/_multiprocessing.py b/verticapy/core/vdataframe/_multiprocessing.py index ec46b4290..57b73fcf9 100755 --- a/verticapy/core/vdataframe/_multiprocessing.py +++ b/verticapy/core/vdataframe/_multiprocessing.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/vdataframe/_pivot.py b/verticapy/core/vdataframe/_pivot.py index 4c952b0ed..c03c0b4b2 100755 --- a/verticapy/core/vdataframe/_pivot.py +++ b/verticapy/core/vdataframe/_pivot.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -326,7 +326,7 @@ def explode_array( must specify `delimiter` as `False`). .. seealso:: - | :py:mod:`verticapy.vDataColumn.pivot` : pivot vDataFrame. + | :py:meth:`verticapy.vDataColumn.pivot` : pivot vDataFrame. """ # Type check diff --git a/verticapy/core/vdataframe/_plotting.py b/verticapy/core/vdataframe/_plotting.py index e7c1e41aa..ea17f4a3f 100755 --- a/verticapy/core/vdataframe/_plotting.py +++ b/verticapy/core/vdataframe/_plotting.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -166,8 +166,8 @@ def boxplot( .. seealso:: - | :py:mod:`verticapy.vDataFrame.outliers_plot` - | :py:mod:`verticapy.vDataColumn.boxplot` + | :py:meth:`verticapy.vDataFrame.outliers_plot` : Outliers Plot. + | :py:meth:`verticapy.vDataColumn.boxplot` : Box Plot. """ columns = format_type(columns, dtype=list) @@ -335,9 +335,9 @@ def bar( .. seealso:: - | :py:mod:`verticapy.vDataFrame.barh` - | :py:mod:`verticapy.vDataColumn.bar` - | :py:mod:`verticapy.vDataColumn.barh` + | :py:meth:`verticapy.vDataFrame.barh` : Horizontal Bar Chart. + | :py:meth:`verticapy.vDataColumn.bar` : Bar Chart. + | :py:meth:`verticapy.vDataColumn.barh` : Horizontal Bar Chart. """ columns = format_type(columns, dtype=list) @@ -542,9 +542,9 @@ def barh( .. seealso:: - | :py:mod:`verticapy.vDataFrame.bar` - | :py:mod:`verticapy.vDataColumn.barh` - | :py:mod:`verticapy.vDataColumn.bar` + | :py:meth:`verticapy.vDataFrame.bar` : Bar Chart. + | :py:meth:`verticapy.vDataColumn.barh` : Horizontal Bar Chart. + | :py:meth:`verticapy.vDataColumn.bar` : Bar Chart. """ @@ -709,9 +709,9 @@ def pie( .. seealso:: - | :py:mod:`verticapy.vDataFrame.hist` - | :py:mod:`verticapy.vDataColumn.bar` - | :py:mod:`verticapy.vDataColumn.pie` + | :py:meth:`verticapy.vDataFrame.hist` : Histogram. + | :py:meth:`verticapy.vDataColumn.bar` : Bar Chart. + | :py:meth:`verticapy.vDataColumn.pie` : Pie Chart. """ vpy_plt, kwargs = self.get_plotting_lib( @@ -864,9 +864,9 @@ def hist( .. seealso:: - | :py:mod:`verticapy.vDataFrame.bar` - | :py:mod:`verticapy.vDataFrame.barh` - | :py:mod:`verticapy.vDataColumn.hist` + | :py:meth:`verticapy.vDataFrame.bar` : Bar Chart. + | :py:meth:`verticapy.vDataFrame.barh` : Horizontal Bar Chart. + | :py:meth:`verticapy.vDataColumn.hist` : Histogram. """ vpy_plt, kwargs = self.get_plotting_lib( @@ -1012,9 +1012,9 @@ def density( .. seealso:: - | :py:mod:`verticapy.vDataFrame.hist` - | :py:mod:`verticapy.vDataFrame.range_plot` - | :py:mod:`verticapy.vDataColumn.density` + | :py:meth:`verticapy.vDataFrame.hist` : Histogram. + | :py:meth:`verticapy.vDataFrame.range_plot` : Range Plot. + | :py:meth:`verticapy.vDataColumn.density` : Density Plot. """ vml = get_vertica_mllib() @@ -1209,8 +1209,8 @@ def plot( .. seealso:: - | :py:mod:`verticapy.vDataFrame.range_plot` - | :py:mod:`verticapy.vDataColumn.plot` + | :py:meth:`verticapy.vDataFrame.range_plot` : Range Plot. + | :py:meth:`verticapy.vDataColumn.plot` : Line Plot. """ columns = format_type(columns, dtype=list) @@ -1355,8 +1355,8 @@ def range_plot( .. seealso:: - | :py:mod:`verticapy.vDataFrame.plot` - | :py:mod:`verticapy.vDataColumn.range_plot` + | :py:meth:`verticapy.vDataFrame.plot` : Line Plot. + | :py:meth:`verticapy.vDataColumn.range_plot` : Range Plot. """ vpy_plt, kwargs = self.get_plotting_lib( @@ -1600,8 +1600,8 @@ def pivot_table( .. seealso:: - | :py:mod:`verticapy.vDataFrame.contour` - | :py:mod:`verticapy.vDataFrame.scatter_matrix` + | :py:meth:`verticapy.vDataFrame.contour` : Contour Plot. + | :py:meth:`verticapy.vDataFrame.scatter_matrix` : Scatter Matrix. """ columns = format_type(columns, dtype=list) @@ -1727,8 +1727,8 @@ def f(x, y): .. seealso:: - | :py:mod:`verticapy.vDataFrame.hexbin` - | :py:mod:`verticapy.vDataFrame.heatmap` + | :py:meth:`verticapy.vDataFrame.hexbin` : Hexbin Plot. + | :py:meth:`verticapy.vDataFrame.heatmap` : Heatmap. """ vpy_plt, kwargs = self.get_plotting_lib( @@ -1864,8 +1864,8 @@ def heatmap( .. seealso:: - | :py:mod:`verticapy.vDataFrame.hexbin` - | :py:mod:`verticapy.vDataFrame.contour` + | :py:meth:`verticapy.vDataFrame.hexbin` : Hexbin Plot. + | :py:meth:`verticapy.vDataFrame.contour` : Contour Plot. """ columns = format_type(columns, dtype=list) @@ -2008,8 +2008,8 @@ def hexbin( .. seealso:: - | :py:mod:`verticapy.vDataFrame.heatmap` - | :py:mod:`verticapy.vDataFrame.contour` + | :py:meth:`verticapy.vDataFrame.heatmap` : Heatmap. + | :py:meth:`verticapy.vDataFrame.contour` : Contour Plot. """ columns, bbox = format_type(columns, bbox, dtype=list) @@ -2173,8 +2173,8 @@ def scatter( .. seealso:: - | :py:mod:`verticapy.vDataFrame.density` - | :py:mod:`verticapy.vDataFrame.outliers_plot` + | :py:meth:`verticapy.vDataFrame.density` : Density Plot. + | :py:meth:`verticapy.vDataFrame.outliers_plot` : Outliers Plot. """ vml = get_vertica_mllib() @@ -2320,8 +2320,8 @@ def scatter_matrix( .. seealso:: - | :py:mod:`verticapy.vDataFrame.contour` - | :py:mod:`verticapy.vDataFrame.heatmap` + | :py:meth:`verticapy.vDataFrame.contour` : Contour Plot. + | :py:meth:`verticapy.vDataFrame.heatmap` : Heatmap. """ columns = format_type(columns, dtype=list) @@ -2460,8 +2460,8 @@ def outliers_plot( .. seealso:: - | :py:mod:`verticapy.vDataFrame.scatter` - | :py:mod:`verticapy.vDataFrame.boxplot` + | :py:meth:`verticapy.vDataFrame.scatter` : Scatter Plot. + | :py:meth:`verticapy.vDataFrame.boxplot` : Box Plot. """ vpy_plt, kwargs = self.get_plotting_lib( @@ -2695,8 +2695,8 @@ def boxplot( .. seealso:: - | :py:mod:`verticapy.vDataFrame.boxplot` - | :py:mod:`verticapy.vDataColumn.outliers_plot` + | :py:meth:`verticapy.vDataFrame.boxplot` : Box Plot. + | :py:meth:`verticapy.vDataColumn.outliers_plot` : Outliers Plot. """ vpy_plt, kwargs = self._parent.get_plotting_lib( @@ -2840,9 +2840,9 @@ def bar( .. seealso:: - | :py:mod:`verticapy.vDataFrame.bar` - | :py:mod:`verticapy.vDataFrame.barh` - | :py:mod:`verticapy.vDataColumn.barh` + | :py:meth:`verticapy.vDataFrame.bar` : Bar Chart. + | :py:meth:`verticapy.vDataFrame.barh` : Horizontal Bar Chart. + | :py:meth:`verticapy.vDataColumn.barh` : Horizontal Bar Chart. """ vpy_plt, kwargs = self._parent.get_plotting_lib( @@ -2983,9 +2983,9 @@ def barh( .. seealso:: - | :py:mod:`verticapy.vDataFrame.bar` - | :py:mod:`verticapy.vDataFrame.barh` - | :py:mod:`verticapy.vDataColumn.bar` + | :py:meth:`verticapy.vDataFrame.bar` : Bar Chart. + | :py:meth:`verticapy.vDataFrame.barh` : Horizontal Bar Chart. + | :py:meth:`verticapy.vDataColumn.bar` : Bar Chart. """ vpy_plt, kwargs = self._parent.get_plotting_lib( @@ -3119,9 +3119,9 @@ def pie( .. seealso:: - | :py:mod:`verticapy.vDataFrame.hist` - | :py:mod:`verticapy.vDataFrame.pie` - | :py:mod:`verticapy.vDataColumn.bar` + | :py:meth:`verticapy.vDataFrame.hist` : Histogram. + | :py:meth:`verticapy.vDataFrame.pie` : Pie Chart. + | :py:meth:`verticapy.vDataColumn.bar` : Bar Chart. """ vpy_plt, kwargs = self._parent.get_plotting_lib( @@ -3249,8 +3249,8 @@ def spider( .. seealso:: - | :py:mod:`verticapy.vDataFrame.pie` - | :py:mod:`verticapy.vDataColumn.pie` + | :py:meth:`verticapy.vDataFrame.pie` : Pie Chart. + | :py:meth:`verticapy.vDataColumn.pie` : Pie Chart. """ by, of = self._parent.format_colnames(by, of) @@ -3404,9 +3404,9 @@ def hist( .. seealso:: - | :py:mod:`verticapy.vDataFrame.hist` - | :py:mod:`verticapy.vDataFrame.barh` - | :py:mod:`verticapy.vDataColumn.bar` + | :py:meth:`verticapy.vDataFrame.hist` : Histogram. + | :py:meth:`verticapy.vDataFrame.barh` : Horizontal Bar Chart. + | :py:meth:`verticapy.vDataColumn.bar` : Bar Chart. """ if self.isnum() and not (self.isbool()): @@ -3552,9 +3552,9 @@ def density( .. seealso:: - | :py:mod:`verticapy.vDataFrame.density` - | :py:mod:`verticapy.vDataFrame.range_plot` - | :py:mod:`verticapy.vDataColumn.hist` + | :py:meth:`verticapy.vDataFrame.density` : Density Plot. + | :py:meth:`verticapy.vDataFrame.range_plot` : Range Plot. + | :py:meth:`verticapy.vDataColumn.hist` : Histogram. """ vml = get_vertica_mllib() @@ -3723,8 +3723,8 @@ def candlestick( .. seealso:: - | :py:mod:`verticapy.vDataFrame.range_plot` - | :py:mod:`verticapy.vDataColumn.range_plot` + | :py:meth:`verticapy.vDataFrame.range_plot` : Range Plot. + | :py:meth:`verticapy.vDataColumn.range_plot` : Range Plot. """ ts = self._parent.format_colnames(ts) @@ -3854,8 +3854,8 @@ def plot( .. seealso:: - | :py:mod:`verticapy.vDataFrame.plot` - | :py:mod:`verticapy.vDataColumn.range_plot` + | :py:meth:`verticapy.vDataFrame.plot` : Line Plot. + | :py:meth:`verticapy.vDataColumn.range_plot` : Range Plot. """ ts, by = self._parent.format_colnames(ts, by) @@ -3976,8 +3976,8 @@ def range_plot( .. seealso:: - | :py:mod:`verticapy.vDataFrame.range_plot` - | :py:mod:`verticapy.vDataColumn.plot` + | :py:meth:`verticapy.vDataFrame.range_plot` : Range Plot. + | :py:meth:`verticapy.vDataColumn.plot` : Line Plot. """ return self._parent.range_plot( @@ -4063,7 +4063,7 @@ def geo_plot(self, *args, **kwargs) -> PlottingObject: .. seealso:: - | :py:mod:`verticapy.vDataColumn.plot` + | :py:meth:`verticapy.vDataColumn.plot` : Line Plot. """ columns = [self._alias] diff --git a/verticapy/core/vdataframe/_plotting_animated.py b/verticapy/core/vdataframe/_plotting_animated.py index f691334c7..92549f083 100755 --- a/verticapy/core/vdataframe/_plotting_animated.py +++ b/verticapy/core/vdataframe/_plotting_animated.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -151,8 +151,8 @@ def animated_bar( .. seealso:: - | :py:mod:`verticapy.vDataFrame.animated_pie` - | :py:mod:`verticapy.vDataColumn.bar` + | :py:meth:`verticapy.vDataFrame.animated_pie` : Animated Pie Chart. + | :py:meth:`verticapy.vDataColumn.bar` : Bar Chart. """ columns = format_type(columns, dtype=list) date_style_dict = format_type(date_style_dict, dtype=dict) @@ -302,8 +302,8 @@ def animated_pie( .. seealso:: - | :py:mod:`verticapy.vDataFrame.animated_bar` - | :py:mod:`verticapy.vDataColumn.pie` + | :py:meth:`verticapy.vDataFrame.animated_bar` : Animated Bar Chart. + | :py:meth:`verticapy.vDataColumn.pie` : Pie Chart. """ columns = format_type(columns, dtype=list) date_style_dict = format_type(date_style_dict, dtype=dict) @@ -442,8 +442,8 @@ def animated_plot( .. seealso:: - | :py:mod:`verticapy.vDataFrame.animated_pie` - | :py:mod:`verticapy.vDataFrame.plot` + | :py:meth:`verticapy.vDataFrame.animated_pie` : Animated Pie Chart. + | :py:meth:`verticapy.vDataFrame.plot` : Line Plot. """ columns = format_type(columns, dtype=list) columns, ts, by = self.format_colnames(columns, ts, by) @@ -614,8 +614,8 @@ def animated_scatter( .. seealso:: - | :py:mod:`verticapy.vDataFrame.animated_pie` - | :py:mod:`verticapy.vDataFrame.scatter` + | :py:meth:`verticapy.vDataFrame.animated_pie` : Animated Pie Chart. + | :py:meth:`verticapy.vDataFrame.scatter` : Scatter Plot. """ columns, bbox = format_type(columns, bbox, dtype=list) date_style_dict = format_type(date_style_dict, dtype=dict) diff --git a/verticapy/core/vdataframe/_read.py b/verticapy/core/vdataframe/_read.py index bb4342544..f740774c0 100755 --- a/verticapy/core/vdataframe/_read.py +++ b/verticapy/core/vdataframe/_read.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/vdataframe/_rolling.py b/verticapy/core/vdataframe/_rolling.py index 598cbc76b..48932a666 100755 --- a/verticapy/core/vdataframe/_rolling.py +++ b/verticapy/core/vdataframe/_rolling.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/vdataframe/_scaler.py b/verticapy/core/vdataframe/_scaler.py index 7606e4e68..e49f59aa2 100755 --- a/verticapy/core/vdataframe/_scaler.py +++ b/verticapy/core/vdataframe/_scaler.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -79,7 +79,7 @@ def scale( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -87,7 +87,7 @@ def scale( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -245,7 +245,7 @@ def scale( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -253,7 +253,7 @@ def scale( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming diff --git a/verticapy/core/vdataframe/_sys.py b/verticapy/core/vdataframe/_sys.py index 9e0414e48..91b94a267 100755 --- a/verticapy/core/vdataframe/_sys.py +++ b/verticapy/core/vdataframe/_sys.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/core/vdataframe/_text.py b/verticapy/core/vdataframe/_text.py index 9ded58c8d..301da3fe8 100755 --- a/verticapy/core/vdataframe/_text.py +++ b/verticapy/core/vdataframe/_text.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -93,6 +93,7 @@ def regexp( Returns the substring that matches a regular expression within a vDataColumn. + position: int, optional The number of characters from the start of the string where the function should start searching for matches. @@ -207,7 +208,7 @@ def regexp( .. seealso:: - | :py:mod:`verticapy.vDataFrame.eval` + | :py:meth:`verticapy.vDataFrame.eval` : Evaluates an expression. """ column = self.format_colnames(column) @@ -299,10 +300,10 @@ def str_contains(self, pat: str) -> "vDataFrame": .. seealso:: - | :py:mod:`verticapy.vDataFrame.str_count` - | :py:mod:`verticapy.vDataFrame.str_extract` - | :py:mod:`verticapy.vDataFrame.str_replace` - | :py:mod:`verticapy.vDataFrame.str_slice` + | :py:meth:`verticapy.vDataFrame.str_count` : Counts occurrences matching the regular expression. + | :py:meth:`verticapy.vDataFrame.str_extract` : Extracts the Regular Expression. + | :py:meth:`verticapy.vDataFrame.str_replace` : Replaces the Regular Expression. + | :py:meth:`verticapy.vDataFrame.str_slice` : Slices the Regular Expression. """ pat = pat.replace("'", "''") return self.apply(func=f"REGEXP_COUNT({{}}, '{pat}') > 0") @@ -379,10 +380,10 @@ def str_count(self, pat: str) -> "vDataFrame": .. seealso:: - | :py:mod:`verticapy.vDataFrame.str_contains` - | :py:mod:`verticapy.vDataFrame.str_extract` - | :py:mod:`verticapy.vDataFrame.str_replace` - | :py:mod:`verticapy.vDataFrame.str_slice` + | :py:meth:`verticapy.vDataFrame.str_contains` : Validates the regular expression. + | :py:meth:`verticapy.vDataFrame.str_extract` : Extracts the Regular Expression. + | :py:meth:`verticapy.vDataFrame.str_replace` : Replaces the Regular Expression. + | :py:meth:`verticapy.vDataFrame.str_slice` : Slices the Regular Expression. """ pat = pat.replace("'", "''") return self.apply(func=f"REGEXP_COUNT({{}}, '{pat}')") @@ -448,10 +449,10 @@ def str_extract(self, pat: str) -> "vDataFrame": .. seealso:: - | :py:mod:`verticapy.vDataFrame.str_contains` - | :py:mod:`verticapy.vDataFrame.str_count` - | :py:mod:`verticapy.vDataFrame.str_replace` - | :py:mod:`verticapy.vDataFrame.str_slice` + | :py:meth:`verticapy.vDataFrame.str_contains` : Validates the regular expression. + | :py:meth:`verticapy.vDataFrame.str_count` : Counts occurrences matching the regular expression. + | :py:meth:`verticapy.vDataFrame.str_replace` : Replaces the Regular Expression. + | :py:meth:`verticapy.vDataFrame.str_slice` : Slices the Regular Expression. """ pat = pat.replace("'", "''") return self.apply(func=f"REGEXP_SUBSTR({{}}, '{pat}')") @@ -526,10 +527,10 @@ def str_replace(self, to_replace: str, value: Optional[str] = None) -> "vDataFra .. seealso:: - | :py:mod:`verticapy.vDataFrame.str_contains` - | :py:mod:`verticapy.vDataFrame.str_count` - | :py:mod:`verticapy.vDataFrame.str_extract` - | :py:mod:`verticapy.vDataFrame.str_slice` + | :py:meth:`verticapy.vDataFrame.str_contains` : Validates the regular expression. + | :py:meth:`verticapy.vDataFrame.str_count` : Counts occurrences matching the regular expression. + | :py:meth:`verticapy.vDataFrame.str_extract` : Extracts the Regular Expression. + | :py:meth:`verticapy.vDataFrame.str_slice` : Slices the Regular Expression. """ to_replace = to_replace.replace("'", "''") value = value.replace("'", "''") @@ -596,9 +597,9 @@ def str_slice(self, start: int, step: int) -> "vDataFrame": .. seealso:: - | :py:mod:`verticapy.vDataFrame.str_contains` - | :py:mod:`verticapy.vDataFrame.str_count` - | :py:mod:`verticapy.vDataFrame.str_replace` - | :py:mod:`verticapy.vDataFrame.str_extract` + | :py:meth:`verticapy.vDataFrame.str_contains` : Validates the regular expression. + | :py:meth:`verticapy.vDataFrame.str_count` : Counts occurrences matching the regular expression. + | :py:meth:`verticapy.vDataFrame.str_replace` : Replaces the Regular Expression. + | :py:meth:`verticapy.vDataFrame.str_extract` : Extracts the Regular Expression. """ return self.apply(func=f"SUBSTR({{}}, {start}, {step})") diff --git a/verticapy/core/vdataframe/_typing.py b/verticapy/core/vdataframe/_typing.py index 477a31683..581e792df 100755 --- a/verticapy/core/vdataframe/_typing.py +++ b/verticapy/core/vdataframe/_typing.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -60,7 +60,7 @@ def astype(self, dtype: dict) -> "vDataFrame": Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -68,7 +68,7 @@ def astype(self, dtype: dict) -> "vDataFrame": .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -162,7 +162,7 @@ def bool_to_int(self) -> "vDataFrame": Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -170,7 +170,7 @@ def bool_to_int(self) -> "vDataFrame": .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -248,7 +248,7 @@ def catcol(self, max_cardinality: int = 12) -> list: Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -256,7 +256,7 @@ def catcol(self, max_cardinality: int = 12) -> list: .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -311,9 +311,9 @@ def catcol(self, max_cardinality: int = 12) -> list: .. seealso:: - | :py:mod:`verticapy.vDataFrame.datecol` - | :py:mod:`verticapy.vDataFrame.numcol` - | :py:mod:`verticapy.vDataFrame.get_columns` + | :py:meth:`verticapy.vDataFrame.datecol` : Returns all vDataColumns with date-type values. + | :py:meth:`verticapy.vDataFrame.numcol` : Returns all vDataColumns with numerical values. + | :py:meth:`verticapy.vDataFrame.get_columns` : Returns all vDataColumns. """ columns = [] for column in self.get_columns(): @@ -350,7 +350,7 @@ def datecol(self) -> list: Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -358,7 +358,7 @@ def datecol(self) -> list: .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -420,9 +420,9 @@ def datecol(self) -> list: .. seealso:: - | :py:mod:`verticapy.vDataFrame.catcol` - | :py:mod:`verticapy.vDataFrame.numcol` - | :py:mod:`verticapy.vDataFrame.get_columns` + | :py:meth:`verticapy.vDataFrame.catcol` : Returns all vDataColumns with categorical values. + | :py:meth:`verticapy.vDataFrame.numcol` : Returns all vDataColumns with numerical values. + | :py:meth:`verticapy.vDataFrame.get_columns` : Returns all vDataColumns. """ columns = [] cols = self.get_columns() @@ -444,7 +444,7 @@ def dtypes(self) -> TableSample: Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -452,7 +452,7 @@ def dtypes(self) -> TableSample: .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -530,7 +530,7 @@ def numcol(self, exclude_columns: Optional[SQLColumns] = None) -> list: Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -538,7 +538,7 @@ def numcol(self, exclude_columns: Optional[SQLColumns] = None) -> list: .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -587,9 +587,9 @@ def numcol(self, exclude_columns: Optional[SQLColumns] = None) -> list: .. seealso:: - | :py:mod:`verticapy.vDataFrame.catcol` - | :py:mod:`verticapy.vDataFrame.datecol` - | :py:mod:`verticapy.vDataFrame.get_columns` + | :py:meth:`verticapy.vDataFrame.catcol` : Returns all vDataColumns with categorical values. + | :py:meth:`verticapy.vDataFrame.datecol` : Returns all vDataColumns with date-type values. + | :py:meth:`verticapy.vDataFrame.get_columns` : Returns all vDataColumns. """ columns, cols = [], self.get_columns(exclude_columns=exclude_columns) for column in cols: @@ -624,7 +624,7 @@ def astype(self, dtype: Union[str, type]) -> "vDataFrame": Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -632,7 +632,7 @@ def astype(self, dtype: Union[str, type]) -> "vDataFrame": .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -856,7 +856,7 @@ def category(self) -> str: Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -864,7 +864,7 @@ def category(self) -> str: .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -924,7 +924,7 @@ def ctype(self) -> str: Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -932,7 +932,7 @@ def ctype(self) -> str: .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -995,7 +995,7 @@ def isarray(self) -> bool: Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1003,7 +1003,7 @@ def isarray(self) -> bool: .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1055,7 +1055,7 @@ def isbool(self) -> bool: Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1063,7 +1063,7 @@ def isbool(self) -> bool: .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1127,7 +1127,7 @@ def isdate(self) -> bool: Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1135,7 +1135,7 @@ def isdate(self) -> bool: .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1197,7 +1197,7 @@ def isnum(self) -> bool: Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1205,7 +1205,7 @@ def isnum(self) -> bool: .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1264,7 +1264,7 @@ def isvmap(self) -> bool: Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1272,7 +1272,7 @@ def isvmap(self) -> bool: .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming diff --git a/verticapy/core/vdataframe/_utils.py b/verticapy/core/vdataframe/_utils.py index 6e8fef34b..69ea10ca4 100755 --- a/verticapy/core/vdataframe/_utils.py +++ b/verticapy/core/vdataframe/_utils.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -97,7 +97,7 @@ def format_colnames( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -105,7 +105,7 @@ def format_colnames( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -250,7 +250,7 @@ def get_match_index( Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -258,7 +258,7 @@ def get_match_index( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -337,7 +337,7 @@ def is_colname_in(self, column: str) -> bool: Examples --------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -345,7 +345,7 @@ def is_colname_in(self, column: str) -> bool: .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming diff --git a/verticapy/core/vdataframe/base.py b/verticapy/core/vdataframe/base.py index ecfdcda5c..017309290 100755 --- a/verticapy/core/vdataframe/base.py +++ b/verticapy/core/vdataframe/base.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/datasets/__init__.py b/verticapy/datasets/__init__.py index e5393ad22..5146844c5 100755 --- a/verticapy/datasets/__init__.py +++ b/verticapy/datasets/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/datasets/data/__init__.py b/verticapy/datasets/data/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/datasets/data/__init__.py +++ b/verticapy/datasets/data/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/datasets/generators.py b/verticapy/datasets/generators.py index 188bf03cc..fe2d18c7d 100755 --- a/verticapy/datasets/generators.py +++ b/verticapy/datasets/generators.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/datasets/loaders.py b/verticapy/datasets/loaders.py index eb1b8a72f..d1a21ddbd 100755 --- a/verticapy/datasets/loaders.py +++ b/verticapy/datasets/loaders.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/datasets/tests_loaders.py b/verticapy/datasets/tests_loaders.py index 1c86db1b0..455bdcc38 100755 --- a/verticapy/datasets/tests_loaders.py +++ b/verticapy/datasets/tests_loaders.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/errors/__init__.py b/verticapy/errors/__init__.py index aeb7af106..3c7a8f547 100755 --- a/verticapy/errors/__init__.py +++ b/verticapy/errors/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/geo/__init__.py b/verticapy/geo/__init__.py index fed2e52bf..f0a67e94d 100755 --- a/verticapy/geo/__init__.py +++ b/verticapy/geo/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.geo' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.sql.geo' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/hchart/__init__.py b/verticapy/hchart/__init__.py index fb52f3270..a30268629 100755 --- a/verticapy/hchart/__init__.py +++ b/verticapy/hchart/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Loading extension 'verticapy.hchart' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.chart' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/jupyter/__init__.py b/verticapy/jupyter/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/jupyter/__init__.py +++ b/verticapy/jupyter/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/jupyter/_javascript.py b/verticapy/jupyter/_javascript.py index 16b3ef7cf..6efd326be 100644 --- a/verticapy/jupyter/_javascript.py +++ b/verticapy/jupyter/_javascript.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/jupyter/extensions/__init__.py b/verticapy/jupyter/extensions/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/jupyter/extensions/__init__.py +++ b/verticapy/jupyter/extensions/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/jupyter/extensions/_utils.py b/verticapy/jupyter/extensions/_utils.py index d99a2e2a8..d3ee1e1d9 100755 --- a/verticapy/jupyter/extensions/_utils.py +++ b/verticapy/jupyter/extensions/_utils.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/jupyter/extensions/chart_magic.py b/verticapy/jupyter/extensions/chart_magic.py index 0c4f23077..e8102fa5e 100644 --- a/verticapy/jupyter/extensions/chart_magic.py +++ b/verticapy/jupyter/extensions/chart_magic.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -262,7 +262,7 @@ def chart_magic( .. Warning:: This method uses a CROSS JOIN during computation and is therefore computationally expensive at O(n * n), where n - is the total count of the ``vDataFrame``. + is the total count of the :py:class:`vDataFrame`. **line** : Line Plot @@ -331,13 +331,15 @@ def chart_magic( import verticapy as vp # Save a new connection - vp.new_connection({ - "host": "10.211.55.14", - "port": "5433", - "database": "testdb", - "password": "XxX", - "user": "dbadmin"}, - name = "VerticaDSN" + vp.new_connection( + { + "host": "10.211.55.14", + "port": "5433", + "database": "testdb", + "password": "XxX", + "user": "dbadmin", + }, + name = "VerticaDSN", ) Otherwise, to use an existing connection: @@ -370,7 +372,7 @@ def chart_magic( amazon = load_amazon() iris = load_iris() - Use the :py:module:`set_option`_ function to set your desired plotting library: + Use the :py:func:`set_option` function to set your desired plotting library: .. ipython:: python diff --git a/verticapy/jupyter/extensions/sql_magic.py b/verticapy/jupyter/extensions/sql_magic.py index f05e56066..a80e29575 100644 --- a/verticapy/jupyter/extensions/sql_magic.py +++ b/verticapy/jupyter/extensions/sql_magic.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -142,13 +142,15 @@ def sql_magic( import verticapy as vp # Save a new connection - vp.new_connection({ - "host": "10.211.55.14", - "port": "5433", - "database": "testdb", - "password": "XxX", - "user": "dbadmin"}, - name = "VerticaDSN" + vp.new_connection( + { + "host": "10.211.55.14", + "port": "5433", + "database": "testdb", + "password": "XxX", + "user": "dbadmin", + }, + name = "VerticaDSN", ) If you already have a connection in a connection diff --git a/verticapy/learn/__init__.py b/verticapy/learn/__init__.py index f1ccaaa64..1c163c102 100755 --- a/verticapy/learn/__init__.py +++ b/verticapy/learn/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.learn' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.machine_learning' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/learn/cluster/__init__.py b/verticapy/learn/cluster/__init__.py index cfeb03d84..3c34ee5eb 100755 --- a/verticapy/learn/cluster/__init__.py +++ b/verticapy/learn/cluster/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.learn.cluster' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.machine_learning.vertica' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/learn/decomposition/__init__.py b/verticapy/learn/decomposition/__init__.py index 6650b0b24..265def55f 100755 --- a/verticapy/learn/decomposition/__init__.py +++ b/verticapy/learn/decomposition/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.learn.decomposition' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.machine_learning.vertica' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/learn/delphi/__init__.py b/verticapy/learn/delphi/__init__.py index e21d52667..a1aba3ab7 100755 --- a/verticapy/learn/delphi/__init__.py +++ b/verticapy/learn/delphi/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.learn.delphi' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.machine_learning.vertica.automl' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/learn/ensemble/__init__.py b/verticapy/learn/ensemble/__init__.py index 883ef1d1c..2884c780a 100755 --- a/verticapy/learn/ensemble/__init__.py +++ b/verticapy/learn/ensemble/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.learn.ensemble' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.machine_learning.vertica' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/learn/linear_model/__init__.py b/verticapy/learn/linear_model/__init__.py index ec07374f2..c01092a9b 100755 --- a/verticapy/learn/linear_model/__init__.py +++ b/verticapy/learn/linear_model/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.learn.linear_model' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.machine_learning.vertica' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/learn/memmodel/__init__.py b/verticapy/learn/memmodel/__init__.py index e4b0be598..9b1ea0bcf 100755 --- a/verticapy/learn/memmodel/__init__.py +++ b/verticapy/learn/memmodel/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.learn.memmodel' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.machine_learning.memmodel' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/learn/metrics/__init__.py b/verticapy/learn/metrics/__init__.py index f1d371811..3566ad6c5 100755 --- a/verticapy/learn/metrics/__init__.py +++ b/verticapy/learn/metrics/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.learn.cluster' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.machine_learning.metrics' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/learn/model_selection/__init__.py b/verticapy/learn/model_selection/__init__.py index 81fa776c2..8665f6b48 100755 --- a/verticapy/learn/model_selection/__init__.py +++ b/verticapy/learn/model_selection/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.learn.model_selection' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.machine_learning.model_selection' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/learn/naive_bayes/__init__.py b/verticapy/learn/naive_bayes/__init__.py index 953c9a303..ec15037dc 100755 --- a/verticapy/learn/naive_bayes/__init__.py +++ b/verticapy/learn/naive_bayes/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.learn.naive_bayes' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.machine_learning.vertica' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/learn/neighbors/__init__.py b/verticapy/learn/neighbors/__init__.py index 403931440..165cc9df3 100755 --- a/verticapy/learn/neighbors/__init__.py +++ b/verticapy/learn/neighbors/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.learn.neighbors' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.machine_learning.vertica' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/learn/pipeline/__init__.py b/verticapy/learn/pipeline/__init__.py index a21f30b81..d42c8f3fd 100755 --- a/verticapy/learn/pipeline/__init__.py +++ b/verticapy/learn/pipeline/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.learn.pipeline' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.machine_learning.vertica' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/learn/preprocessing/__init__.py b/verticapy/learn/preprocessing/__init__.py index 1ae12bff5..36b2abfc8 100755 --- a/verticapy/learn/preprocessing/__init__.py +++ b/verticapy/learn/preprocessing/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.learn.preprocessing' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.machine_learning.vertica' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/learn/svm/__init__.py b/verticapy/learn/svm/__init__.py index 6a735c7f8..24ee60cce 100755 --- a/verticapy/learn/svm/__init__.py +++ b/verticapy/learn/svm/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.learn.svm' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.machine_learning.vertica' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/learn/tools/__init__.py b/verticapy/learn/tools/__init__.py index 973c273f7..546dc6031 100755 --- a/verticapy/learn/tools/__init__.py +++ b/verticapy/learn/tools/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.learn.tools' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.machine_learning.vertica' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/learn/tree/__init__.py b/verticapy/learn/tree/__init__.py index 155824220..d50e0fe91 100755 --- a/verticapy/learn/tree/__init__.py +++ b/verticapy/learn/tree/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.learn.tree' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.machine_learning.vertica' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/learn/tsa/__init__.py b/verticapy/learn/tsa/__init__.py index ffdf0a9c4..bd2c3b8ae 100755 --- a/verticapy/learn/tsa/__init__.py +++ b/verticapy/learn/tsa/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.learn.tsa' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.machine_learning.vertica' instead " "to ensure compatibility with upcoming versions.\n" "Note: SARIMAX and VAR have been removed. Please explore " diff --git a/verticapy/learn/vmodel/__init__.py b/verticapy/learn/vmodel/__init__.py index b18982d4d..82572cbad 100755 --- a/verticapy/learn/vmodel/__init__.py +++ b/verticapy/learn/vmodel/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.learn.vmodel' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.machine_learning.vertica' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/machine_learning/__init__.py b/verticapy/machine_learning/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/machine_learning/__init__.py +++ b/verticapy/machine_learning/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/memmodel/__init__.py b/verticapy/machine_learning/memmodel/__init__.py index b82b3bfad..462fdcf6d 100755 --- a/verticapy/machine_learning/memmodel/__init__.py +++ b/verticapy/machine_learning/memmodel/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/memmodel/base.py b/verticapy/machine_learning/memmodel/base.py index 01c0fccfc..3627f8eef 100755 --- a/verticapy/machine_learning/memmodel/base.py +++ b/verticapy/machine_learning/memmodel/base.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/memmodel/cluster.py b/verticapy/machine_learning/memmodel/cluster.py index 69cea4c05..34d85ea17 100755 --- a/verticapy/machine_learning/memmodel/cluster.py +++ b/verticapy/machine_learning/memmodel/cluster.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -28,17 +28,17 @@ class Clustering(InMemoryModel): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of clustering algorithms. .. note:: This is base class for all in-memory implementations of clustering algorithms viz. - :py:mod:`verticapy.machine_learning.memmodel.cluster.KMeans`, - :py:mod:`verticapy.machine_learning.memmodel.cluster.NearestCentroid` - , :py:mod:`verticapy.machine_learning.memmodel.cluster.BisectingKMeans` - and :py:mod:`verticapy.machine_learning.memmodel.cluster.KPrototypes` + :py:meth:`verticapy.machine_learning.memmodel.cluster.KMeans`, + :py:meth:`verticapy.machine_learning.memmodel.cluster.NearestCentroid` + , :py:meth:`verticapy.machine_learning.memmodel.cluster.BisectingKMeans` + and :py:meth:`verticapy.machine_learning.memmodel.cluster.KPrototypes` Parameters ---------- @@ -244,7 +244,7 @@ def transform_sql(self, X: ArrayLike) -> list[str]: class KMeans(Clustering): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of KMeans. Parameters @@ -256,7 +256,7 @@ class KMeans(Clustering): .. note:: - :py:mod:`verticapy.machine_learning.memmodel` are + :py:meth:`verticapy.machine_learning.memmodel` are defined entirely by their attributes. For example, 'cluster centroids' and 'p value' define a KMeans model. @@ -285,7 +285,7 @@ class KMeans(Clustering): p = 2 Let's create a - :py:mod:`verticapy.machine_learning.memmodel.cluster.KMeans` model. + :py:meth:`verticapy.machine_learning.memmodel.cluster.KMeans` model. .. ipython:: python @@ -308,7 +308,7 @@ class KMeans(Clustering): .. note:: - :py:mod:`verticapy.machine_learning.memmodel.cluster.KMeans` + :py:meth:`verticapy.machine_learning.memmodel.cluster.KMeans` assigns a cluster id to identify each cluster. In this example, cluster with centroid [0.5, 0.6] will have id = 0, with centroid [1,2] will have id = 1 and so on. @@ -385,7 +385,7 @@ def __init__(self, clusters: ArrayLike, p: int = 2) -> None: class NearestCentroid(Clustering): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of NearestCentroid algorithm. Parameters @@ -424,7 +424,7 @@ class NearestCentroid(Clustering): classes = ['class_a', 'class_b', 'class_c'] Let's create a - :py:mod:`verticapy.machine_learning.memmodel.cluster.NearestCentroid` + :py:meth:`verticapy.machine_learning.memmodel.cluster.NearestCentroid` model. .. ipython:: python @@ -530,7 +530,7 @@ def __init__( class BisectingKMeans(Clustering, Tree): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of BisectingKMeans. Parameters @@ -582,7 +582,7 @@ class BisectingKMeans(Clustering, Tree): children_right = [2, 4, None, None, None] Let's create a - :py:mod:`verticapy.machine_learning.memmodel.cluster.BisectingKMeans` + :py:meth:`verticapy.machine_learning.memmodel.cluster.BisectingKMeans` model. .. ipython:: python @@ -961,7 +961,7 @@ def to_graphviz( class KPrototypes(Clustering): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of KPrototypes. Parameters @@ -982,7 +982,7 @@ class KPrototypes(Clustering): .. note:: - :py:mod:`verticapy.machine_learning.memmodel.cluster.KPrototypes` + :py:meth:`verticapy.machine_learning.memmodel.cluster.KPrototypes` algorithm allows you to use categorical variables directly without the need to encode them. @@ -1014,7 +1014,7 @@ class KPrototypes(Clustering): is_categorical = [0, 1] Let's create a - :py:mod:`verticapy.machine_learning.memmodel.cluster.KPrototypes` + :py:meth:`verticapy.machine_learning.memmodel.cluster.KPrototypes` model. .. ipython:: python @@ -1039,7 +1039,7 @@ class KPrototypes(Clustering): .. note:: - :py:mod:`verticapy.machine_learning.memmodel.cluster.KPrototypes` + :py:meth:`verticapy.machine_learning.memmodel.cluster.KPrototypes` assigns a cluster id to identify each cluster. In this example, cluster with centroid [0.5, 'high'] will have id = 0, with centroid [1,'low'] will have id = 1 and so on. diff --git a/verticapy/machine_learning/memmodel/decomposition.py b/verticapy/machine_learning/memmodel/decomposition.py index 899c6d408..e530bdb7a 100755 --- a/verticapy/machine_learning/memmodel/decomposition.py +++ b/verticapy/machine_learning/memmodel/decomposition.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -26,7 +26,7 @@ class PCA(InMemoryModel): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of the PCA algorithm. Parameters @@ -38,7 +38,7 @@ class PCA(InMemoryModel): .. note:: - :py:mod:`verticapy.machine_learning.memmodel` are defined entirely + :py:meth:`verticapy.machine_learning.memmodel` are defined entirely by their attributes. For example, ``principal components`` and ``mean`` define a PCA model. @@ -67,7 +67,7 @@ class PCA(InMemoryModel): mean = [0.1, 0.3] Let's create a - :py:mod:`verticapy.machine_learning.memmodel.decomposition.PCA` + :py:meth:`verticapy.machine_learning.memmodel.decomposition.PCA` model. .. ipython:: python @@ -286,7 +286,7 @@ def rotate(self, gamma: float = 1.0, q: int = 20, tol: float = 1e-6) -> None: class SVD(InMemoryModel): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of the SVD Algorithm. Parameters @@ -299,7 +299,7 @@ class SVD(InMemoryModel): .. note:: - :py:mod:`verticapy.machine_learning.memmodel` are defined + :py:meth:`verticapy.machine_learning.memmodel` are defined entirely by their attributes. For example, ``vectors`` and 'values' define a SVD model. @@ -328,7 +328,7 @@ class SVD(InMemoryModel): values = [0.1, 0.3] Let's create a - :py:mod:`verticapy.machine_learning.memmodel.decomposition.SVD` + :py:meth:`verticapy.machine_learning.memmodel.decomposition.SVD` model. .. ipython:: python diff --git a/verticapy/machine_learning/memmodel/ensemble.py b/verticapy/machine_learning/memmodel/ensemble.py index ff9ac3e23..edef7e619 100755 --- a/verticapy/machine_learning/memmodel/ensemble.py +++ b/verticapy/machine_learning/memmodel/ensemble.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -36,7 +36,7 @@ class Ensemble(InMemoryModel): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of ensemble algorithms. """ @@ -88,7 +88,7 @@ def plot_tree( class RandomForestRegressor(Ensemble): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of the random forest regressor algorithm. Parameters @@ -108,7 +108,7 @@ class RandomForestRegressor(Ensemble): A Random Forest Regressor model is an ensemble of multiple binary tree regressor models. In this example, we will create three - :py:mod:`verticapy.machine_learning.memmodel.tree.BinaryTreeRegressor` + :py:meth:`verticapy.machine_learning.memmodel.tree.BinaryTreeRegressor` models: .. ipython:: python @@ -138,7 +138,7 @@ class RandomForestRegressor(Ensemble): ) Now we will use above models to create - :py:mod:`verticapy.machine_learning.memmodel.ensemble.RandomForestRegressor` + :py:meth:`verticapy.machine_learning.memmodel.ensemble.RandomForestRegressor` model. .. ipython:: python @@ -271,7 +271,7 @@ def predict_sql(self, X: ArrayLike) -> str: class RandomForestClassifier(Ensemble, MulticlassClassifier): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of the random forest classifier algorithm. Parameters @@ -293,7 +293,7 @@ class RandomForestClassifier(Ensemble, MulticlassClassifier): A Random Forest Classifier model is an ensemble of multiple binary tree classifier models. In this example, we will create three - :py:mod:`verticapy.machine_learning.memmodel.tree.BinaryTreeClassifier` + :py:meth:`verticapy.machine_learning.memmodel.tree.BinaryTreeClassifier` models: .. ipython:: python @@ -326,7 +326,7 @@ class RandomForestClassifier(Ensemble, MulticlassClassifier): ) Now we will use above models to create - :py:mod:`verticapy.machine_learning.memmodel.ensemble.RandomForestClassifier` + :py:meth:`verticapy.machine_learning.memmodel.ensemble.RandomForestClassifier` model. .. ipython:: python @@ -518,7 +518,7 @@ def predict_proba_sql(self, X: ArrayLike) -> list[str]: class XGBRegressor(Ensemble): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of the XGBoost regressor algorithm. Parameters @@ -542,7 +542,7 @@ class XGBRegressor(Ensemble): A model is an ensemble of multiple binary tree regressors. In this example, we will create three - :py:mod:`verticapy.machine_learning.memmodel.tree.BinaryTreeRegressor` + :py:meth:`verticapy.machine_learning.memmodel.tree.BinaryTreeRegressor` models. .. ipython:: python @@ -572,7 +572,7 @@ class XGBRegressor(Ensemble): ) Now we will use above models to create - :py:mod:`verticapy.machine_learning.memmodel.ensemble.XGBRegressor` + :py:meth:`verticapy.machine_learning.memmodel.ensemble.XGBRegressor` model. .. ipython:: python @@ -723,7 +723,7 @@ def predict_sql(self, X: ArrayLike) -> str: class XGBClassifier(Ensemble, MulticlassClassifier): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of the XGBoost classifier algorithm. Parameters @@ -750,7 +750,7 @@ class XGBClassifier(Ensemble, MulticlassClassifier): A XGBoost Classifier model is an ensemble of multiple binary tree classifier models. In this example, we will create three - :py:mod:`verticapy.machine_learning.memmodel.tree.BinaryTreeClassifier` + :py:meth:`verticapy.machine_learning.memmodel.tree.BinaryTreeClassifier` models: .. ipython:: python @@ -783,7 +783,7 @@ class XGBClassifier(Ensemble, MulticlassClassifier): ) Now we will use above models to create - :py:mod:`verticapy.machine_learning.memmodel.ensemble.XGBClassifier` + :py:meth:`verticapy.machine_learning.memmodel.ensemble.XGBClassifier` model. .. ipython:: python @@ -973,7 +973,7 @@ def predict_proba_sql(self, X: ArrayLike) -> list[str]: class IsolationForest(Ensemble): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of the isolation forest algorithm. Parameters @@ -993,7 +993,7 @@ class IsolationForest(Ensemble): An Isolation Forest model is an ensemble of multiple binary tree anomaly models. In this example, we will create three - :py:mod:`verticapy.machine_learning.memmodel.tree.BinaryTreeAnomaly` + :py:meth:`verticapy.machine_learning.memmodel.tree.BinaryTreeAnomaly` models: .. ipython:: python @@ -1026,7 +1026,7 @@ class IsolationForest(Ensemble): ) Now we will use above models to create - :py:mod:`verticapy.machine_learning.memmodel.ensemble.IsolationForest` + :py:meth:`verticapy.machine_learning.memmodel.ensemble.IsolationForest` model. .. ipython:: python diff --git a/verticapy/machine_learning/memmodel/linear_model.py b/verticapy/machine_learning/memmodel/linear_model.py index 476fd8716..ec9fa4a65 100755 --- a/verticapy/machine_learning/memmodel/linear_model.py +++ b/verticapy/machine_learning/memmodel/linear_model.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -25,7 +25,7 @@ class LinearModel(InMemoryModel): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of linear algorithms. Parameters @@ -37,7 +37,7 @@ class LinearModel(InMemoryModel): .. note:: - :py:mod:`verticapy.machine_learning.memmodel` are defined entirely + :py:meth:`verticapy.machine_learning.memmodel` are defined entirely by their attributes. For example, ``coefficients`` and ``intercept`` define a linear regression model. @@ -65,7 +65,7 @@ class LinearModel(InMemoryModel): coefficients = [0.5, 1.2] intercept = 2.0 - Let's create a :py:mod:`verticapy.machine_learning.memmodel.linear_model`. + Let's create a :py:meth:`verticapy.machine_learning.memmodel.linear_model`. .. ipython:: python @@ -80,7 +80,7 @@ class LinearModel(InMemoryModel): **Making In-Memory Predictions** Use - :py:mod:`verticapy.machine_learning.memmodel.linear_model.LinearModel.predict` + :py:meth:`verticapy.machine_learning.memmodel.linear_model.LinearModel.predict` method to do predictions. .. ipython:: python @@ -96,7 +96,7 @@ class LinearModel(InMemoryModel): cnames = ['col1', 'col2'] Use - :py:mod:`verticapy.machine_learning.memmodel.linear_model.LinearModel.predict_sql` + :py:meth:`verticapy.machine_learning.memmodel.linear_model.LinearModel.predict_sql` method to get the SQL code needed to deploy the model using its attributes. @@ -234,7 +234,7 @@ def predict_proba_sql(self, X: ArrayLike) -> list[str]: class LinearModelClassifier(LinearModel): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` Implementation of linear algorithms for classification. Parameters @@ -268,7 +268,7 @@ class LinearModelClassifier(LinearModel): coefficients = [0.5, 1.2] intercept = 2.0 - Let's create a :py:mod:`verticapy.machine_learning.memmodel.linear_model`. + Let's create a :py:meth:`verticapy.machine_learning.memmodel.linear_model`. .. ipython:: python diff --git a/verticapy/machine_learning/memmodel/naive_bayes.py b/verticapy/machine_learning/memmodel/naive_bayes.py index 556f3b23a..610a42310 100755 --- a/verticapy/machine_learning/memmodel/naive_bayes.py +++ b/verticapy/machine_learning/memmodel/naive_bayes.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -27,7 +27,7 @@ class NaiveBayes(MulticlassClassifier): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of the naive Bayes algorithm. Parameters @@ -93,7 +93,7 @@ class NaiveBayes(MulticlassClassifier): .. note:: - :py:mod:`verticapy.machine_learning.memmodel` are defined + :py:meth:`verticapy.machine_learning.memmodel` are defined entirely by their attributes. For example, 'prior probabilities', 'classes' and 'input feature attributes' specific to the type of distribution, defines a NaiveBayes model. @@ -170,7 +170,7 @@ class NaiveBayes(MulticlassClassifier): classes = ["C", "Q", "S"] Let's create a - :py:mod:`verticapy.machine_learning.memmodel.naive_bayes` + :py:meth:`verticapy.machine_learning.memmodel.naive_bayes` model. .. ipython:: python diff --git a/verticapy/machine_learning/memmodel/preprocessing.py b/verticapy/machine_learning/memmodel/preprocessing.py index 40126259d..c7b0e7d2a 100755 --- a/verticapy/machine_learning/memmodel/preprocessing.py +++ b/verticapy/machine_learning/memmodel/preprocessing.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -28,7 +28,7 @@ class Scaler(InMemoryModel): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of scalers. Parameters @@ -106,7 +106,7 @@ def transform_sql(self, X: ArrayLike) -> list[str]: class StandardScaler(Scaler): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of standard scaler. Parameters @@ -118,7 +118,7 @@ class StandardScaler(Scaler): .. note:: - :py:mod:`verticapy.machine_learning.memmodel` are defined + :py:meth:`verticapy.machine_learning.memmodel` are defined entirely by their attributes. For example, 'mean', and 'standard deviation' of feature(S) define a StandardScaler model. @@ -126,7 +126,7 @@ class StandardScaler(Scaler): Attributes ---------- Attributes are identical to - :py:mod:`verticapy.machine_learning.memmodel.preprocessing.Scaler`. + :py:meth:`verticapy.machine_learning.memmodel.preprocessing.Scaler`. Examples -------- @@ -148,7 +148,7 @@ class StandardScaler(Scaler): std = [0.5, 0.2] Let's create a - :py:mod:`verticapy.machine_learning.memmodel.preprocessing.StandardScaler` + :py:meth:`verticapy.machine_learning.memmodel.preprocessing.StandardScaler` model. .. ipython:: python @@ -208,7 +208,7 @@ def __init__(self, mean: ArrayLike, std: ArrayLike) -> None: class MinMaxScaler(Scaler): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of MinMax scaler. Parameters @@ -221,7 +221,7 @@ class MinMaxScaler(Scaler): .. note:: - :py:mod:`verticapy.machine_learning.memmodel` are defined + :py:meth:`verticapy.machine_learning.memmodel` are defined entirely by their attributes. For example, 'minimum', and 'maximum' values of the input features define a MinMaxScaler model. @@ -229,7 +229,7 @@ class MinMaxScaler(Scaler): Attributes ---------- Attributes are identical to - :py:mod:`verticapy.machine_learning.memmodel.preprocessing.Scaler`. + :py:meth:`verticapy.machine_learning.memmodel.preprocessing.Scaler`. Examples -------- @@ -251,7 +251,7 @@ class MinMaxScaler(Scaler): max = [0.5, 0.2] Let's create a - :py:mod:`verticapy.machine_learning.memmodel.preprocessing.MinMaxScaler` + :py:meth:`verticapy.machine_learning.memmodel.preprocessing.MinMaxScaler` model. .. ipython:: python @@ -311,7 +311,7 @@ def __init__(self, min_: ArrayLike, max_: ArrayLike) -> None: class OneHotEncoder(InMemoryModel): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of one-hot encoder. Parameters @@ -337,7 +337,7 @@ class OneHotEncoder(InMemoryModel): .. note:: - :py:mod:`verticapy.machine_learning.memmodel` are defined + :py:meth:`verticapy.machine_learning.memmodel` are defined entirely by their attributes. For example, 'categories' to encode defines a OneHotEncoder model. You can optionally provide 'column naming' criteria and a 'drop_first' flag to @@ -363,7 +363,7 @@ class OneHotEncoder(InMemoryModel): criteria and drop_first flag. Let's create a - :py:mod:`verticapy.machine_learning.memmodel.preprocessing.OneHotEncoder` + :py:meth:`verticapy.machine_learning.memmodel.preprocessing.OneHotEncoder` model. .. ipython:: python diff --git a/verticapy/machine_learning/memmodel/tree.py b/verticapy/machine_learning/memmodel/tree.py index 9e3ffd838..d30cf6584 100755 --- a/verticapy/machine_learning/memmodel/tree.py +++ b/verticapy/machine_learning/memmodel/tree.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -454,7 +454,7 @@ def plot_tree( class BinaryTreeRegressor(Tree): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of binary trees for regression. Parameters @@ -499,7 +499,7 @@ class BinaryTreeRegressor(Tree): Final values at leaf nodes are also required. Let's create a - :py:mod:`verticapy.machine_learning.memmodel.tree.BinaryTreeRegressor` + :py:meth:`verticapy.machine_learning.memmodel.tree.BinaryTreeRegressor` model: .. ipython:: python @@ -635,7 +635,7 @@ def _scoring_function(self, node_id: int = 0) -> float: class BinaryTreeAnomaly(Tree): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of binary trees for anomaly detection. Parameters @@ -680,7 +680,7 @@ class BinaryTreeAnomaly(Tree): child node id's, feature and threshold value to split a node. Final values at leaf nodes are also required. Let's create a - :py:mod:`verticapy.machine_learning.memmodel.tree.BinaryTreeAnomaly` + :py:meth:`verticapy.machine_learning.memmodel.tree.BinaryTreeAnomaly` model: .. ipython:: python @@ -842,7 +842,7 @@ def _scoring_function(self, node_id: int = 0) -> float: class BinaryTreeClassifier(Tree): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of binary trees for classification. Parameters @@ -888,7 +888,7 @@ class BinaryTreeClassifier(Tree): and right child node id's, feature and threshold value to split a node. Final values at leaf nodes and name of classes are also required. Let's create a - :py:mod:`verticapy.machine_learning.memmodel.tree.BinaryTreeClassifier` + :py:meth:`verticapy.machine_learning.memmodel.tree.BinaryTreeClassifier` model. .. ipython:: python @@ -1062,7 +1062,7 @@ def _scoring_function_proba(self, node_id: int = 0) -> float: class NonBinaryTree(Tree): """ - :py:mod:`verticapy.machine_learning.memmodel.base.InMemoryModel` + :py:meth:`verticapy.machine_learning.memmodel.base.InMemoryModel` implementation of non-binary trees. Parameters @@ -1129,7 +1129,7 @@ class NonBinaryTree(Tree): Our non-binary tree is ready, we will now provide information about classes and create a - :py:mod:`verticapy.machine_learning.memmodel.tree.NonBinaryTree` + :py:meth:`verticapy.machine_learning.memmodel.tree.NonBinaryTree` model. .. ipython:: python diff --git a/verticapy/machine_learning/metrics/__init__.py b/verticapy/machine_learning/metrics/__init__.py index cbb0df8aa..ea91e94e8 100755 --- a/verticapy/machine_learning/metrics/__init__.py +++ b/verticapy/machine_learning/metrics/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/metrics/classification.py b/verticapy/machine_learning/metrics/classification.py index 20217d8a9..46c183590 100755 --- a/verticapy/machine_learning/metrics/classification.py +++ b/verticapy/machine_learning/metrics/classification.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -371,7 +371,7 @@ def confusion_matrix( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. @@ -411,7 +411,7 @@ def confusion_matrix( .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ if isinstance(pos_label, NoneType) and isinstance(labels, NoneType): pos_label = 1 @@ -589,13 +589,13 @@ def accuracy_score( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _accuracy_score, @@ -732,13 +732,13 @@ def balanced_accuracy_score( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _balanced_accuracy_score, @@ -877,13 +877,13 @@ def critical_success_index( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _critical_success_index, @@ -1025,13 +1025,13 @@ def diagnostic_odds_ratio( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _diagnostic_odds_ratio, @@ -1170,13 +1170,13 @@ def f1_score( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _f1_score, @@ -1314,13 +1314,13 @@ def false_negative_rate( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score(_false_negative_rate, **locals()) @@ -1455,13 +1455,13 @@ def false_positive_rate( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _false_positive_rate, @@ -1599,13 +1599,13 @@ def false_discovery_rate( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _false_discovery_rate, @@ -1743,13 +1743,13 @@ def false_omission_rate( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _false_omission_rate, @@ -1887,13 +1887,13 @@ def fowlkes_mallows_index( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _fowlkes_mallows_index, @@ -2031,13 +2031,13 @@ def informedness( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _informedness, @@ -2177,13 +2177,13 @@ def markedness( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _markedness, @@ -2325,13 +2325,13 @@ def matthews_corrcoef( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _matthews_corrcoef, @@ -2469,13 +2469,13 @@ def negative_predictive_score( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _negative_predictive_score, @@ -2613,13 +2613,13 @@ def negative_likelihood_ratio( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _negative_likelihood_ratio, @@ -2758,13 +2758,13 @@ def positive_likelihood_ratio( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _positive_likelihood_ratio, @@ -2902,13 +2902,13 @@ def precision_score( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _precision_score, @@ -3047,13 +3047,13 @@ def prevalence_threshold( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _prevalence_threshold, @@ -3191,13 +3191,13 @@ def recall_score( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _recall_score, @@ -3335,13 +3335,13 @@ def specificity_score( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_score( _specificity_score, @@ -3828,13 +3828,13 @@ def best_cutoff( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ if not isinstance(pos_label, NoneType) or isinstance(labels, NoneType): threshold, false_positive, true_positive = _compute_function_metrics( @@ -3989,13 +3989,13 @@ def average_precision_score( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ if not isinstance(pos_label, NoneType) or isinstance(labels, NoneType): recall, precision = _compute_function_metrics( @@ -4212,13 +4212,13 @@ def roc_auc_score( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_auc_score( y_true=y_true, @@ -4380,13 +4380,13 @@ def prc_auc_score( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return _compute_final_auc_score( y_true=y_true, @@ -4537,13 +4537,13 @@ def log_loss( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ if not isinstance(pos_label, NoneType) or isinstance(labels, NoneType): y_s = _get_yscore(y_score, labels, pos_label) @@ -4901,7 +4901,7 @@ def classification_report( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. @@ -4945,7 +4945,7 @@ def classification_report( .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ # Initialization diff --git a/verticapy/machine_learning/metrics/plotting.py b/verticapy/machine_learning/metrics/plotting.py index 224c8c4f8..fe6eb08b8 100755 --- a/verticapy/machine_learning/metrics/plotting.py +++ b/verticapy/machine_learning/metrics/plotting.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/metrics/regression.py b/verticapy/machine_learning/metrics/regression.py index 5db0592dc..6b57ab300 100755 --- a/verticapy/machine_learning/metrics/regression.py +++ b/verticapy/machine_learning/metrics/regression.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -137,13 +137,13 @@ def aic_score( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return regression_report(y_true, y_score, input_relation, metrics="aic", k=k) @@ -224,13 +224,13 @@ def bic_score( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return regression_report(y_true, y_score, input_relation, metrics="bic", k=k) @@ -310,13 +310,13 @@ def explained_variance(y_true: str, y_score: str, input_relation: SQLRelation) - .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return regression_report( y_true, y_score, input_relation, metrics="explained_variance" @@ -398,13 +398,13 @@ def max_error(y_true: str, y_score: str, input_relation: SQLRelation) -> float: .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return regression_report(y_true, y_score, input_relation, metrics="max_error") @@ -486,13 +486,13 @@ def mean_absolute_error( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return regression_report(y_true, y_score, input_relation, metrics="mae") @@ -577,13 +577,13 @@ def mean_squared_error( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return regression_report( y_true, y_score, input_relation, metrics="rmse" if root else "mse" @@ -667,13 +667,13 @@ def mean_squared_log_error( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return regression_report(y_true, y_score, input_relation, metrics="msle") @@ -755,13 +755,13 @@ def median_absolute_error( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return regression_report( y_true, y_score, input_relation, metrics="median_absolute_error" @@ -840,13 +840,13 @@ def quantile_error( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return regression_report(y_true, y_score, input_relation, metrics=f"qe{100 * q}%") @@ -937,13 +937,13 @@ def r2_score( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ if adj: kwargs = {"metrics": "r2_adj", "k": k} @@ -1028,13 +1028,13 @@ def anova_table( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ n, avg = _executeSQL( query=f""" @@ -1193,13 +1193,13 @@ def regression_report( .. note:: VerticaPy uses simple SQL queries to compute various metrics. - You can use the :py:mod:`verticapy.set_option` function with + You can use the :py:meth:`verticapy.set_option` function with the ``sql_on`` parameter to enable SQL generation and examine the generated queries. .. seealso:: - :py:mod:`verticapy.vDataFrame.score` + | :py:meth:`verticapy.vDataFrame.score` : Computes the input ML metric. """ return_scalar = False if isinstance(metrics, str): diff --git a/verticapy/machine_learning/model_selection/__init__.py b/verticapy/machine_learning/model_selection/__init__.py index 63e84e7a2..3b7f23747 100755 --- a/verticapy/machine_learning/model_selection/__init__.py +++ b/verticapy/machine_learning/model_selection/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/model_selection/hp_tuning/__init__.py b/verticapy/machine_learning/model_selection/hp_tuning/__init__.py index 971d2343e..d2dd18c77 100755 --- a/verticapy/machine_learning/model_selection/hp_tuning/__init__.py +++ b/verticapy/machine_learning/model_selection/hp_tuning/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/model_selection/hp_tuning/cv.py b/verticapy/machine_learning/model_selection/hp_tuning/cv.py index b7eb3c86f..2e7fdf4c2 100755 --- a/verticapy/machine_learning/model_selection/hp_tuning/cv.py +++ b/verticapy/machine_learning/model_selection/hp_tuning/cv.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/model_selection/hp_tuning/param_gen.py b/verticapy/machine_learning/model_selection/hp_tuning/param_gen.py index 3c50f6ad0..589e076dc 100755 --- a/verticapy/machine_learning/model_selection/hp_tuning/param_gen.py +++ b/verticapy/machine_learning/model_selection/hp_tuning/param_gen.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/model_selection/hp_tuning/plotting.py b/verticapy/machine_learning/model_selection/hp_tuning/plotting.py index 274a8cd64..c807b4f09 100755 --- a/verticapy/machine_learning/model_selection/hp_tuning/plotting.py +++ b/verticapy/machine_learning/model_selection/hp_tuning/plotting.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/model_selection/kmeans.py b/verticapy/machine_learning/model_selection/kmeans.py index 1f035101a..5a1466baf 100755 --- a/verticapy/machine_learning/model_selection/kmeans.py +++ b/verticapy/machine_learning/model_selection/kmeans.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/model_selection/model_validation.py b/verticapy/machine_learning/model_selection/model_validation.py index 23f1d1379..8173f7c0f 100755 --- a/verticapy/machine_learning/model_selection/model_validation.py +++ b/verticapy/machine_learning/model_selection/model_validation.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/model_selection/statistical_tests/__init__.py b/verticapy/machine_learning/model_selection/statistical_tests/__init__.py index c3a165640..e4622c0dc 100755 --- a/verticapy/machine_learning/model_selection/statistical_tests/__init__.py +++ b/verticapy/machine_learning/model_selection/statistical_tests/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/model_selection/statistical_tests/norm.py b/verticapy/machine_learning/model_selection/statistical_tests/norm.py index 0afdb797d..8bf89c952 100755 --- a/verticapy/machine_learning/model_selection/statistical_tests/norm.py +++ b/verticapy/machine_learning/model_selection/statistical_tests/norm.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -88,7 +88,7 @@ def jarque_bera(input_relation: SQLRelation, column: str) -> tuple[float, float] # Dataset data = np.random.normal(mean, std_dev, N) - Now we can create the ``vDataFrame``: + Now we can create the :py:class:`vDataFrame`: .. ipython:: python @@ -116,7 +116,7 @@ def jarque_bera(input_relation: SQLRelation, column: str) -> tuple[float, float] from verticapy.machine_learning.model_selection.statistical_tests import jarque_bera - And simply apply it on the ``vDataFrame``: + And simply apply it on the :py:class:`vDataFrame`: .. ipython:: python @@ -190,7 +190,7 @@ def jarque_bera(input_relation: SQLRelation, column: str) -> tuple[float, float] .. raw:: html :file: SPHINX_DIRECTORY/figures/plotting_machine_learning_model_selection_norm_jarque_bera_2.html - And simply apply it on the ``vDataFrame``: + And simply apply it on the :py:class:`vDataFrame`: .. ipython:: python @@ -277,7 +277,7 @@ def kurtosistest(input_relation: SQLRelation, column: str) -> tuple[float, float # Dataset data = np.random.normal(mean, std_dev, N) - Now we can create the ``vDataFrame``: + Now we can create the :py:class:`vDataFrame`: .. ipython:: python @@ -305,7 +305,7 @@ def kurtosistest(input_relation: SQLRelation, column: str) -> tuple[float, float from verticapy.machine_learning.model_selection.statistical_tests import kurtosistest - And simply apply it on the ``vDataFrame``: + And simply apply it on the :py:class:`vDataFrame`: .. ipython:: python @@ -380,7 +380,7 @@ def kurtosistest(input_relation: SQLRelation, column: str) -> tuple[float, float .. raw:: html :file: SPHINX_DIRECTORY/figures/plotting_machine_learning_model_selection_norm_kurtosistest_2.html - And simply apply it on the ``vDataFrame``: + And simply apply it on the :py:class:`vDataFrame`: .. ipython:: python @@ -476,7 +476,7 @@ def normaltest(input_relation: SQLRelation, column: str) -> tuple[float, float]: # Dataset data = np.random.normal(mean, std_dev, N) - Now we can create the ``vDataFrame``: + Now we can create the :py:class:`vDataFrame`: .. ipython:: python @@ -504,7 +504,7 @@ def normaltest(input_relation: SQLRelation, column: str) -> tuple[float, float]: from verticapy.machine_learning.model_selection.statistical_tests import normaltest - And simply apply it on the ``vDataFrame``: + And simply apply it on the :py:class:`vDataFrame`: .. ipython:: python @@ -578,7 +578,7 @@ def normaltest(input_relation: SQLRelation, column: str) -> tuple[float, float]: .. raw:: html :file: SPHINX_DIRECTORY/figures/plotting_machine_learning_model_selection_norm_normaltest_2.html - And simply apply it on the ``vDataFrame``: + And simply apply it on the :py:class:`vDataFrame`: .. ipython:: python @@ -666,7 +666,7 @@ def skewtest(input_relation: SQLRelation, column: str) -> tuple[float, float]: # Dataset data = np.random.normal(mean, std_dev, N) - Now we can create the ``vDataFrame``: + Now we can create the :py:class:`vDataFrame`: .. ipython:: python @@ -694,7 +694,7 @@ def skewtest(input_relation: SQLRelation, column: str) -> tuple[float, float]: from verticapy.machine_learning.model_selection.statistical_tests import skewtest - And simply apply it on the ``vDataFrame``: + And simply apply it on the :py:class:`vDataFrame`: .. ipython:: python @@ -782,7 +782,7 @@ def skewtest(input_relation: SQLRelation, column: str) -> tuple[float, float]: .. raw:: html :file: SPHINX_DIRECTORY/figures/plotting_machine_learning_model_selection_norm_skewtest_2.html - And simply apply it on the ``vDataFrame``: + And simply apply it on the :py:class:`vDataFrame`: .. ipython:: python diff --git a/verticapy/machine_learning/model_selection/statistical_tests/ols.py b/verticapy/machine_learning/model_selection/statistical_tests/ols.py index 09c0588e6..da00c52bc 100755 --- a/verticapy/machine_learning/model_selection/statistical_tests/ols.py +++ b/verticapy/machine_learning/model_selection/statistical_tests/ols.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -99,7 +99,7 @@ def het_breuschpagan( y_vals = [0, 2, 4, 6, 8, 10] + np.random.normal(0, 0.4, 6) - We can use those values to create the ``vDataFrame``: + We can use those values to create the :py:class:`vDataFrame`: .. ipython:: python @@ -122,7 +122,7 @@ def het_breuschpagan( model.fit(input_relation = vdf, X = "x", y = "y") - We can create a column in the ``vDataFrame`` that + We can create a column in the :py:class:`vDataFrame` that has the predictions: .. ipython:: python @@ -160,7 +160,7 @@ def het_breuschpagan( from verticapy.machine_learning.model_selection.statistical_tests import het_breuschpagan - And simply apply it on the ``vDataFrame``: + And simply apply it on the :py:class:`vDataFrame`: .. ipython:: python @@ -238,7 +238,7 @@ def het_breuschpagan( model.fit(input_relation = vdf, X = "x", y = "y") - We can create a column in the ``vDataFrame`` that + We can create a column in the :py:class:`vDataFrame` that has the predictions: .. ipython:: python @@ -395,7 +395,7 @@ def het_goldfeldquandt( x_val = list(range(N)) y_val = [x * 2 for x in x_val] + np.random.normal(0, 0.4, N) - We can use those values to create the ``vDataFrame``: + We can use those values to create the :py:class:`vDataFrame`: .. ipython:: python @@ -432,7 +432,7 @@ def het_goldfeldquandt( from verticapy.machine_learning.model_selection.statistical_tests import het_goldfeldquandt - And simply apply it on the ``vDataFrame``: + And simply apply it on the :py:class:`vDataFrame`: .. ipython:: python @@ -648,7 +648,7 @@ def het_white( y_vals = [0, 2, 4, 6, 8, 10] + np.random.normal(0, 0.4, 6) - We can use those values to create the ``vDataFrame``: + We can use those values to create the :py:class:`vDataFrame`: .. ipython:: python @@ -671,7 +671,7 @@ def het_white( model.fit(input_relation = vdf, X = "x", y = "y") - We can create a column in the ``vDataFrame`` that + We can create a column in the :py:class:`vDataFrame` that has the predictions: .. ipython:: python @@ -709,7 +709,7 @@ def het_white( from verticapy.machine_learning.model_selection.statistical_tests import het_white - And simply apply it on the ``vDataFrame``: + And simply apply it on the :py:class:`vDataFrame`: .. ipython:: python @@ -787,7 +787,7 @@ def het_white( model.fit(input_relation = vdf, X = "x", y = "y") - We can create a column in the ``vDataFrame`` that + We can create a column in the :py:class:`vDataFrame` that has the predictions: .. ipython:: python @@ -954,7 +954,7 @@ def variance_inflation_factor( x_val_2 = [2 * x + np.random.normal(scale = 4) for x in x_val_1] x_val_3 = np.random.normal(0, 4, N) - We can use those values to create the ``vDataFrame``: + We can use those values to create the :py:class:`vDataFrame`: .. ipython:: python diff --git a/verticapy/machine_learning/model_selection/statistical_tests/tsa.py b/verticapy/machine_learning/model_selection/statistical_tests/tsa.py index 7db344a18..038822ee1 100755 --- a/verticapy/machine_learning/model_selection/statistical_tests/tsa.py +++ b/verticapy/machine_learning/model_selection/statistical_tests/tsa.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -250,7 +250,7 @@ def adfuller( from verticapy.machine_learning.model_selection.statistical_tests import adfuller - And then simply applying it on the ``vDataFrame``: + And then simply applying it on the :py:class:`vDataFrame`: .. ipython:: python @@ -506,7 +506,7 @@ def mkt( from verticapy.machine_learning.model_selection.statistical_tests import mkt - And then simply applying it on the ``vDataFrame``: + And then simply applying it on the :py:class:`vDataFrame`: .. ipython:: python @@ -944,7 +944,7 @@ def durbin_watson( model.fit(vdf, X = "day", y = "y1") - We can create a column in the ``vDataFrame`` that + We can create a column in the :py:class:`vDataFrame` that has the predictions: .. code-block:: python diff --git a/verticapy/machine_learning/model_selection/variables_selection.py b/verticapy/machine_learning/model_selection/variables_selection.py index 6b3e9f88a..1c33ebd27 100755 --- a/verticapy/machine_learning/model_selection/variables_selection.py +++ b/verticapy/machine_learning/model_selection/variables_selection.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/vertica/__init__.py b/verticapy/machine_learning/vertica/__init__.py index ae28adb28..6c492c6e1 100755 --- a/verticapy/machine_learning/vertica/__init__.py +++ b/verticapy/machine_learning/vertica/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/vertica/automl/__init__.py b/verticapy/machine_learning/vertica/automl/__init__.py index 5c50d9cc4..ccfdf61ca 100755 --- a/verticapy/machine_learning/vertica/automl/__init__.py +++ b/verticapy/machine_learning/vertica/automl/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/vertica/automl/clustering.py b/verticapy/machine_learning/vertica/automl/clustering.py index 65be04c18..03226b3d7 100755 --- a/verticapy/machine_learning/vertica/automl/clustering.py +++ b/verticapy/machine_learning/vertica/automl/clustering.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/vertica/automl/dataprep.py b/verticapy/machine_learning/vertica/automl/dataprep.py index b98b29bbc..ba32f3c0c 100755 --- a/verticapy/machine_learning/vertica/automl/dataprep.py +++ b/verticapy/machine_learning/vertica/automl/dataprep.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/vertica/automl/supervised.py b/verticapy/machine_learning/vertica/automl/supervised.py index cb9e4469a..2db1cd724 100755 --- a/verticapy/machine_learning/vertica/automl/supervised.py +++ b/verticapy/machine_learning/vertica/automl/supervised.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/vertica/base.py b/verticapy/machine_learning/vertica/base.py index fe49849d8..ea2afe062 100755 --- a/verticapy/machine_learning/vertica/base.py +++ b/verticapy/machine_learning/vertica/base.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/vertica/cluster.py b/verticapy/machine_learning/vertica/cluster.py index 5b519f80e..f4012d275 100755 --- a/verticapy/machine_learning/vertica/cluster.py +++ b/verticapy/machine_learning/vertica/cluster.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -272,13 +272,13 @@ class KMeans(Clustering): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.cluster.Clustering.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.cluster.Clustering.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.cluster.Clustering.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.cluster.Clustering.get_vertica_attributes`` method. Examples @@ -293,7 +293,7 @@ class KMeans(Clustering): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -301,7 +301,7 @@ class KMeans(Clustering): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -364,7 +364,7 @@ class KMeans(Clustering): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -387,9 +387,9 @@ class KMeans(Clustering): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -595,7 +595,7 @@ class KMeans(Clustering): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.tree.KMeans.to_python` + :py:meth:`verticapy.machine_learning.vertica.tree.KMeans.to_python` method is used to retrieve the anomaly score. For specific details on how to use this method for different model types, refer to the relevant @@ -832,13 +832,13 @@ class KPrototypes(KMeans): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.cluster.Clustering.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.cluster.Clustering.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.cluster.Clustering.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.cluster.Clustering.get_vertica_attributes`` method. Examples @@ -853,7 +853,7 @@ class KPrototypes(KMeans): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -861,7 +861,7 @@ class KPrototypes(KMeans): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -925,7 +925,7 @@ class KPrototypes(KMeans): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -948,7 +948,7 @@ class KPrototypes(KMeans): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. .. note:: @@ -1031,7 +1031,7 @@ class KPrototypes(KMeans): As we are using a categorical feature in this example, this plot cannot be drawn. It is only for numeric features. - Please have a look at :py:mod:`verticapy.machine_learning.vertica.KMeans` + Please have a look at :py:meth:`verticapy.machine_learning.vertica.KMeans` for plotting examples. Plots - Voronoi @@ -1048,7 +1048,7 @@ class KPrototypes(KMeans): As we are using a categorical feature in this example, this plot cannot be drawn. It is only for numeric features. - Please have a look at :py:mod:`verticapy.machine_learning.vertica.KMeans` + Please have a look at :py:meth:`verticapy.machine_learning.vertica.KMeans` for plotting examples. @@ -1066,7 +1066,7 @@ class KPrototypes(KMeans): As we are using a categorical feature in this example, this plot cannot be drawn. It is only for numeric features. - Please have a look at :py:mod:`verticapy.machine_learning.vertica.KMeans` + Please have a look at :py:meth:`verticapy.machine_learning.vertica.KMeans` for plotting examples. .. note:: @@ -1153,7 +1153,7 @@ class KPrototypes(KMeans): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.tree.KPrototypes.to_python` + :py:meth:`verticapy.machine_learning.vertica.tree.KPrototypes.to_python` method is used to retrieve the anomaly score. For specific details on how to use this method for different model types, refer to the relevant @@ -1374,13 +1374,13 @@ class BisectingKMeans(KMeans, Tree): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.cluster.Clustering.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.cluster.Clustering.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.cluster.Clustering.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.cluster.Clustering.get_vertica_attributes`` method. Examples @@ -1395,7 +1395,7 @@ class BisectingKMeans(KMeans, Tree): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1403,7 +1403,7 @@ class BisectingKMeans(KMeans, Tree): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -1470,7 +1470,7 @@ class BisectingKMeans(KMeans, Tree): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -1493,9 +1493,9 @@ class BisectingKMeans(KMeans, Tree): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -1724,7 +1724,7 @@ class BisectingKMeans(KMeans, Tree): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.tree.BisectingKMeans.to_python` + :py:meth:`verticapy.machine_learning.vertica.tree.BisectingKMeans.to_python` method is used to retrieve the anomaly score. For specific details on how to use this method for different model types, refer to the relevant @@ -2009,7 +2009,7 @@ class DBSCAN(VerticaModel): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.base.VerticaModel.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.VerticaModel.get_attributes`` method. Examples @@ -2024,7 +2024,7 @@ class DBSCAN(VerticaModel): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -2032,7 +2032,7 @@ class DBSCAN(VerticaModel): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -2099,7 +2099,7 @@ class DBSCAN(VerticaModel): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. .. hint:: @@ -2512,7 +2512,7 @@ class NearestCentroid(MulticlassClassifier): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.base.VerticaModel.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.VerticaModel.get_attributes`` method. Examples @@ -2527,7 +2527,7 @@ class NearestCentroid(MulticlassClassifier): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -2535,7 +2535,7 @@ class NearestCentroid(MulticlassClassifier): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -2565,7 +2565,7 @@ class NearestCentroid(MulticlassClassifier): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -2579,7 +2579,7 @@ class NearestCentroid(MulticlassClassifier): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -2596,7 +2596,7 @@ class NearestCentroid(MulticlassClassifier): In VerticaPy, balancing a dataset to address class imbalances is made straightforward through the - :py:mod:`verticapy.machine_learning.vertica.preprocessing.balance` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.balance` function within the ``preprocessing`` module. This function enables users to rectify skewed class distributions efficiently. By specifying the target variable and setting parameters like @@ -2604,7 +2604,7 @@ class NearestCentroid(MulticlassClassifier): equitable representation of classes in their dataset. Whether opting for over-sampling, under-sampling, or a combination of both, VerticaPy's - :py:mod:`verticapy.machine_learning.vertica.preprocessing.balance` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.balance` function streamlines the process, empowering users to enhance the performance and fairness of their machine learning models trained on imbalanced data. @@ -2680,9 +2680,9 @@ class distributions. By addressing disparities in the number of .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -2747,7 +2747,7 @@ class distributions. By addressing disparities in the number of .. note:: - For multi-class scoring, ``verticapy`` allows the + For multi-class scoring, :py:mod:`verticapy` allows the flexibility to use three averaging techniques: micro, macro and weighted. Please refer to `this link `_ @@ -2795,10 +2795,10 @@ class distributions. By addressing disparities in the number of Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.cluster.NearestCentroid.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.cluster.NearestCentroid.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Probabilities @@ -3003,7 +3003,7 @@ class distributions. By addressing disparities in the number of .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.cluster.NearestCentroid.to_python` + :py:meth:`verticapy.machine_learning.vertica.cluster.NearestCentroid.to_python` method is used to retrieve predictions, probabilities, or cluster distances. For specific details on how to use this method for different model types, refer to the relevant diff --git a/verticapy/machine_learning/vertica/decomposition.py b/verticapy/machine_learning/vertica/decomposition.py index 6be36251f..7700f4f0d 100755 --- a/verticapy/machine_learning/vertica/decomposition.py +++ b/verticapy/machine_learning/vertica/decomposition.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -449,13 +449,13 @@ class PCA(Decomposition): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.decomposition.Decomposition.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.decomposition.Decomposition.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.decomposition.Decomposition.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.decomposition.Decomposition.get_vertica_attributes`` method. Examples @@ -470,7 +470,7 @@ class PCA(Decomposition): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -478,7 +478,7 @@ class PCA(Decomposition): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -548,7 +548,7 @@ class PCA(Decomposition): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -571,7 +571,7 @@ class PCA(Decomposition): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. Scores @@ -585,7 +585,7 @@ class PCA(Decomposition): model.score() For more details on the function, check out - :py:mod:`verticapy.machine_learning.PCA.score` + :py:meth:`verticapy.machine_learning.PCA.score` You can also fetch the explained variance by: @@ -603,8 +603,8 @@ class PCA(Decomposition): model.transform(data) - Please refer to :py:mod:`verticapy.machine_learning.PCA.transform` - for more details on transforming a ``vDataFrame``. + Please refer to :py:meth:`verticapy.machine_learning.PCA.transform` + for more details on transforming a :py:class:`vDataFrame`. Similarly, you can perform the inverse tranform to get the original features using: @@ -721,7 +721,7 @@ class PCA(Decomposition): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.decomposition.PCA.to_python` + :py:meth:`verticapy.machine_learning.vertica.decomposition.PCA.to_python` method is used to retrieve the Principal Component values. For specific details on how to use this method for different model types, refer to the relevant @@ -860,13 +860,13 @@ class MCA(PCA): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.decomposition.Decomposition.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.decomposition.Decomposition.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.decomposition.Decomposition.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.decomposition.Decomposition.get_vertica_attributes`` method. Examples @@ -881,7 +881,7 @@ class MCA(PCA): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -889,7 +889,7 @@ class MCA(PCA): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -969,7 +969,7 @@ class MCA(PCA): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. Scores @@ -983,7 +983,7 @@ class MCA(PCA): model.score() For more details on the function, check out - :py:mod:`verticapy.machine_learning.MCA.score` + :py:meth:`verticapy.machine_learning.MCA.score` You can also fetch the explained variance by: @@ -1001,8 +1001,8 @@ class MCA(PCA): model.transform(tcdt) - Please refer to :py:mod:`verticapy.machine_learning.MCA.transform` - for more details on transforming a ``vDataFrame``. + Please refer to :py:meth:`verticapy.machine_learning.MCA.transform` + for more details on transforming a :py:class:`vDataFrame`. Similarly, you can perform the inverse tranform to get the original features using: @@ -1118,7 +1118,7 @@ class MCA(PCA): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.decomposition.MCA.to_python` + :py:meth:`verticapy.machine_learning.vertica.decomposition.MCA.to_python` method is used to retrieve the Principal Component values. For specific details on how to use this method for different model types, refer to the relevant @@ -1396,13 +1396,13 @@ class SVD(Decomposition): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.decomposition.Decomposition.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.decomposition.Decomposition.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.decomposition.Decomposition.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.decomposition.Decomposition.get_vertica_attributes`` method. Examples @@ -1417,7 +1417,7 @@ class SVD(Decomposition): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1425,7 +1425,7 @@ class SVD(Decomposition): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -1495,7 +1495,7 @@ class SVD(Decomposition): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -1518,7 +1518,7 @@ class SVD(Decomposition): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. Scores @@ -1532,7 +1532,7 @@ class SVD(Decomposition): model.score() For more details on the function, check out - :py:mod:`verticapy.machine_learning.SVD.score` + :py:meth:`verticapy.machine_learning.SVD.score` You can also fetch the explained variance by: @@ -1550,8 +1550,8 @@ class SVD(Decomposition): model.transform(data) - Please refer to :py:mod:`verticapy.machine_learning.SVD.transform` - for more details on transforming a ``vDataFrame``. + Please refer to :py:meth:`verticapy.machine_learning.SVD.transform` + for more details on transforming a :py:class:`vDataFrame`. Similarly, you can perform the inverse tranform to get the original features using: @@ -1668,7 +1668,7 @@ class SVD(Decomposition): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.decomposition.SVD.to_python` + :py:meth:`verticapy.machine_learning.vertica.decomposition.SVD.to_python` method is used to retrieve the Principal Component values. For specific details on how to use this method for different model types, refer to the relevant diff --git a/verticapy/machine_learning/vertica/ensemble.py b/verticapy/machine_learning/vertica/ensemble.py index d5f37a7be..329d4cc41 100755 --- a/verticapy/machine_learning/vertica/ensemble.py +++ b/verticapy/machine_learning/vertica/ensemble.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -419,7 +419,7 @@ class RandomForestRegressor(Regressor, RandomForest): each possessing various attributes. For more detailed information, refer to the documentation for - :py:mod:`verticapy.machine_learning.memmodel.tree.BinaryTreeRegressor`. + :py:meth:`verticapy.machine_learning.memmodel.tree.BinaryTreeRegressor`. features_importance_: numpy.array The importance of features. It is calculated using the MDI (Mean Decreased Impurity). To @@ -427,7 +427,7 @@ class RandomForestRegressor(Regressor, RandomForest): scores of each tree, normalizes them and applies an activation function to scale them. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.features_importance` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -437,7 +437,7 @@ class RandomForestRegressor(Regressor, RandomForest): The importance of features is calculated using the MDI (Mean Decreased Impurity). It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.features_importance` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -447,13 +447,13 @@ class RandomForestRegressor(Regressor, RandomForest): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.get_vertica_attributes`` method. Examples @@ -474,7 +474,7 @@ class RandomForestRegressor(Regressor, RandomForest): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -482,7 +482,7 @@ class RandomForestRegressor(Regressor, RandomForest): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -512,7 +512,7 @@ class RandomForestRegressor(Regressor, RandomForest): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -526,7 +526,7 @@ class RandomForestRegressor(Regressor, RandomForest): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -564,7 +564,7 @@ class RandomForestRegressor(Regressor, RandomForest): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -599,9 +599,9 @@ class RandomForestRegressor(Regressor, RandomForest): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -659,7 +659,7 @@ class RandomForestRegressor(Regressor, RandomForest): E.g. ``model.report(metrics = ["mse", "r2"])``. You can utilize the - :py:mod:`verticapy.machine_learning.vertica.ensemble.RandomForestRegressor.score` + :py:meth:`verticapy.machine_learning.vertica.ensemble.RandomForestRegressor.score` function to calculate various regression metrics, with the R-squared being the default. .. ipython:: python @@ -712,10 +712,10 @@ class RandomForestRegressor(Regressor, RandomForest): Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.ensemble.RandomForestRegressor.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.ensemble.RandomForestRegressor.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Plots @@ -818,7 +818,7 @@ class RandomForestRegressor(Regressor, RandomForest): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.tree.RandomForestRegressor.to_python` + :py:meth:`verticapy.machine_learning.vertica.tree.RandomForestRegressor.to_python` method is used to retrieve predictions, probabilities, or cluster distances. For specific details on how to use this method for different model types, refer to the relevant @@ -988,7 +988,7 @@ class XGBRegressor(Regressor, XGBoost): each possessing various attributes. For more detailed information, refer to the documentation for - :py:mod:`verticapy.machine_learning.memmodel.tree.BinaryTreeRegressor`. + :py:meth:`verticapy.machine_learning.memmodel.tree.BinaryTreeRegressor`. features_importance_: numpy.array The importance of features. It is calculated using the average gain of each tree. To determine @@ -996,7 +996,7 @@ class XGBRegressor(Regressor, XGBoost): tree, normalizes them and applies an activation function to scale them. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.features_importance` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -1006,7 +1006,7 @@ class XGBRegressor(Regressor, XGBoost): The importance of features is calculated using the average gain of each tree. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.features_importance` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -1028,13 +1028,13 @@ class XGBRegressor(Regressor, XGBoost): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.get_vertica_attributes`` method. Examples @@ -1055,7 +1055,7 @@ class XGBRegressor(Regressor, XGBoost): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -1063,7 +1063,7 @@ class XGBRegressor(Regressor, XGBoost): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1093,7 +1093,7 @@ class XGBRegressor(Regressor, XGBoost): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -1107,7 +1107,7 @@ class XGBRegressor(Regressor, XGBoost): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -1149,7 +1149,7 @@ class XGBRegressor(Regressor, XGBoost): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -1184,9 +1184,9 @@ class XGBRegressor(Regressor, XGBoost): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -1244,7 +1244,7 @@ class XGBRegressor(Regressor, XGBoost): E.g. ``model.report(metrics = ["mse", "r2"])``. You can utilize the - :py:mod:`verticapy.machine_learning.vertica.ensemble.XGBRegressor.score` + :py:meth:`verticapy.machine_learning.vertica.ensemble.XGBRegressor.score` function to calculate various regression metrics, with the R-squared being the default. .. ipython:: python @@ -1297,10 +1297,10 @@ class XGBRegressor(Regressor, XGBoost): Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.ensemble.XGBRegressor.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.ensemble.XGBRegressor.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Plots @@ -1413,7 +1413,7 @@ class XGBRegressor(Regressor, XGBoost): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.tree.XGBRegressor.to_python` + :py:meth:`verticapy.machine_learning.vertica.tree.XGBRegressor.to_python` method is used to retrieve predictions, probabilities, or cluster distances. For specific details on how to use this method for different model types, refer to the relevant @@ -1602,7 +1602,7 @@ class RandomForestClassifier(MulticlassClassifier, RandomForest): each possessing various attributes. For more detailed information, refer to the documentation for - :py:mod:`verticapy.machine_learning.memmodel.tree.BinaryTreeClassifier`. + :py:meth:`verticapy.machine_learning.memmodel.tree.BinaryTreeClassifier`. features_importance_: numpy.array The importance of features. It is calculated using the MDI (Mean Decreased Impurity). To @@ -1610,7 +1610,7 @@ class RandomForestClassifier(MulticlassClassifier, RandomForest): scores of each tree, normalizes them and applies an activation function to scale them. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.features_importance` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -1620,7 +1620,7 @@ class RandomForestClassifier(MulticlassClassifier, RandomForest): The importance of features is calculated using the MDI (Mean Decreased Impurity). It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.features_importance` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -1632,13 +1632,13 @@ class RandomForestClassifier(MulticlassClassifier, RandomForest): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.get_vertica_attributes`` method. Examples @@ -1659,7 +1659,7 @@ class RandomForestClassifier(MulticlassClassifier, RandomForest): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -1667,7 +1667,7 @@ class RandomForestClassifier(MulticlassClassifier, RandomForest): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -1697,7 +1697,7 @@ class RandomForestClassifier(MulticlassClassifier, RandomForest): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -1711,7 +1711,7 @@ class RandomForestClassifier(MulticlassClassifier, RandomForest): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -1728,7 +1728,7 @@ class RandomForestClassifier(MulticlassClassifier, RandomForest): In VerticaPy, balancing a dataset to address class imbalances is made straightforward through the - :py:mod:`verticapy.machine_learning.vertica.preprocessing.balance` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.balance` function within the ``preprocessing`` module. This function enables users to rectify skewed class distributions efficiently. By specifying the target variable and setting parameters like @@ -1736,7 +1736,7 @@ class RandomForestClassifier(MulticlassClassifier, RandomForest): equitable representation of classes in their dataset. Whether opting for over-sampling, under-sampling, or a combination of both, VerticaPy's - :py:mod:`verticapy.machine_learning.vertica.preprocessing.balance` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.balance` function streamlines the process, empowering users to enhance the performance and fairness of their machine learning models trained on imbalanced data. @@ -1807,7 +1807,7 @@ class distributions. By addressing disparities in the number of .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -1842,9 +1842,9 @@ class distributions. By addressing disparities in the number of .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -1920,7 +1920,7 @@ class distributions. By addressing disparities in the number of :file: SPHINX_DIRECTORY/figures/machine_learning_vertica_rf_classifier_report_cutoff.html You can also use the - :py:mod:`verticapy.machine_learning.vertica.ensemble.RandomForestClassifier.score` + :py:meth:`verticapy.machine_learning.vertica.ensemble.RandomForestClassifier.score` function to compute any classification metric. The default metric is the accuracy: .. ipython:: python @@ -1973,10 +1973,10 @@ class distributions. By addressing disparities in the number of Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.ensemble.RandomForestClassifier.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.ensemble.RandomForestClassifier.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Probabilities @@ -2205,7 +2205,7 @@ class distributions. By addressing disparities in the number of .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.tree.RandomForestClassifier.to_python` + :py:meth:`verticapy.machine_learning.vertica.tree.RandomForestClassifier.to_python` method is used to retrieve predictions, probabilities, or cluster distances. For specific details on how to use this method for different model types, refer to the relevant @@ -2392,7 +2392,7 @@ class XGBClassifier(MulticlassClassifier, XGBoost): each possessing various attributes. For more detailed information, refer to the documentation for - :py:mod:`verticapy.machine_learning.memmodel.tree.BinaryTreeClassifier`. + :py:meth:`verticapy.machine_learning.memmodel.tree.BinaryTreeClassifier`. features_importance_: numpy.array The importance of features. It is calculated using the average gain of each tree. To determine @@ -2400,7 +2400,7 @@ class XGBClassifier(MulticlassClassifier, XGBoost): tree, normalizes them and applies an activation function to scale them. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.features_importance` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -2410,7 +2410,7 @@ class XGBClassifier(MulticlassClassifier, XGBoost): The importance of features is calculated using the average gain of each tree. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.features_importance` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -2436,13 +2436,13 @@ class XGBClassifier(MulticlassClassifier, XGBoost): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.get_vertica_attributes`` method. Examples @@ -2463,7 +2463,7 @@ class XGBClassifier(MulticlassClassifier, XGBoost): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -2471,7 +2471,7 @@ class XGBClassifier(MulticlassClassifier, XGBoost): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -2501,7 +2501,7 @@ class XGBClassifier(MulticlassClassifier, XGBoost): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -2515,7 +2515,7 @@ class XGBClassifier(MulticlassClassifier, XGBoost): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -2532,7 +2532,7 @@ class XGBClassifier(MulticlassClassifier, XGBoost): In VerticaPy, balancing a dataset to address class imbalances is made straightforward through the - :py:mod:`verticapy.machine_learning.vertica.preprocessing.balance` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.balance` function within the ``preprocessing`` module. This function enables users to rectify skewed class distributions efficiently. By specifying the target variable and setting parameters like @@ -2540,7 +2540,7 @@ class XGBClassifier(MulticlassClassifier, XGBoost): equitable representation of classes in their dataset. Whether opting for over-sampling, under-sampling, or a combination of both, VerticaPy's - :py:mod:`verticapy.machine_learning.vertica.preprocessing.balance` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.balance` function streamlines the process, empowering users to enhance the performance and fairness of their machine learning models trained on imbalanced data. @@ -2615,7 +2615,7 @@ class distributions. By addressing disparities in the number of .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -2650,9 +2650,9 @@ class distributions. By addressing disparities in the number of .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -2728,7 +2728,7 @@ class distributions. By addressing disparities in the number of :file: SPHINX_DIRECTORY/figures/machine_learning_vertica_xgb_classifier_report_cutoff.html You can also use the - :py:mod:`verticapy.machine_learning.vertica.ensemble.XGBClassifier.score` + :py:meth:`verticapy.machine_learning.vertica.ensemble.XGBClassifier.score` function to compute any classification metric. The default metric is the accuracy: .. ipython:: python @@ -2781,10 +2781,10 @@ class distributions. By addressing disparities in the number of Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.ensemble.XGBClassifier.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.ensemble.XGBClassifier.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Probabilities @@ -3023,7 +3023,7 @@ class distributions. By addressing disparities in the number of .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.tree.XGBClassifier.to_python` + :py:meth:`verticapy.machine_learning.vertica.tree.XGBClassifier.to_python` method is used to retrieve predictions, probabilities, or cluster distances. For specific details on how to use this method for different model types, refer to the relevant @@ -3219,7 +3219,7 @@ class IsolationForest(Clustering, Tree): each possessing various attributes. For more detailed information, refer to the documentation for - :py:mod:`verticapy.machine_learning.memmodel.tree.BinaryTreeAnomaly`. + :py:meth:`verticapy.machine_learning.memmodel.tree.BinaryTreeAnomaly`. psy_: int Sampling size used to compute the final score. n_estimators_: int @@ -3228,13 +3228,13 @@ class IsolationForest(Clustering, Tree): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.get_vertica_attributes`` method. Examples @@ -3249,7 +3249,7 @@ class IsolationForest(Clustering, Tree): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -3257,7 +3257,7 @@ class IsolationForest(Clustering, Tree): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -3319,7 +3319,7 @@ class IsolationForest(Clustering, Tree): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -3342,9 +3342,9 @@ class IsolationForest(Clustering, Tree): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -3539,7 +3539,7 @@ class IsolationForest(Clustering, Tree): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.tree.IsolationForest.to_python` + :py:meth:`verticapy.machine_learning.vertica.tree.IsolationForest.to_python` method is used to retrieve the anomaly score. For specific details on how to use this method for different model types, refer to the relevant diff --git a/verticapy/machine_learning/vertica/feature_extraction/__init__.py b/verticapy/machine_learning/vertica/feature_extraction/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/machine_learning/vertica/feature_extraction/__init__.py +++ b/verticapy/machine_learning/vertica/feature_extraction/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/vertica/feature_extraction/text.py b/verticapy/machine_learning/vertica/feature_extraction/text.py index 73967fbbd..15e4bc77d 100644 --- a/verticapy/machine_learning/vertica/feature_extraction/text.py +++ b/verticapy/machine_learning/vertica/feature_extraction/text.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -150,13 +150,13 @@ class TfidfVectorizer(VerticaModel): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.base.VerticaModel.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.VerticaModel.get_attributes`` method. Examples -------- - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -164,7 +164,7 @@ class TfidfVectorizer(VerticaModel): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -188,7 +188,7 @@ class TfidfVectorizer(VerticaModel): "Data preprocessing is an important step in preparing data for machine learning.", ] - Next, we can insert this text into a ``vDataFrame``: + Next, we can insert this text into a :py:class:`vDataFrame`: .. ipython:: python @@ -300,7 +300,7 @@ class TfidfVectorizer(VerticaModel): model.stop_words_ .. seealso:: - | :py:mod:`verticapy.vDataColumn.pivot` : pivot vDataFrame. + | :py:meth:`verticapy.vDataColumn.pivot` : pivot vDataFrame. """ # Properties. diff --git a/verticapy/machine_learning/vertica/linear_model.py b/verticapy/machine_learning/vertica/linear_model.py index 4835e280e..011a642cb 100755 --- a/verticapy/machine_learning/vertica/linear_model.py +++ b/verticapy/machine_learning/vertica/linear_model.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -330,7 +330,7 @@ class ElasticNet(LinearModel, Regressor): based on their range. Subsequently, an activation function calculates the final score. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -338,13 +338,13 @@ class ElasticNet(LinearModel, Regressor): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_vertica_attributes`` method. Examples @@ -359,7 +359,7 @@ class ElasticNet(LinearModel, Regressor): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -367,7 +367,7 @@ class ElasticNet(LinearModel, Regressor): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -397,7 +397,7 @@ class ElasticNet(LinearModel, Regressor): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -411,7 +411,7 @@ class ElasticNet(LinearModel, Regressor): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -447,7 +447,7 @@ class ElasticNet(LinearModel, Regressor): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -495,9 +495,9 @@ class ElasticNet(LinearModel, Regressor): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -598,10 +598,10 @@ class ElasticNet(LinearModel, Regressor): Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Plots @@ -685,7 +685,7 @@ class ElasticNet(LinearModel, Regressor): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.to_python` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.to_python` method is used to retrieve predictions, probabilities, or cluster distances. For specific details on how to use this method for different model types, refer to the relevant @@ -799,7 +799,7 @@ class Lasso(LinearModel, Regressor): based on their range. Subsequently, an activation function calculates the final score. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -807,13 +807,13 @@ class Lasso(LinearModel, Regressor): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_vertica_attributes`` method. Examples @@ -828,7 +828,7 @@ class Lasso(LinearModel, Regressor): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -836,7 +836,7 @@ class Lasso(LinearModel, Regressor): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -866,7 +866,7 @@ class Lasso(LinearModel, Regressor): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -880,7 +880,7 @@ class Lasso(LinearModel, Regressor): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -914,7 +914,7 @@ class Lasso(LinearModel, Regressor): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -960,9 +960,9 @@ class Lasso(LinearModel, Regressor): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -1063,10 +1063,10 @@ class Lasso(LinearModel, Regressor): Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Plots @@ -1165,7 +1165,7 @@ class Lasso(LinearModel, Regressor): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.to_python` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.to_python` method is used to retrieve predictions, probabilities, or cluster distances. For specific details on how to use this method for different model types, refer to the relevant @@ -1270,7 +1270,7 @@ class LinearRegression(LinearModel, Regressor): the model coefficients, which are normalized based on their range. Subsequently, an activation function calculates the final score. - It is necessary to use the :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance`method + It is necessary to use the :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance`method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -1278,13 +1278,13 @@ class LinearRegression(LinearModel, Regressor): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_vertica_attributes`` method. Examples @@ -1299,7 +1299,7 @@ class LinearRegression(LinearModel, Regressor): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -1307,7 +1307,7 @@ class LinearRegression(LinearModel, Regressor): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1337,7 +1337,7 @@ class LinearRegression(LinearModel, Regressor): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -1351,7 +1351,7 @@ class LinearRegression(LinearModel, Regressor): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -1385,7 +1385,7 @@ class LinearRegression(LinearModel, Regressor): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -1430,9 +1430,9 @@ class LinearRegression(LinearModel, Regressor): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -1559,10 +1559,10 @@ class LinearRegression(LinearModel, Regressor): Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Plots @@ -1661,7 +1661,7 @@ class LinearRegression(LinearModel, Regressor): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.to_python` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.to_python` method is used to retrieve predictions, probabilities, or cluster distances. For specific details on how to use this method for different model types, refer to the @@ -1776,7 +1776,7 @@ class PoissonRegressor(LinearModel, Regressor): based on their range. Subsequently, an activation function calculates the final score. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -1784,13 +1784,13 @@ class PoissonRegressor(LinearModel, Regressor): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_vertica_attributes`` method. Examples @@ -1805,7 +1805,7 @@ class PoissonRegressor(LinearModel, Regressor): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -1813,7 +1813,7 @@ class PoissonRegressor(LinearModel, Regressor): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1843,7 +1843,7 @@ class PoissonRegressor(LinearModel, Regressor): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -1857,7 +1857,7 @@ class PoissonRegressor(LinearModel, Regressor): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -1892,7 +1892,7 @@ class PoissonRegressor(LinearModel, Regressor): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -1939,9 +1939,9 @@ class PoissonRegressor(LinearModel, Regressor): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -2042,10 +2042,10 @@ class PoissonRegressor(LinearModel, Regressor): Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Plots @@ -2129,7 +2129,7 @@ class PoissonRegressor(LinearModel, Regressor): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.to_python` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.to_python` method is used to retrieve predictions, probabilities, or cluster distances. For specific details on how to use this method for different model types, refer to the relevant @@ -2238,7 +2238,7 @@ class Ridge(LinearModel, Regressor): based on their range. Subsequently, an activation function calculates the final score. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -2246,13 +2246,13 @@ class Ridge(LinearModel, Regressor): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_vertica_attributes`` method. Examples @@ -2267,7 +2267,7 @@ class Ridge(LinearModel, Regressor): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -2275,7 +2275,7 @@ class Ridge(LinearModel, Regressor): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -2305,7 +2305,7 @@ class Ridge(LinearModel, Regressor): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -2319,7 +2319,7 @@ class Ridge(LinearModel, Regressor): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -2353,7 +2353,7 @@ class Ridge(LinearModel, Regressor): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -2398,9 +2398,9 @@ class Ridge(LinearModel, Regressor): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -2526,10 +2526,10 @@ class Ridge(LinearModel, Regressor): Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Plots @@ -2628,7 +2628,7 @@ class Ridge(LinearModel, Regressor): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.to_python` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.to_python` method is used to retrieve predictions, probabilities, or cluster distances. For specific details on how to use this method for different model types, refer to the relevant @@ -2752,7 +2752,7 @@ class LogisticRegression(LinearModelClassifier, BinaryClassifier): based on their range. Subsequently, an activation function calculates the final score. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -2762,13 +2762,13 @@ class LogisticRegression(LinearModelClassifier, BinaryClassifier): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_vertica_attributes`` method. Examples @@ -2783,7 +2783,7 @@ class LogisticRegression(LinearModelClassifier, BinaryClassifier): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -2791,7 +2791,7 @@ class LogisticRegression(LinearModelClassifier, BinaryClassifier): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -2821,7 +2821,7 @@ class LogisticRegression(LinearModelClassifier, BinaryClassifier): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -2835,7 +2835,7 @@ class LogisticRegression(LinearModelClassifier, BinaryClassifier): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -2852,7 +2852,7 @@ class LogisticRegression(LinearModelClassifier, BinaryClassifier): In VerticaPy, balancing a dataset to address class imbalances is made straightforward through the - :py:mod:`verticapy.machine_learning.vertica.preprocessing.balance` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.balance` function within the ``preprocessing`` module. This function enables users to rectify skewed class distributions efficiently. By specifying the target variable and setting parameters like @@ -2860,7 +2860,7 @@ class LogisticRegression(LinearModelClassifier, BinaryClassifier): equitable representation of classes in their dataset. Whether opting for over-sampling, under-sampling, or a combination of both, VerticaPy's - :py:mod:`verticapy.machine_learning.vertica.preprocessing.balance` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.balance` function streamlines the process, empowering users to enhance the performance and fairness of their machine learning models trained on imbalanced data. @@ -2922,7 +2922,7 @@ class distributions. By addressing disparities in the number of .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -2967,9 +2967,9 @@ class distributions. By addressing disparities in the number of .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -3097,10 +3097,10 @@ class distributions. By addressing disparities in the number of Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Probabilities @@ -3311,7 +3311,7 @@ class distributions. By addressing disparities in the number of .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.to_python` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.to_python` method is used to retrieve predictions, probabilities, or cluster distances. For specific details on how to use this method for different model types, refer to the relevant diff --git a/verticapy/machine_learning/vertica/model_management.py b/verticapy/machine_learning/vertica/model_management.py index e7c393782..79d72a341 100755 --- a/verticapy/machine_learning/vertica/model_management.py +++ b/verticapy/machine_learning/vertica/model_management.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/vertica/naive_bayes.py b/verticapy/machine_learning/vertica/naive_bayes.py index ba043c574..cb3297142 100755 --- a/verticapy/machine_learning/vertica/naive_bayes.py +++ b/verticapy/machine_learning/vertica/naive_bayes.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -103,13 +103,13 @@ class NaiveBayes(MulticlassClassifier): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.base.MulticlassClassifier.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.MulticlassClassifier.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.base.MulticlassClassifier.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.MulticlassClassifier.get_vertica_attributes`` method. Examples @@ -124,7 +124,7 @@ class NaiveBayes(MulticlassClassifier): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -132,7 +132,7 @@ class NaiveBayes(MulticlassClassifier): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -162,7 +162,7 @@ class NaiveBayes(MulticlassClassifier): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -176,7 +176,7 @@ class NaiveBayes(MulticlassClassifier): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -193,7 +193,7 @@ class NaiveBayes(MulticlassClassifier): In VerticaPy, balancing a dataset to address class imbalances is made straightforward through the - :py:mod:`verticapy.machine_learning.vertica.preprocessing.balance` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.balance` function within the ``preprocessing`` module. This function enables users to rectify skewed class distributions efficiently. By specifying the target variable and setting parameters like @@ -201,7 +201,7 @@ class NaiveBayes(MulticlassClassifier): equitable representation of classes in their dataset. Whether opting for over-sampling, under-sampling, or a combination of both, VerticaPy's - :py:mod:`verticapy.machine_learning.vertica.preprocessing.balance` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.balance` function streamlines the process, empowering users to enhance the performance and fairness of their machine learning models trained on imbalanced data. @@ -258,7 +258,7 @@ class distributions. By addressing disparities in the number of .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -290,9 +290,9 @@ class distributions. By addressing disparities in the number of .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -351,7 +351,7 @@ class distributions. By addressing disparities in the number of .. note:: - For multi-class scoring, ``verticapy`` allows the + For multi-class scoring, :py:mod:`verticapy` allows the flexibility to use three averaging techniques: micro, macro and weighted. Please refer to `this link `_ @@ -399,10 +399,10 @@ class distributions. By addressing disparities in the number of Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.naive_bayes.NaiveBayes.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.naive_bayes.NaiveBayes.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Probabilities @@ -610,7 +610,7 @@ class distributions. By addressing disparities in the number of .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.naive_bayes.NaiveBayes.to_python` + :py:meth:`verticapy.machine_learning.vertica.naive_bayes.NaiveBayes.to_python` method is used to retrieve predictions, probabilities, or cluster distances. For specific details on how to use this method for different model types, refer to the relevant diff --git a/verticapy/machine_learning/vertica/neighbors.py b/verticapy/machine_learning/vertica/neighbors.py index 2d6b55a47..c0899f6e6 100755 --- a/verticapy/machine_learning/vertica/neighbors.py +++ b/verticapy/machine_learning/vertica/neighbors.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -111,7 +111,7 @@ class KNeighborsRegressor(Regressor): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.base.VerticaModel.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.VerticaModel.get_attributes`` method. Examples @@ -126,7 +126,7 @@ class KNeighborsRegressor(Regressor): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -134,7 +134,7 @@ class KNeighborsRegressor(Regressor): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -164,7 +164,7 @@ class KNeighborsRegressor(Regressor): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -177,7 +177,7 @@ class KNeighborsRegressor(Regressor): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -206,7 +206,7 @@ class KNeighborsRegressor(Regressor): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -240,9 +240,9 @@ class KNeighborsRegressor(Regressor): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -344,10 +344,10 @@ class KNeighborsRegressor(Regressor): Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Parameter Modification @@ -619,7 +619,7 @@ class KNeighborsClassifier(MulticlassClassifier): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.base.VerticaModel.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.VerticaModel.get_attributes`` method. Examples @@ -634,7 +634,7 @@ class KNeighborsClassifier(MulticlassClassifier): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -642,7 +642,7 @@ class KNeighborsClassifier(MulticlassClassifier): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -686,7 +686,7 @@ class KNeighborsClassifier(MulticlassClassifier): data = data.balance(column="quality", x = 1) You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -699,7 +699,7 @@ class KNeighborsClassifier(MulticlassClassifier): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -719,7 +719,7 @@ class KNeighborsClassifier(MulticlassClassifier): In VerticaPy, balancing a dataset to address class imbalances is made straightforward through the - :py:mod:`verticapy.machine_learning.vertica.preprocessing.balance` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.balance` function within the ``preprocessing`` module. This function enables users to rectify skewed class distributions efficiently. By specifying the target variable and setting parameters like @@ -727,7 +727,7 @@ class KNeighborsClassifier(MulticlassClassifier): equitable representation of classes in their dataset. Whether opting for over-sampling, under-sampling, or a combination of both, VerticaPy's - :py:mod:`verticapy.machine_learning.vertica.preprocessing.balance` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.balance` function streamlines the process, empowering users to enhance the performance and fairness of their machine learning models trained on imbalanced data. @@ -793,7 +793,7 @@ class distributions. By addressing disparities in the number of .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -820,9 +820,9 @@ class distributions. By addressing disparities in the number of .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -887,7 +887,7 @@ class distributions. By addressing disparities in the number of .. note:: - For multi-class scoring, ``verticapy`` allows the + For multi-class scoring, :py:mod:`verticapy` allows the flexibility to use three averaging techniques: micro, macro and weighted. Please refer to `this link `_ @@ -935,10 +935,10 @@ class distributions. By addressing disparities in the number of Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Probabilities @@ -1109,7 +1109,7 @@ class distributions. By addressing disparities in the number of It is not possible to export this type of model, but you can still examine the SQL code generated by using the - :py:mod:`verticapy.machine_learning.vertica.neighbors.KNeighborsClassifier.deploySQL` + :py:meth:`verticapy.machine_learning.vertica.neighbors.KNeighborsClassifier.deploySQL` method. """ @@ -1607,7 +1607,7 @@ class KernelDensity(Regressor, Tree): ---------- Several attributes are computed during the fitting phase, and in the case of kernel density estimation (KDE), a - :py:mod:`verticapy.machine_learning.vertica.ensemble.RandomForestRegressor`` + :py:meth:`verticapy.machine_learning.vertica.ensemble.RandomForestRegressor`` is employed to approximate the k-nearest neighbors (KNN) computation. This reliance on RandomForestRegressor enhances the efficiency and accuracy of the KDE algorithm. @@ -2054,7 +2054,7 @@ class LocalOutlierFactor(VerticaModel): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.base.VerticaModel.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.VerticaModel.get_attributes`` method. Examples @@ -2069,7 +2069,7 @@ class LocalOutlierFactor(VerticaModel): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -2077,7 +2077,7 @@ class LocalOutlierFactor(VerticaModel): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -2154,9 +2154,9 @@ class LocalOutlierFactor(VerticaModel): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. diff --git a/verticapy/machine_learning/vertica/pipeline.py b/verticapy/machine_learning/vertica/pipeline.py index e88be286d..3bb800354 100755 --- a/verticapy/machine_learning/vertica/pipeline.py +++ b/verticapy/machine_learning/vertica/pipeline.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/vertica/pmml/__init__.py b/verticapy/machine_learning/vertica/pmml/__init__.py index 16d700566..49b96f7c9 100755 --- a/verticapy/machine_learning/vertica/pmml/__init__.py +++ b/verticapy/machine_learning/vertica/pmml/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/vertica/pmml/base.py b/verticapy/machine_learning/vertica/pmml/base.py index 79bf131e0..2279d8b52 100644 --- a/verticapy/machine_learning/vertica/pmml/base.py +++ b/verticapy/machine_learning/vertica/pmml/base.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -38,19 +38,19 @@ class PMMLModel(VerticaModel): name: str, optional Name of the model. The model must be stored in the database. If it is not the case, you can use - :py:mod:`verticapy.machine_learning.vertica.import_models` + :py:meth:`verticapy.machine_learning.vertica.import_models` to import your PMML model. Attributes ---------- All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.base.VerticaModel.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.VerticaModel.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.base.VerticaModel.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.VerticaModel.get_vertica_attributes`` method. """ diff --git a/verticapy/machine_learning/vertica/preprocessing.py b/verticapy/machine_learning/vertica/preprocessing.py index 3af732679..7d91a89fe 100755 --- a/verticapy/machine_learning/vertica/preprocessing.py +++ b/verticapy/machine_learning/vertica/preprocessing.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -112,7 +112,7 @@ def balance( Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -120,7 +120,7 @@ def balance( .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -195,8 +195,7 @@ def balance( :file: SPHINX_DIRECTORY/figures/machine_learning_vertica_preprocessing_balance.html .. seealso:: - | :py:mod:`verticapy.vDataFrame.sample` : - Sampling the dataset. + | :py:meth:`verticapy.vDataFrame.sample` : Sampling the dataset. """ _executeSQL( query=f""" @@ -551,7 +550,7 @@ class CountVectorizer(VerticaModel): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.preprocessing.Preprocessing.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.Preprocessing.get_attributes`` method. """ @@ -835,13 +834,13 @@ class Scaler(Preprocessing): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.preprocessing.Preprocessing.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.Preprocessing.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.preprocessing.Preprocessing.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.Preprocessing.get_vertica_attributes`` method. Examples @@ -856,7 +855,7 @@ class Scaler(Preprocessing): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -864,7 +863,7 @@ class Scaler(Preprocessing): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -906,7 +905,7 @@ class Scaler(Preprocessing): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -929,7 +928,7 @@ class Scaler(Preprocessing): .. important:: - To fit a model, you can directly use the ``vDataFrame`` + To fit a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. Model Parameters @@ -959,8 +958,8 @@ class Scaler(Preprocessing): model.transform(data) Please refer to - :py:mod:`verticapy.machine_learning.Scaler.transform` - for more details on transforming a ``vDataFrame``. + :py:meth:`verticapy.machine_learning.Scaler.transform` + for more details on transforming a :py:class:`vDataFrame`. Similarly, you can perform the inverse tranform to get the original features using: @@ -1024,17 +1023,17 @@ class Scaler(Preprocessing): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.preprocessing.Scaler.to_python` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.Scaler.to_python` method is used to scale the data. For specific details on how to use this method for different model types, refer to the relevant documentation for each model. .. seealso:: - | :py:mod:`verticapy.machine_learning.vertica.preprocessing.StandardScaler` : + | :py:meth:`verticapy.machine_learning.vertica.preprocessing.StandardScaler` : Scalar with method set as ``zscore``. - | :py:mod:`verticapy.machine_learning.vertica.preprocessing.RobustScaler` : + | :py:meth:`verticapy.machine_learning.vertica.preprocessing.RobustScaler` : Scalar with method set as ``robust_zscore``. - | :py:mod:`verticapy.machine_learning.vertica.preprocessing.MinMaxScaler` : + | :py:meth:`verticapy.machine_learning.vertica.preprocessing.MinMaxScaler` : Scalar with method set as ``minmax``. """ @@ -1122,7 +1121,7 @@ class StandardScaler(Scaler): .. note:: This is a child class. See - :py:mod:`verticapy.machine_learning.vertica.preprocessing.Scaler` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.Scaler` for more details and examples. """ @@ -1141,7 +1140,7 @@ class RobustScaler(Scaler): .. note:: This is a child class. See - :py:mod:`verticapy.machine_learning.vertica.preprocessing.Scaler` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.Scaler` for more details and examples. """ @@ -1160,7 +1159,7 @@ class MinMaxScaler(Scaler): .. note:: This is a child class. See - :py:mod:`verticapy.machine_learning.vertica.preprocessing.Scaler` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.Scaler` for more details and examples. """ @@ -1243,13 +1242,13 @@ class OneHotEncoder(Preprocessing): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.preprocessing.Preprocessing.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.Preprocessing.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.preprocessing.Preprocessing.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.Preprocessing.get_vertica_attributes`` method. Examples @@ -1264,7 +1263,7 @@ class OneHotEncoder(Preprocessing): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1272,7 +1271,7 @@ class OneHotEncoder(Preprocessing): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -1328,7 +1327,7 @@ class OneHotEncoder(Preprocessing): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -1351,7 +1350,7 @@ class OneHotEncoder(Preprocessing): .. important:: - To train a model, you can directly use the ``vDataFrame`` + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. Classes @@ -1377,8 +1376,8 @@ class OneHotEncoder(Preprocessing): model.transform(data)[:20] Please refer to - :py:mod:`verticapy.machine_learning.OneHotEncoder.transform` - for more details on transforming a ``vDataFrame``. + :py:meth:`verticapy.machine_learning.OneHotEncoder.transform` + for more details on transforming a :py:class:`vDataFrame`. Similarly, you can perform the inverse tranform to get the original features using: @@ -1443,7 +1442,7 @@ class OneHotEncoder(Preprocessing): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.preprocessing.OneHotEncoder.to_python` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.OneHotEncoder.to_python` method is used to transform the data and compute the different categories. For specific details on how to use this method for different model types, refer to the relevant documentation for diff --git a/verticapy/machine_learning/vertica/svm.py b/verticapy/machine_learning/vertica/svm.py index f044c437e..76b4433ab 100755 --- a/verticapy/machine_learning/vertica/svm.py +++ b/verticapy/machine_learning/vertica/svm.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -100,7 +100,7 @@ class LinearSVR(LinearModel, Regressor): based on their range. Subsequently, an activation function calculates the final score. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -108,13 +108,13 @@ class LinearSVR(LinearModel, Regressor): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_vertica_attributes`` method. Examples @@ -129,7 +129,7 @@ class LinearSVR(LinearModel, Regressor): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -137,7 +137,7 @@ class LinearSVR(LinearModel, Regressor): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -167,7 +167,7 @@ class LinearSVR(LinearModel, Regressor): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -181,7 +181,7 @@ class LinearSVR(LinearModel, Regressor): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -217,7 +217,7 @@ class LinearSVR(LinearModel, Regressor): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -264,9 +264,9 @@ class LinearSVR(LinearModel, Regressor): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -392,10 +392,10 @@ class LinearSVR(LinearModel, Regressor): Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Plots @@ -494,7 +494,7 @@ class LinearSVR(LinearModel, Regressor): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.to_python` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.to_python` method is used to retrieve predictions, probabilities, or cluster distances. For specific details on how to use this method for different model types, refer to the relevant @@ -636,7 +636,7 @@ class LinearSVC(LinearModelClassifier, BinaryClassifier): based on their range. Subsequently, an activation function calculates the final score. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -646,13 +646,13 @@ class LinearSVC(LinearModelClassifier, BinaryClassifier): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.get_vertica_attributes`` method. Examples @@ -667,7 +667,7 @@ class LinearSVC(LinearModelClassifier, BinaryClassifier): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -675,7 +675,7 @@ class LinearSVC(LinearModelClassifier, BinaryClassifier): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -705,7 +705,7 @@ class LinearSVC(LinearModelClassifier, BinaryClassifier): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -719,7 +719,7 @@ class LinearSVC(LinearModelClassifier, BinaryClassifier): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -760,7 +760,7 @@ class LinearSVC(LinearModelClassifier, BinaryClassifier): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -796,9 +796,9 @@ class LinearSVC(LinearModelClassifier, BinaryClassifier): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -926,10 +926,10 @@ class LinearSVC(LinearModelClassifier, BinaryClassifier): Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Probabilities @@ -1140,7 +1140,7 @@ class LinearSVC(LinearModelClassifier, BinaryClassifier): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.to_python` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.to_python` method is used to retrieve predictions, probabilities, or cluster distances. For specific details on how to use this method for different model types, refer to the relevant diff --git a/verticapy/machine_learning/vertica/tensorflow/__init__.py b/verticapy/machine_learning/vertica/tensorflow/__init__.py index 3364f609a..77a22cd8c 100755 --- a/verticapy/machine_learning/vertica/tensorflow/__init__.py +++ b/verticapy/machine_learning/vertica/tensorflow/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/machine_learning/vertica/tensorflow/base.py b/verticapy/machine_learning/vertica/tensorflow/base.py index 8bfc44488..bcc2aebe1 100644 --- a/verticapy/machine_learning/vertica/tensorflow/base.py +++ b/verticapy/machine_learning/vertica/tensorflow/base.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -38,19 +38,19 @@ class TensorFlowModel(VerticaModel): name: str, optional Name of the model. The model must be stored in the database. If it is not the case, you can use - :py:mod:`verticapy.machine_learning.vertica.import_models` + :py:meth:`verticapy.machine_learning.vertica.import_models` to import your TensorFlow model. Attributes ---------- All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.base.VerticaModel.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.VerticaModel.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.base.VerticaModel.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.VerticaModel.get_vertica_attributes`` method. """ diff --git a/verticapy/machine_learning/vertica/tree.py b/verticapy/machine_learning/vertica/tree.py index 4c0197ef4..4f686d70b 100755 --- a/verticapy/machine_learning/vertica/tree.py +++ b/verticapy/machine_learning/vertica/tree.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -82,7 +82,7 @@ class DecisionTreeRegressor(RandomForestRegressor): ``BinaryTreeRegressor``. It possess various attributes. For more detailed information, refer to the documentation for - :py:mod:`verticapy.machine_learning.memmodel.tree.BinaryTreeRegressor`. + :py:meth:`verticapy.machine_learning.memmodel.tree.BinaryTreeRegressor`. features_importance_: numpy.array The importance of features. It is calculated using the MDI (Mean Decreased Impurity). To @@ -90,7 +90,7 @@ class DecisionTreeRegressor(RandomForestRegressor): scores of each tree, normalizes them and applies an activation function to scale them. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.features_importance` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -98,13 +98,13 @@ class DecisionTreeRegressor(RandomForestRegressor): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.get_vertica_attributes`` method. Examples @@ -125,7 +125,7 @@ class DecisionTreeRegressor(RandomForestRegressor): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -133,7 +133,7 @@ class DecisionTreeRegressor(RandomForestRegressor): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -163,7 +163,7 @@ class DecisionTreeRegressor(RandomForestRegressor): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -177,7 +177,7 @@ class DecisionTreeRegressor(RandomForestRegressor): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -214,7 +214,7 @@ class DecisionTreeRegressor(RandomForestRegressor): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -250,9 +250,9 @@ class DecisionTreeRegressor(RandomForestRegressor): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -310,7 +310,7 @@ class DecisionTreeRegressor(RandomForestRegressor): E.g. ``model.report(metrics = ["mse", "r2"])``. You can utilize the - :py:mod:`verticapy.machine_learning.vertica.ensemble.RandomForestRegressor.score` + :py:meth:`verticapy.machine_learning.vertica.ensemble.RandomForestRegressor.score` function to calculate various regression metrics, with the R-squared being the default. .. ipython:: python @@ -363,10 +363,10 @@ class DecisionTreeRegressor(RandomForestRegressor): Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.ensemble.RandomForestRegressor.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.ensemble.RandomForestRegressor.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Plots @@ -469,7 +469,7 @@ class DecisionTreeRegressor(RandomForestRegressor): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.tree.DecisionTreeRegressor.to_python` + :py:meth:`verticapy.machine_learning.vertica.tree.DecisionTreeRegressor.to_python` method is used to retrieve predictions, probabilities, or cluster distances. For specific details on how to use this method for different model types, refer to the relevant @@ -529,7 +529,7 @@ class DummyTreeRegressor(RandomForestRegressor): ``BinaryTreeRegressor``. It possess various attributes. For more detailed information, refer to the documentation for - :py:mod:`verticapy.machine_learning.memmodel.tree.BinaryTreeRegressor`. + :py:meth:`verticapy.machine_learning.memmodel.tree.BinaryTreeRegressor`. features_importance_: numpy.array The importance of features. It is calculated using the MDI (Mean Decreased Impurity). To @@ -537,7 +537,7 @@ class DummyTreeRegressor(RandomForestRegressor): scores of each tree, normalizes them and applies an activation function to scale them. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.features_importance` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -545,13 +545,13 @@ class DummyTreeRegressor(RandomForestRegressor): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.get_vertica_attributes`` method. Examples @@ -572,7 +572,7 @@ class DummyTreeRegressor(RandomForestRegressor): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -580,7 +580,7 @@ class DummyTreeRegressor(RandomForestRegressor): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -610,7 +610,7 @@ class DummyTreeRegressor(RandomForestRegressor): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -624,7 +624,7 @@ class DummyTreeRegressor(RandomForestRegressor): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -653,7 +653,7 @@ class DummyTreeRegressor(RandomForestRegressor): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -688,9 +688,9 @@ class DummyTreeRegressor(RandomForestRegressor): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -748,7 +748,7 @@ class DummyTreeRegressor(RandomForestRegressor): E.g. ``model.report(metrics = ["mse", "r2"])``. You can utilize the - :py:mod:`verticapy.machine_learning.vertica.ensemble.RandomForestRegressor.score` + :py:meth:`verticapy.machine_learning.vertica.ensemble.RandomForestRegressor.score` function to calculate various regression metrics, with the R-squared being the default. .. ipython:: python @@ -801,10 +801,10 @@ class DummyTreeRegressor(RandomForestRegressor): Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.ensemble.RandomForestRegressor.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.ensemble.RandomForestRegressor.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Plots @@ -907,7 +907,7 @@ class DummyTreeRegressor(RandomForestRegressor): .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.tree.DummyTreeRegressor.to_python` + :py:meth:`verticapy.machine_learning.vertica.tree.DummyTreeRegressor.to_python` method is used to retrieve predictions, probabilities, or cluster distances. For specific details on how to use this method for different model types, refer to the relevant @@ -989,7 +989,7 @@ class DecisionTreeClassifier(RandomForestClassifier): ``BinaryTreeClassifier``. It possess various attributes. For more detailed information, refer to the documentation for - :py:mod:`verticapy.machine_learning.memmodel.tree.BinaryTreeClassifier`. + :py:meth:`verticapy.machine_learning.memmodel.tree.BinaryTreeClassifier`. features_importance_: numpy.array The importance of features. It is calculated using the MDI (Mean Decreased Impurity). To @@ -997,7 +997,7 @@ class DecisionTreeClassifier(RandomForestClassifier): scores of each tree, normalizes them and applies an activation function to scale them. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.features_importance` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -1007,13 +1007,13 @@ class DecisionTreeClassifier(RandomForestClassifier): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.get_vertica_attributes`` method. Examples @@ -1034,7 +1034,7 @@ class DecisionTreeClassifier(RandomForestClassifier): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -1042,7 +1042,7 @@ class DecisionTreeClassifier(RandomForestClassifier): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -1072,7 +1072,7 @@ class DecisionTreeClassifier(RandomForestClassifier): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -1086,7 +1086,7 @@ class DecisionTreeClassifier(RandomForestClassifier): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -1103,7 +1103,7 @@ class DecisionTreeClassifier(RandomForestClassifier): In VerticaPy, balancing a dataset to address class imbalances is made straightforward through the - :py:mod:`verticapy.machine_learning.vertica.preprocessing.balance` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.balance` function within the ``preprocessing`` module. This function enables users to rectify skewed class distributions efficiently. By specifying the target variable and setting parameters like @@ -1111,7 +1111,7 @@ class DecisionTreeClassifier(RandomForestClassifier): equitable representation of classes in their dataset. Whether opting for over-sampling, under-sampling, or a combination of both, VerticaPy's - :py:mod:`verticapy.machine_learning.vertica.preprocessing.balance` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.balance` function streamlines the process, empowering users to enhance the performance and fairness of their machine learning models trained on imbalanced data. @@ -1181,7 +1181,7 @@ class distributions. By addressing disparities in the number of .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -1216,9 +1216,9 @@ class distributions. By addressing disparities in the number of .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -1295,7 +1295,7 @@ class distributions. By addressing disparities in the number of You can also use the - :py:mod:`verticapy.machine_learning.vertica.ensemble.RandomForestClassifier.score` + :py:meth:`verticapy.machine_learning.vertica.ensemble.RandomForestClassifier.score` function to compute any classification metric. The default metric is the accuracy: .. ipython:: python @@ -1348,10 +1348,10 @@ class distributions. By addressing disparities in the number of Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.ensemble.RandomForestClassifier.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.ensemble.RandomForestClassifier.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Probabilities @@ -1580,7 +1580,7 @@ class distributions. By addressing disparities in the number of .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.tree.DecisionTreeClassifier.to_python` + :py:meth:`verticapy.machine_learning.vertica.tree.DecisionTreeClassifier.to_python` method is used to retrieve predictions, probabilities, or cluster distances. For specific details on how to use this method for different model types, refer to the relevant @@ -1640,7 +1640,7 @@ class DummyTreeClassifier(RandomForestClassifier): ``BinaryTreeClassifier``. It possess various attributes. For more detailed information, refer to the documentation for - :py:mod:`verticapy.machine_learning.memmodel.tree.BinaryTreeClassifier`. + :py:meth:`verticapy.machine_learning.memmodel.tree.BinaryTreeClassifier`. features_importance_: numpy.array The importance of features. It is calculated using the MDI (Mean Decreased Impurity). To @@ -1648,7 +1648,7 @@ class DummyTreeClassifier(RandomForestClassifier): scores of each tree, normalizes them and applies an activation function to scale them. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.features_importance` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -1658,13 +1658,13 @@ class DummyTreeClassifier(RandomForestClassifier): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.base.Tree.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.base.Tree.get_vertica_attributes`` method. Examples @@ -1685,7 +1685,7 @@ class DummyTreeClassifier(RandomForestClassifier): Load data for machine learning ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. code-block:: python @@ -1693,7 +1693,7 @@ class DummyTreeClassifier(RandomForestClassifier): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk of code + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming conflicts. @@ -1723,7 +1723,7 @@ class DummyTreeClassifier(RandomForestClassifier): skills within the VerticaPy environment. You can easily divide your dataset into training and testing subsets - using the :py:mod:`vDataFrame.train_test_split` method. This is a + using the :py:meth:`vDataFrame.train_test_split` method. This is a crucial step when preparing your data for machine learning, as it allows you to evaluate the performance of your models accurately. @@ -1737,7 +1737,7 @@ class DummyTreeClassifier(RandomForestClassifier): In this case, VerticaPy utilizes seeded randomization to guarantee the reproducibility of your data split. However, please be aware that this approach may lead to reduced performance. For a more - efficient data split, you can use the :py:mod:`vDataFrame.to_db` + efficient data split, you can use the :py:meth:`vDataFrame.to_db` method to save your results into ``tables`` or ``temporary tables``. This will help enhance the overall performance of the process. @@ -1754,7 +1754,7 @@ class DummyTreeClassifier(RandomForestClassifier): In VerticaPy, balancing a dataset to address class imbalances is made straightforward through the - :py:mod:`verticapy.machine_learning.vertica.preprocessing.balance` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.balance` function within the ``preprocessing`` module. This function enables users to rectify skewed class distributions efficiently. By specifying the target variable and setting parameters like @@ -1762,7 +1762,7 @@ class DummyTreeClassifier(RandomForestClassifier): equitable representation of classes in their dataset. Whether opting for over-sampling, under-sampling, or a combination of both, VerticaPy's - :py:mod:`verticapy.machine_learning.vertica.preprocessing.balance` + :py:meth:`verticapy.machine_learning.vertica.preprocessing.balance` function streamlines the process, empowering users to enhance the performance and fairness of their machine learning models trained on imbalanced data. @@ -1826,7 +1826,7 @@ class distributions. By addressing disparities in the number of .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -1861,9 +1861,9 @@ class distributions. By addressing disparities in the number of .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -1940,7 +1940,7 @@ class distributions. By addressing disparities in the number of You can also use the - :py:mod:`verticapy.machine_learning.vertica.ensemble.RandomForestClassifier.score` + :py:meth:`verticapy.machine_learning.vertica.ensemble.RandomForestClassifier.score` function to compute any classification metric. The default metric is the accuracy: .. ipython:: python @@ -1993,10 +1993,10 @@ class distributions. By addressing disparities in the number of Predictions can be made automatically using the test set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.ensemble.RandomForestClassifier.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.ensemble.RandomForestClassifier.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. Probabilities @@ -2210,7 +2210,7 @@ class distributions. By addressing disparities in the number of .. hint:: The - :py:mod:`verticapy.machine_learning.vertica.tree.DummyTreeClassifier.to_python` + :py:meth:`verticapy.machine_learning.vertica.tree.DummyTreeClassifier.to_python` method is used to retrieve predictions, probabilities, or cluster distances. For specific details on how to use this method for different model types, refer to the relevant diff --git a/verticapy/machine_learning/vertica/tsa.py b/verticapy/machine_learning/vertica/tsa.py index 4d08c32c3..201975928 100755 --- a/verticapy/machine_learning/vertica/tsa.py +++ b/verticapy/machine_learning/vertica/tsa.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -1103,7 +1103,7 @@ class ARIMA(TimeSeriesModelBase): are normalized based on their range. Subsequently, an activation function calculates the final score. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -1119,13 +1119,13 @@ class ARIMA(TimeSeriesModelBase): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.tsa.TimeSeriesModelBase.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.tsa.TimeSeriesModelBase.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.tsa.TimeSeriesModelBase.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.tsa.TimeSeriesModelBase.get_vertica_attributes`` method. Examples @@ -1140,7 +1140,7 @@ class ARIMA(TimeSeriesModelBase): Initialization ^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1148,7 +1148,7 @@ class ARIMA(TimeSeriesModelBase): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1202,7 +1202,7 @@ class ARIMA(TimeSeriesModelBase): Though the increasing trend is obvious in our example, we can confirm it by the - :py:mod:`verticapy.machine_learning.model_selection.statistical_tests.mkt` + :py:meth:`verticapy.machine_learning.model_selection.statistical_tests.mkt` (Mann Kendall test) test: .. code-block:: python @@ -1247,7 +1247,7 @@ class ARIMA(TimeSeriesModelBase): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -1270,9 +1270,9 @@ class ARIMA(TimeSeriesModelBase): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -1402,7 +1402,7 @@ class ARIMA(TimeSeriesModelBase): E.g. ``model.report(metrics = ["mse", "r2"])``. You can utilize the - :py:mod:`verticapy.machine_learning.vertica.tsa.ARIMA.score` + :py:meth:`verticapy.machine_learning.vertica.tsa.ARIMA.score` function to calculate various regression metrics, with the explained variance being the default. @@ -1458,10 +1458,10 @@ class ARIMA(TimeSeriesModelBase): Predictions can be made automatically by using the training set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.tsa.ARIMA.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.tsa.ARIMA.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. If you would like to have the 'time-stamps' (ts) in the output then @@ -1594,7 +1594,7 @@ class ARIMA(TimeSeriesModelBase): You can utilize the - :py:mod:`verticapy.machine_learning.vertica.tsa.ARIMA.score` + :py:meth:`verticapy.machine_learning.vertica.tsa.ARIMA.score` function to calculate various regression metrics, with the explained variance being the default. @@ -1815,7 +1815,7 @@ class ARMA(TimeSeriesModelBase): are normalized based on their range. Subsequently, an activation function calculates the final score. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -1831,13 +1831,13 @@ class ARMA(TimeSeriesModelBase): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.tsa.TimeSeriesModelBase.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.tsa.TimeSeriesModelBase.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.tsa.TimeSeriesModelBase.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.tsa.TimeSeriesModelBase.get_vertica_attributes`` method. Examples @@ -1852,7 +1852,7 @@ class ARMA(TimeSeriesModelBase): Initialization ^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -1860,7 +1860,7 @@ class ARMA(TimeSeriesModelBase): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -1914,7 +1914,7 @@ class ARMA(TimeSeriesModelBase): Though the increasing trend is obvious in our example, we can confirm it by the - :py:mod:`verticapy.machine_learning.model_selection.statistical_tests.mkt` + :py:meth:`verticapy.machine_learning.model_selection.statistical_tests.mkt` (Mann Kendall test) test: .. code-block:: python @@ -1959,7 +1959,7 @@ class ARMA(TimeSeriesModelBase): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -1982,9 +1982,9 @@ class ARMA(TimeSeriesModelBase): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -2105,7 +2105,7 @@ class ARMA(TimeSeriesModelBase): E.g. ``model.report(metrics = ["mse", "r2"])``. You can utilize the - :py:mod:`verticapy.machine_learning.vertica.tsa.ARMA.score` + :py:meth:`verticapy.machine_learning.vertica.tsa.ARMA.score` function to calculate various regression metrics, with the explained variance being the default. @@ -2161,10 +2161,10 @@ class ARMA(TimeSeriesModelBase): Predictions can be made automatically by using the training set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.tsa.ARMA.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.tsa.ARMA.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. If you would like to have the 'time-stamps' (ts) in the output then @@ -2296,7 +2296,7 @@ class ARMA(TimeSeriesModelBase): You can utilize the - :py:mod:`verticapy.machine_learning.vertica.tsa.ARIMA.score` + :py:meth:`verticapy.machine_learning.vertica.tsa.ARIMA.score` function to calculate various regression metrics, with the explained variance being the default. @@ -2514,7 +2514,7 @@ class AR(TimeSeriesModelBase): are normalized based on their range. Subsequently, an activation function calculates the final score. It is necessary to use the - :py:mod:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` + :py:meth:`verticapy.machine_learning.vertica.linear_model.LinearModel.features_importance` method to compute it initially, and the computed values will be subsequently utilized for subsequent calls. @@ -2530,13 +2530,13 @@ class AR(TimeSeriesModelBase): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.tsa.TimeSeriesModelBase.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.tsa.TimeSeriesModelBase.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.tsa.TimeSeriesModelBase.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.tsa.TimeSeriesModelBase.get_vertica_attributes`` method. Examples @@ -2551,7 +2551,7 @@ class AR(TimeSeriesModelBase): Initialization ^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -2559,7 +2559,7 @@ class AR(TimeSeriesModelBase): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -2618,7 +2618,7 @@ class AR(TimeSeriesModelBase): Though the increasing trend is obvious in our example, we can confirm it by the - :py:mod:`verticapy.machine_learning.model_selection.statistical_tests.mkt` + :py:meth:`verticapy.machine_learning.model_selection.statistical_tests.mkt` (Mann Kendall test) test: .. code-block:: python @@ -2663,7 +2663,7 @@ class AR(TimeSeriesModelBase): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -2686,9 +2686,9 @@ class AR(TimeSeriesModelBase): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -2805,7 +2805,7 @@ class AR(TimeSeriesModelBase): E.g. ``model.report(metrics = ["mse", "r2"])``. You can utilize the - :py:mod:`verticapy.machine_learning.vertica.tsa.AR.score` + :py:meth:`verticapy.machine_learning.vertica.tsa.AR.score` function to calculate various regression metrics, with the explained variance being the default. @@ -2853,10 +2853,10 @@ class AR(TimeSeriesModelBase): Predictions can be made automatically by using the training set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.tsa.AR.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.tsa.AR.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. If you would like to have the 'time-stamps' (ts) in the output then @@ -2984,7 +2984,7 @@ class AR(TimeSeriesModelBase): You can utilize the - :py:mod:`verticapy.machine_learning.vertica.tsa.ARIMA.score` + :py:meth:`verticapy.machine_learning.vertica.tsa.ARIMA.score` function to calculate various regression metrics, with the explained variance being the default. @@ -3192,13 +3192,13 @@ class MA(TimeSeriesModelBase): .. note:: All attributes can be accessed using the - :py:mod:`verticapy.machine_learning.vertica.tsa.TimeSeriesModelBase.get_attributes`` + :py:meth:`verticapy.machine_learning.vertica.tsa.TimeSeriesModelBase.get_attributes`` method. .. note:: Several other attributes can be accessed by using the - :py:mod:`verticapy.machine_learning.vertica.tsa.TimeSeriesModelBase.get_vertica_attributes`` + :py:meth:`verticapy.machine_learning.vertica.tsa.TimeSeriesModelBase.get_vertica_attributes`` method. Examples @@ -3213,7 +3213,7 @@ class MA(TimeSeriesModelBase): Initialization ^^^^^^^^^^^^^^^ - We import ``verticapy``: + We import :py:mod:`verticapy`: .. ipython:: python @@ -3221,7 +3221,7 @@ class MA(TimeSeriesModelBase): .. hint:: - By assigning an alias to ``verticapy``, we mitigate the risk + By assigning an alias to :py:mod:`verticapy`, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like "average" and "median", which can potentially lead to naming @@ -3297,7 +3297,7 @@ class MA(TimeSeriesModelBase): It is obvious there is no trend in our example, but we can confirm it by the - :py:mod:`verticapy.machine_learning.model_selection.statistical_tests.mkt` + :py:meth:`verticapy.machine_learning.model_selection.statistical_tests.mkt` (Mann Kendall test) test: .. code-block:: python @@ -3343,7 +3343,7 @@ class MA(TimeSeriesModelBase): .. hint:: - In ``verticapy`` 1.0.x and higher, you do not need to specify the + In :py:mod:`verticapy` 1.0.x and higher, you do not need to specify the model name, as the name is automatically assigned. If you need to re-use the model, you can fetch the model name from the model's attributes. @@ -3366,9 +3366,9 @@ class MA(TimeSeriesModelBase): .. important:: - To train a model, you can directly use the ``vDataFrame`` or the + To train a model, you can directly use the :py:class:`vDataFrame` or the name of the relation stored in the database. The test set is optional - and is only used to compute the test metrics. In ``verticapy``, we + and is only used to compute the test metrics. In :py:mod:`verticapy`, we don't work using ``X`` matrices and ``y`` vectors. Instead, we work directly with lists of predictors and the response name. @@ -3465,7 +3465,7 @@ class MA(TimeSeriesModelBase): E.g. ``model.report(metrics = ["mse", "r2"])``. You can utilize the - :py:mod:`verticapy.machine_learning.vertica.tsa.MA.score` + :py:meth:`verticapy.machine_learning.vertica.tsa.MA.score` function to calculate various regression metrics, with the explained variance being the default. @@ -3513,10 +3513,10 @@ class MA(TimeSeriesModelBase): Predictions can be made automatically by using the training set, in which case you don't need to specify the predictors. Alternatively, you - can pass only the ``vDataFrame`` to the - :py:mod:`verticapy.machine_learning.vertica.tsa.MA.predict` + can pass only the :py:class:`vDataFrame` to the + :py:meth:`verticapy.machine_learning.vertica.tsa.MA.predict` function, but in this case, it's essential that the column names of - the ``vDataFrame`` match the predictors and response name in the + the :py:class:`vDataFrame` match the predictors and response name in the model. If you would like to have the 'time-stamps' (ts) in the output then @@ -3657,7 +3657,7 @@ class MA(TimeSeriesModelBase): You can utilize the - :py:mod:`verticapy.machine_learning.vertica.tsa.ARIMA.score` + :py:meth:`verticapy.machine_learning.vertica.tsa.ARIMA.score` function to calculate various regression metrics, with the explained variance being the default. diff --git a/verticapy/mlops/__init__.py b/verticapy/mlops/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/mlops/__init__.py +++ b/verticapy/mlops/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/mlops/model_tracking/__init__.py b/verticapy/mlops/model_tracking/__init__.py index f4a10d140..a797bea93 100755 --- a/verticapy/mlops/model_tracking/__init__.py +++ b/verticapy/mlops/model_tracking/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/mlops/model_tracking/base.py b/verticapy/mlops/model_tracking/base.py index 6c10de641..577022f5c 100644 --- a/verticapy/mlops/model_tracking/base.py +++ b/verticapy/mlops/model_tracking/base.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/mlops/model_versioning/__init__.py b/verticapy/mlops/model_versioning/__init__.py index 216f752ae..3ed084b1e 100644 --- a/verticapy/mlops/model_versioning/__init__.py +++ b/verticapy/mlops/model_versioning/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/mlops/model_versioning/base.py b/verticapy/mlops/model_versioning/base.py index b1350ad8f..7df54626a 100644 --- a/verticapy/mlops/model_versioning/base.py +++ b/verticapy/mlops/model_versioning/base.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/performance/__init__.py b/verticapy/performance/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/performance/__init__.py +++ b/verticapy/performance/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/performance/vertica/__init__.py b/verticapy/performance/vertica/__init__.py index a0d6721db..9a7bb477e 100755 --- a/verticapy/performance/vertica/__init__.py +++ b/verticapy/performance/vertica/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/performance/vertica/qprof.py b/verticapy/performance/vertica/qprof.py index d19c3081e..051340aa5 100755 --- a/verticapy/performance/vertica/qprof.py +++ b/verticapy/performance/vertica/qprof.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -675,7 +675,7 @@ def get_version() -> tuple[int, int, int, int]: .. note:: For more details, please look at - :mod:`verticapy.performance.vertica.QueryProfiler`. + :py:class:`verticapy.performance.vertica.QueryProfiler`. """ return vertica_version() @@ -734,7 +734,7 @@ def get_request( .. note:: For more details, please look at - :mod:`verticapy.performance.vertica.QueryProfiler`. + :py:class:`verticapy.performance.vertica.QueryProfiler`. """ res = format_query( query=self.request, indent_sql=indent_sql, print_sql=print_sql @@ -798,7 +798,7 @@ def get_qduration( .. note:: For more details, please look at - :mod:`verticapy.performance.vertica.QueryProfiler`. + :py:class:`verticapy.performance.vertica.QueryProfiler`. """ query = f""" SELECT @@ -897,7 +897,7 @@ def get_qsteps( .. note:: For more details, please look at - :mod:`verticapy.performance.vertica.QueryProfiler`. + :py:class:`verticapy.performance.vertica.QueryProfiler`. """ div = self._get_interval_str(unit) query = f""" @@ -967,7 +967,7 @@ def get_qplan( .. note:: For more details, please look at - :mod:`verticapy.performance.vertica.QueryProfiler`. + :py:class:`verticapy.performance.vertica.QueryProfiler`. """ query = f""" SELECT @@ -1075,7 +1075,7 @@ def get_qplan_profile( .. note:: For more details, please look at - :mod:`verticapy.performance.vertica.QueryProfiler`. + :py:class:`verticapy.performance.vertica.QueryProfiler`. """ div = self._get_interval_str(unit) where = "" @@ -1170,7 +1170,7 @@ def get_cpu_time( .. note:: For more details, please look at - :mod:`verticapy.performance.vertica.QueryProfiler`. + :py:class:`verticapy.performance.vertica.QueryProfiler`. """ query = f""" SELECT @@ -1233,7 +1233,7 @@ def get_qexecution_report(self) -> vDataFrame: .. note:: For more details, please look at - :mod:`verticapy.performance.vertica.QueryProfiler`. + :py:class:`verticapy.performance.vertica.QueryProfiler`. """ query = f""" SELECT @@ -1375,7 +1375,7 @@ def get_qexecution( .. note:: For more details, please look at - :mod:`verticapy.performance.vertica.QueryProfiler`. + :py:class:`verticapy.performance.vertica.QueryProfiler`. """ cond = f"node_name = '{node_name}'" if not (isinstance(path_id, NoneType)): @@ -1428,7 +1428,7 @@ def get_rp_status(self) -> vDataFrame: .. note:: For more details, please look at - :mod:`verticapy.performance.vertica.QueryProfiler`. + :py:class:`verticapy.performance.vertica.QueryProfiler`. """ query = """SELECT * FROM v_monitor.resource_pool_status;""" return vDataFrame(query) @@ -1475,7 +1475,7 @@ def get_cluster_config(self) -> vDataFrame: .. note:: For more details, please look at - :mod:`verticapy.performance.vertica.QueryProfiler`. + :py:class:`verticapy.performance.vertica.QueryProfiler`. """ query = """SELECT * FROM v_monitor.host_resources;""" return vDataFrame(query) diff --git a/verticapy/plotting/__init__.py b/verticapy/plotting/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/plotting/__init__.py +++ b/verticapy/plotting/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/__init__.py b/verticapy/plotting/_highcharts/__init__.py index cb562aea4..a0d6aac25 100755 --- a/verticapy/plotting/_highcharts/__init__.py +++ b/verticapy/plotting/_highcharts/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/acf.py b/verticapy/plotting/_highcharts/acf.py index 2b842b59f..58790c79f 100755 --- a/verticapy/plotting/_highcharts/acf.py +++ b/verticapy/plotting/_highcharts/acf.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/bar.py b/verticapy/plotting/_highcharts/bar.py index 943bfba0d..cda1e40d0 100755 --- a/verticapy/plotting/_highcharts/bar.py +++ b/verticapy/plotting/_highcharts/bar.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/barh.py b/verticapy/plotting/_highcharts/barh.py index 9c6986477..f7e294e7e 100755 --- a/verticapy/plotting/_highcharts/barh.py +++ b/verticapy/plotting/_highcharts/barh.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/base.py b/verticapy/plotting/_highcharts/base.py index c8213dcfa..7baf866e2 100755 --- a/verticapy/plotting/_highcharts/base.py +++ b/verticapy/plotting/_highcharts/base.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/boxplot.py b/verticapy/plotting/_highcharts/boxplot.py index 6396e0364..162a1b4f9 100755 --- a/verticapy/plotting/_highcharts/boxplot.py +++ b/verticapy/plotting/_highcharts/boxplot.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/candlestick.py b/verticapy/plotting/_highcharts/candlestick.py index bbd8c7c76..4c5728e72 100755 --- a/verticapy/plotting/_highcharts/candlestick.py +++ b/verticapy/plotting/_highcharts/candlestick.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/contour.py b/verticapy/plotting/_highcharts/contour.py index 9b5c151be..bf0da97de 100755 --- a/verticapy/plotting/_highcharts/contour.py +++ b/verticapy/plotting/_highcharts/contour.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/density.py b/verticapy/plotting/_highcharts/density.py index 30fc0613e..338be23f9 100755 --- a/verticapy/plotting/_highcharts/density.py +++ b/verticapy/plotting/_highcharts/density.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/heatmap.py b/verticapy/plotting/_highcharts/heatmap.py index 704d2d332..883e83816 100755 --- a/verticapy/plotting/_highcharts/heatmap.py +++ b/verticapy/plotting/_highcharts/heatmap.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/hist.py b/verticapy/plotting/_highcharts/hist.py index ec2912840..536c0dbe8 100644 --- a/verticapy/plotting/_highcharts/hist.py +++ b/verticapy/plotting/_highcharts/hist.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/line.py b/verticapy/plotting/_highcharts/line.py index b95177c6c..05fb7cac2 100755 --- a/verticapy/plotting/_highcharts/line.py +++ b/verticapy/plotting/_highcharts/line.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/machine_learning/__init__.py b/verticapy/plotting/_highcharts/machine_learning/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/plotting/_highcharts/machine_learning/__init__.py +++ b/verticapy/plotting/_highcharts/machine_learning/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/machine_learning/champion_challenger.py b/verticapy/plotting/_highcharts/machine_learning/champion_challenger.py index c5ef90b67..bf90059ab 100755 --- a/verticapy/plotting/_highcharts/machine_learning/champion_challenger.py +++ b/verticapy/plotting/_highcharts/machine_learning/champion_challenger.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/machine_learning/elbow.py b/verticapy/plotting/_highcharts/machine_learning/elbow.py index 46ecf73ef..44fc7d191 100755 --- a/verticapy/plotting/_highcharts/machine_learning/elbow.py +++ b/verticapy/plotting/_highcharts/machine_learning/elbow.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/machine_learning/importance.py b/verticapy/plotting/_highcharts/machine_learning/importance.py index 5b5d025d2..23b5a84b2 100755 --- a/verticapy/plotting/_highcharts/machine_learning/importance.py +++ b/verticapy/plotting/_highcharts/machine_learning/importance.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/machine_learning/lof.py b/verticapy/plotting/_highcharts/machine_learning/lof.py index 9152e1c9b..f1ec7c300 100755 --- a/verticapy/plotting/_highcharts/machine_learning/lof.py +++ b/verticapy/plotting/_highcharts/machine_learning/lof.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/machine_learning/logistic_reg.py b/verticapy/plotting/_highcharts/machine_learning/logistic_reg.py index 4fdef3085..2d017c7ff 100755 --- a/verticapy/plotting/_highcharts/machine_learning/logistic_reg.py +++ b/verticapy/plotting/_highcharts/machine_learning/logistic_reg.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/machine_learning/model_evaluation.py b/verticapy/plotting/_highcharts/machine_learning/model_evaluation.py index 5189927ff..3355e4622 100755 --- a/verticapy/plotting/_highcharts/machine_learning/model_evaluation.py +++ b/verticapy/plotting/_highcharts/machine_learning/model_evaluation.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/machine_learning/pca.py b/verticapy/plotting/_highcharts/machine_learning/pca.py index b6c49f48b..368f1c3dc 100755 --- a/verticapy/plotting/_highcharts/machine_learning/pca.py +++ b/verticapy/plotting/_highcharts/machine_learning/pca.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/machine_learning/regression.py b/verticapy/plotting/_highcharts/machine_learning/regression.py index f718a721d..5bac23afa 100755 --- a/verticapy/plotting/_highcharts/machine_learning/regression.py +++ b/verticapy/plotting/_highcharts/machine_learning/regression.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/machine_learning/regression_tree.py b/verticapy/plotting/_highcharts/machine_learning/regression_tree.py index e98e0a89f..3e7b6e7fd 100755 --- a/verticapy/plotting/_highcharts/machine_learning/regression_tree.py +++ b/verticapy/plotting/_highcharts/machine_learning/regression_tree.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/machine_learning/stepwise.py b/verticapy/plotting/_highcharts/machine_learning/stepwise.py index 1d2a337a0..a37b511d0 100755 --- a/verticapy/plotting/_highcharts/machine_learning/stepwise.py +++ b/verticapy/plotting/_highcharts/machine_learning/stepwise.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/machine_learning/svm.py b/verticapy/plotting/_highcharts/machine_learning/svm.py index 8cd8967f0..ef84f4813 100755 --- a/verticapy/plotting/_highcharts/machine_learning/svm.py +++ b/verticapy/plotting/_highcharts/machine_learning/svm.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/machine_learning/tsa.py b/verticapy/plotting/_highcharts/machine_learning/tsa.py index bbba76960..68849c299 100755 --- a/verticapy/plotting/_highcharts/machine_learning/tsa.py +++ b/verticapy/plotting/_highcharts/machine_learning/tsa.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/outliers.py b/verticapy/plotting/_highcharts/outliers.py index 71267ea46..de19519d9 100755 --- a/verticapy/plotting/_highcharts/outliers.py +++ b/verticapy/plotting/_highcharts/outliers.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/pie.py b/verticapy/plotting/_highcharts/pie.py index ee4955d2a..eded8a105 100755 --- a/verticapy/plotting/_highcharts/pie.py +++ b/verticapy/plotting/_highcharts/pie.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/range.py b/verticapy/plotting/_highcharts/range.py index 48da56d52..2747eeffb 100755 --- a/verticapy/plotting/_highcharts/range.py +++ b/verticapy/plotting/_highcharts/range.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/scatter.py b/verticapy/plotting/_highcharts/scatter.py index ed58ccdd6..a6514024f 100755 --- a/verticapy/plotting/_highcharts/scatter.py +++ b/verticapy/plotting/_highcharts/scatter.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_highcharts/spider.py b/verticapy/plotting/_highcharts/spider.py index 9a99af16f..d96c2ab15 100755 --- a/verticapy/plotting/_highcharts/spider.py +++ b/verticapy/plotting/_highcharts/spider.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/__init__.py b/verticapy/plotting/_matplotlib/__init__.py index 7c2f25c5c..f0935c70c 100755 --- a/verticapy/plotting/_matplotlib/__init__.py +++ b/verticapy/plotting/_matplotlib/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/acf.py b/verticapy/plotting/_matplotlib/acf.py index 72641baef..9bef4b889 100755 --- a/verticapy/plotting/_matplotlib/acf.py +++ b/verticapy/plotting/_matplotlib/acf.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/animated/__init__.py b/verticapy/plotting/_matplotlib/animated/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/plotting/_matplotlib/animated/__init__.py +++ b/verticapy/plotting/_matplotlib/animated/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/animated/bar.py b/verticapy/plotting/_matplotlib/animated/bar.py index 28bb041a7..f829fe8b5 100755 --- a/verticapy/plotting/_matplotlib/animated/bar.py +++ b/verticapy/plotting/_matplotlib/animated/bar.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/animated/base.py b/verticapy/plotting/_matplotlib/animated/base.py index 66352fa9a..22878f9b7 100755 --- a/verticapy/plotting/_matplotlib/animated/base.py +++ b/verticapy/plotting/_matplotlib/animated/base.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/animated/bubble.py b/verticapy/plotting/_matplotlib/animated/bubble.py index 84d1a69fd..adbd8ef01 100755 --- a/verticapy/plotting/_matplotlib/animated/bubble.py +++ b/verticapy/plotting/_matplotlib/animated/bubble.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/animated/line.py b/verticapy/plotting/_matplotlib/animated/line.py index 4a8ab57f5..93e6f1203 100755 --- a/verticapy/plotting/_matplotlib/animated/line.py +++ b/verticapy/plotting/_matplotlib/animated/line.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/animated/pie.py b/verticapy/plotting/_matplotlib/animated/pie.py index 7ba993556..a41b65b0b 100755 --- a/verticapy/plotting/_matplotlib/animated/pie.py +++ b/verticapy/plotting/_matplotlib/animated/pie.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/bar.py b/verticapy/plotting/_matplotlib/bar.py index d37bf49de..9ab49c184 100755 --- a/verticapy/plotting/_matplotlib/bar.py +++ b/verticapy/plotting/_matplotlib/bar.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/barh.py b/verticapy/plotting/_matplotlib/barh.py index 376987c4e..89e469e27 100755 --- a/verticapy/plotting/_matplotlib/barh.py +++ b/verticapy/plotting/_matplotlib/barh.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/base.py b/verticapy/plotting/_matplotlib/base.py index 30ded5e77..bb4240dc1 100755 --- a/verticapy/plotting/_matplotlib/base.py +++ b/verticapy/plotting/_matplotlib/base.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/boxplot.py b/verticapy/plotting/_matplotlib/boxplot.py index 05b0afcde..0a1577dab 100755 --- a/verticapy/plotting/_matplotlib/boxplot.py +++ b/verticapy/plotting/_matplotlib/boxplot.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/candlestick.py b/verticapy/plotting/_matplotlib/candlestick.py index 5209e960b..28fbd693b 100644 --- a/verticapy/plotting/_matplotlib/candlestick.py +++ b/verticapy/plotting/_matplotlib/candlestick.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/contour.py b/verticapy/plotting/_matplotlib/contour.py index 79cd0b144..8a5c18996 100755 --- a/verticapy/plotting/_matplotlib/contour.py +++ b/verticapy/plotting/_matplotlib/contour.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/density.py b/verticapy/plotting/_matplotlib/density.py index f5c82411b..4ecba6456 100755 --- a/verticapy/plotting/_matplotlib/density.py +++ b/verticapy/plotting/_matplotlib/density.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/heatmap.py b/verticapy/plotting/_matplotlib/heatmap.py index 5971c784c..2d1f467df 100755 --- a/verticapy/plotting/_matplotlib/heatmap.py +++ b/verticapy/plotting/_matplotlib/heatmap.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/hexbin.py b/verticapy/plotting/_matplotlib/hexbin.py index e0d835bdc..21d26c2f2 100755 --- a/verticapy/plotting/_matplotlib/hexbin.py +++ b/verticapy/plotting/_matplotlib/hexbin.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/hist.py b/verticapy/plotting/_matplotlib/hist.py index a10ac419a..dab5aaf85 100755 --- a/verticapy/plotting/_matplotlib/hist.py +++ b/verticapy/plotting/_matplotlib/hist.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/line.py b/verticapy/plotting/_matplotlib/line.py index aefa8290f..455575178 100755 --- a/verticapy/plotting/_matplotlib/line.py +++ b/verticapy/plotting/_matplotlib/line.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/machine_learning/__init__.py b/verticapy/plotting/_matplotlib/machine_learning/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/plotting/_matplotlib/machine_learning/__init__.py +++ b/verticapy/plotting/_matplotlib/machine_learning/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/machine_learning/champion_challenger.py b/verticapy/plotting/_matplotlib/machine_learning/champion_challenger.py index 6a6a0060d..3a6e2f6a6 100755 --- a/verticapy/plotting/_matplotlib/machine_learning/champion_challenger.py +++ b/verticapy/plotting/_matplotlib/machine_learning/champion_challenger.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/machine_learning/elbow.py b/verticapy/plotting/_matplotlib/machine_learning/elbow.py index 7007463b6..44ff44dda 100755 --- a/verticapy/plotting/_matplotlib/machine_learning/elbow.py +++ b/verticapy/plotting/_matplotlib/machine_learning/elbow.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/machine_learning/importance.py b/verticapy/plotting/_matplotlib/machine_learning/importance.py index d5bb53b3c..399342124 100755 --- a/verticapy/plotting/_matplotlib/machine_learning/importance.py +++ b/verticapy/plotting/_matplotlib/machine_learning/importance.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/machine_learning/kmeans.py b/verticapy/plotting/_matplotlib/machine_learning/kmeans.py index 4303f8249..0345995ff 100755 --- a/verticapy/plotting/_matplotlib/machine_learning/kmeans.py +++ b/verticapy/plotting/_matplotlib/machine_learning/kmeans.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/machine_learning/lof.py b/verticapy/plotting/_matplotlib/machine_learning/lof.py index 3be2bf54d..9d1d0e5e7 100755 --- a/verticapy/plotting/_matplotlib/machine_learning/lof.py +++ b/verticapy/plotting/_matplotlib/machine_learning/lof.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/machine_learning/logistic_reg.py b/verticapy/plotting/_matplotlib/machine_learning/logistic_reg.py index 174894b0a..3f70cfbd5 100755 --- a/verticapy/plotting/_matplotlib/machine_learning/logistic_reg.py +++ b/verticapy/plotting/_matplotlib/machine_learning/logistic_reg.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/machine_learning/model_evaluation.py b/verticapy/plotting/_matplotlib/machine_learning/model_evaluation.py index dc9940eac..8578a614e 100755 --- a/verticapy/plotting/_matplotlib/machine_learning/model_evaluation.py +++ b/verticapy/plotting/_matplotlib/machine_learning/model_evaluation.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/machine_learning/pca.py b/verticapy/plotting/_matplotlib/machine_learning/pca.py index a4198ae25..1dbb2a345 100755 --- a/verticapy/plotting/_matplotlib/machine_learning/pca.py +++ b/verticapy/plotting/_matplotlib/machine_learning/pca.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/machine_learning/regression.py b/verticapy/plotting/_matplotlib/machine_learning/regression.py index 8fee48b90..3af4796d3 100755 --- a/verticapy/plotting/_matplotlib/machine_learning/regression.py +++ b/verticapy/plotting/_matplotlib/machine_learning/regression.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/machine_learning/regression_tree.py b/verticapy/plotting/_matplotlib/machine_learning/regression_tree.py index 1992d204b..42cf0f5be 100755 --- a/verticapy/plotting/_matplotlib/machine_learning/regression_tree.py +++ b/verticapy/plotting/_matplotlib/machine_learning/regression_tree.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/machine_learning/stepwise.py b/verticapy/plotting/_matplotlib/machine_learning/stepwise.py index 70f74acfc..b673ba1f0 100755 --- a/verticapy/plotting/_matplotlib/machine_learning/stepwise.py +++ b/verticapy/plotting/_matplotlib/machine_learning/stepwise.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/machine_learning/svm.py b/verticapy/plotting/_matplotlib/machine_learning/svm.py index b546d9b5e..a83a85333 100755 --- a/verticapy/plotting/_matplotlib/machine_learning/svm.py +++ b/verticapy/plotting/_matplotlib/machine_learning/svm.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/machine_learning/tsa.py b/verticapy/plotting/_matplotlib/machine_learning/tsa.py index d3d72184b..8ff612963 100755 --- a/verticapy/plotting/_matplotlib/machine_learning/tsa.py +++ b/verticapy/plotting/_matplotlib/machine_learning/tsa.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/outliers.py b/verticapy/plotting/_matplotlib/outliers.py index 0ab2d593a..7d5f33e11 100755 --- a/verticapy/plotting/_matplotlib/outliers.py +++ b/verticapy/plotting/_matplotlib/outliers.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/pie.py b/verticapy/plotting/_matplotlib/pie.py index 788366195..dd72a0737 100755 --- a/verticapy/plotting/_matplotlib/pie.py +++ b/verticapy/plotting/_matplotlib/pie.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/range.py b/verticapy/plotting/_matplotlib/range.py index bdd71199d..a7e554a7c 100755 --- a/verticapy/plotting/_matplotlib/range.py +++ b/verticapy/plotting/_matplotlib/range.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/scatter.py b/verticapy/plotting/_matplotlib/scatter.py index ffd07d44c..d87937454 100755 --- a/verticapy/plotting/_matplotlib/scatter.py +++ b/verticapy/plotting/_matplotlib/scatter.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_matplotlib/spider.py b/verticapy/plotting/_matplotlib/spider.py index 707ad2ad0..845f1969c 100755 --- a/verticapy/plotting/_matplotlib/spider.py +++ b/verticapy/plotting/_matplotlib/spider.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/__init__.py b/verticapy/plotting/_plotly/__init__.py index 21b433dd2..fe0893e9d 100755 --- a/verticapy/plotting/_plotly/__init__.py +++ b/verticapy/plotting/_plotly/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/acf.py b/verticapy/plotting/_plotly/acf.py index febf44c0b..c767b56e3 100644 --- a/verticapy/plotting/_plotly/acf.py +++ b/verticapy/plotting/_plotly/acf.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/bar.py b/verticapy/plotting/_plotly/bar.py index e0b091406..250a74b04 100755 --- a/verticapy/plotting/_plotly/bar.py +++ b/verticapy/plotting/_plotly/bar.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/barh.py b/verticapy/plotting/_plotly/barh.py index 1707f2922..de8954449 100644 --- a/verticapy/plotting/_plotly/barh.py +++ b/verticapy/plotting/_plotly/barh.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/base.py b/verticapy/plotting/_plotly/base.py index 19497436d..21efca6fa 100755 --- a/verticapy/plotting/_plotly/base.py +++ b/verticapy/plotting/_plotly/base.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/boxplot.py b/verticapy/plotting/_plotly/boxplot.py index cfe3d450d..2f3b08ea7 100644 --- a/verticapy/plotting/_plotly/boxplot.py +++ b/verticapy/plotting/_plotly/boxplot.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/candlestick.py b/verticapy/plotting/_plotly/candlestick.py index ec04d0938..655d3d83a 100644 --- a/verticapy/plotting/_plotly/candlestick.py +++ b/verticapy/plotting/_plotly/candlestick.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/contour.py b/verticapy/plotting/_plotly/contour.py index 56fac38e3..28b2582f5 100644 --- a/verticapy/plotting/_plotly/contour.py +++ b/verticapy/plotting/_plotly/contour.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/density.py b/verticapy/plotting/_plotly/density.py index f2164ed32..1612d5fb4 100644 --- a/verticapy/plotting/_plotly/density.py +++ b/verticapy/plotting/_plotly/density.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/heatmap.py b/verticapy/plotting/_plotly/heatmap.py index a972c2956..215538f95 100644 --- a/verticapy/plotting/_plotly/heatmap.py +++ b/verticapy/plotting/_plotly/heatmap.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/hist.py b/verticapy/plotting/_plotly/hist.py index 7fb229ff8..be5962f07 100644 --- a/verticapy/plotting/_plotly/hist.py +++ b/verticapy/plotting/_plotly/hist.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/line.py b/verticapy/plotting/_plotly/line.py index 251ff45aa..a7277af4b 100644 --- a/verticapy/plotting/_plotly/line.py +++ b/verticapy/plotting/_plotly/line.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/machine_learning/__init__.py b/verticapy/plotting/_plotly/machine_learning/__init__.py index 62eb0aeaa..ffcd9fb20 100644 --- a/verticapy/plotting/_plotly/machine_learning/__init__.py +++ b/verticapy/plotting/_plotly/machine_learning/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/machine_learning/champion_challenger.py b/verticapy/plotting/_plotly/machine_learning/champion_challenger.py index 52cd8e8ce..d83f36724 100644 --- a/verticapy/plotting/_plotly/machine_learning/champion_challenger.py +++ b/verticapy/plotting/_plotly/machine_learning/champion_challenger.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/machine_learning/elbow.py b/verticapy/plotting/_plotly/machine_learning/elbow.py index 499d54707..d8744a489 100644 --- a/verticapy/plotting/_plotly/machine_learning/elbow.py +++ b/verticapy/plotting/_plotly/machine_learning/elbow.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/machine_learning/importance.py b/verticapy/plotting/_plotly/machine_learning/importance.py index 347de6668..b79c28ed8 100644 --- a/verticapy/plotting/_plotly/machine_learning/importance.py +++ b/verticapy/plotting/_plotly/machine_learning/importance.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/machine_learning/kmeans.py b/verticapy/plotting/_plotly/machine_learning/kmeans.py index c30b40df7..6330cd002 100644 --- a/verticapy/plotting/_plotly/machine_learning/kmeans.py +++ b/verticapy/plotting/_plotly/machine_learning/kmeans.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/machine_learning/lof.py b/verticapy/plotting/_plotly/machine_learning/lof.py index 37e468030..4ed04b997 100644 --- a/verticapy/plotting/_plotly/machine_learning/lof.py +++ b/verticapy/plotting/_plotly/machine_learning/lof.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/machine_learning/logistic_reg.py b/verticapy/plotting/_plotly/machine_learning/logistic_reg.py index 24a296210..176e7d157 100644 --- a/verticapy/plotting/_plotly/machine_learning/logistic_reg.py +++ b/verticapy/plotting/_plotly/machine_learning/logistic_reg.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/machine_learning/model_evaluation.py b/verticapy/plotting/_plotly/machine_learning/model_evaluation.py index 61e60eb54..36e8c4480 100644 --- a/verticapy/plotting/_plotly/machine_learning/model_evaluation.py +++ b/verticapy/plotting/_plotly/machine_learning/model_evaluation.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/machine_learning/pca.py b/verticapy/plotting/_plotly/machine_learning/pca.py index f0c2c0c05..842cd5ae9 100644 --- a/verticapy/plotting/_plotly/machine_learning/pca.py +++ b/verticapy/plotting/_plotly/machine_learning/pca.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/machine_learning/regression.py b/verticapy/plotting/_plotly/machine_learning/regression.py index 0fdd485cf..aefa07c6b 100644 --- a/verticapy/plotting/_plotly/machine_learning/regression.py +++ b/verticapy/plotting/_plotly/machine_learning/regression.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/machine_learning/regression_tree.py b/verticapy/plotting/_plotly/machine_learning/regression_tree.py index a0cb7646a..01e57eb92 100644 --- a/verticapy/plotting/_plotly/machine_learning/regression_tree.py +++ b/verticapy/plotting/_plotly/machine_learning/regression_tree.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/machine_learning/stepwise.py b/verticapy/plotting/_plotly/machine_learning/stepwise.py index c16d2e836..c3cd6f610 100644 --- a/verticapy/plotting/_plotly/machine_learning/stepwise.py +++ b/verticapy/plotting/_plotly/machine_learning/stepwise.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/machine_learning/svm.py b/verticapy/plotting/_plotly/machine_learning/svm.py index 0401d7e16..bce5d840d 100644 --- a/verticapy/plotting/_plotly/machine_learning/svm.py +++ b/verticapy/plotting/_plotly/machine_learning/svm.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/machine_learning/tsa.py b/verticapy/plotting/_plotly/machine_learning/tsa.py index 628f21488..17de8bb36 100644 --- a/verticapy/plotting/_plotly/machine_learning/tsa.py +++ b/verticapy/plotting/_plotly/machine_learning/tsa.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/outliers.py b/verticapy/plotting/_plotly/outliers.py index eb56c4c0f..437b76fdf 100644 --- a/verticapy/plotting/_plotly/outliers.py +++ b/verticapy/plotting/_plotly/outliers.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/pie.py b/verticapy/plotting/_plotly/pie.py index 6f6518898..cab156129 100644 --- a/verticapy/plotting/_plotly/pie.py +++ b/verticapy/plotting/_plotly/pie.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/range.py b/verticapy/plotting/_plotly/range.py index caedb9fd9..e7bf7a54a 100644 --- a/verticapy/plotting/_plotly/range.py +++ b/verticapy/plotting/_plotly/range.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/scatter.py b/verticapy/plotting/_plotly/scatter.py index 7d77cd0e2..b91c316d6 100644 --- a/verticapy/plotting/_plotly/scatter.py +++ b/verticapy/plotting/_plotly/scatter.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_plotly/spider.py b/verticapy/plotting/_plotly/spider.py index cd31bf4c2..c19656ad1 100644 --- a/verticapy/plotting/_plotly/spider.py +++ b/verticapy/plotting/_plotly/spider.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/_utils.py b/verticapy/plotting/_utils.py index 06787d886..6c993fce0 100755 --- a/verticapy/plotting/_utils.py +++ b/verticapy/plotting/_utils.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/base.py b/verticapy/plotting/base.py index 8896e099d..dbef2c22f 100755 --- a/verticapy/plotting/base.py +++ b/verticapy/plotting/base.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/plotting/sql.py b/verticapy/plotting/sql.py index db38e1fa8..cfc4f2ed4 100755 --- a/verticapy/plotting/sql.py +++ b/verticapy/plotting/sql.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sdk/__init__.py b/verticapy/sdk/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/sdk/__init__.py +++ b/verticapy/sdk/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sdk/vertica/__init__.py b/verticapy/sdk/vertica/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/sdk/vertica/__init__.py +++ b/verticapy/sdk/vertica/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sdk/vertica/udf/__init__.py b/verticapy/sdk/vertica/udf/__init__.py index e70675245..2d89e0e30 100755 --- a/verticapy/sdk/vertica/udf/__init__.py +++ b/verticapy/sdk/vertica/udf/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sdk/vertica/udf/gen.py b/verticapy/sdk/vertica/udf/gen.py index ab10f0363..f38077a49 100755 --- a/verticapy/sdk/vertica/udf/gen.py +++ b/verticapy/sdk/vertica/udf/gen.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sdk/vertica/udf/load.py b/verticapy/sdk/vertica/udf/load.py index fb8658128..35cc65378 100755 --- a/verticapy/sdk/vertica/udf/load.py +++ b/verticapy/sdk/vertica/udf/load.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sdk/vertica/udf/utils.py b/verticapy/sdk/vertica/udf/utils.py index bd91f839b..3507e5465 100755 --- a/verticapy/sdk/vertica/udf/utils.py +++ b/verticapy/sdk/vertica/udf/utils.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sql/__init__.py b/verticapy/sql/__init__.py index 07831ea75..08cdeca8d 100755 --- a/verticapy/sql/__init__.py +++ b/verticapy/sql/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sql/create.py b/verticapy/sql/create.py index fcb968102..71547341a 100755 --- a/verticapy/sql/create.py +++ b/verticapy/sql/create.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sql/drop.py b/verticapy/sql/drop.py index 1fdf18c80..8f9b486fb 100755 --- a/verticapy/sql/drop.py +++ b/verticapy/sql/drop.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sql/dtypes.py b/verticapy/sql/dtypes.py index 002ce3234..c26d31e05 100644 --- a/verticapy/sql/dtypes.py +++ b/verticapy/sql/dtypes.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sql/flex.py b/verticapy/sql/flex.py index d04856b2b..5e71d0535 100755 --- a/verticapy/sql/flex.py +++ b/verticapy/sql/flex.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sql/functions/__init__.py b/verticapy/sql/functions/__init__.py index 3d44b6a95..765e5bd00 100755 --- a/verticapy/sql/functions/__init__.py +++ b/verticapy/sql/functions/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sql/functions/analytic.py b/verticapy/sql/functions/analytic.py index 754cb011d..39fc3e87d 100755 --- a/verticapy/sql/functions/analytic.py +++ b/verticapy/sql/functions/analytic.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sql/functions/conditional.py b/verticapy/sql/functions/conditional.py index 9f6f23d46..3a5ed9b46 100755 --- a/verticapy/sql/functions/conditional.py +++ b/verticapy/sql/functions/conditional.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sql/functions/date.py b/verticapy/sql/functions/date.py index 4df60fe75..0d8cb769d 100755 --- a/verticapy/sql/functions/date.py +++ b/verticapy/sql/functions/date.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sql/functions/math.py b/verticapy/sql/functions/math.py index 465be07cb..0cb4000a2 100755 --- a/verticapy/sql/functions/math.py +++ b/verticapy/sql/functions/math.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sql/functions/null_handling.py b/verticapy/sql/functions/null_handling.py index e442214a4..b9e4b42ca 100755 --- a/verticapy/sql/functions/null_handling.py +++ b/verticapy/sql/functions/null_handling.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sql/functions/random.py b/verticapy/sql/functions/random.py index 7aa106ef6..d70ce2c7f 100755 --- a/verticapy/sql/functions/random.py +++ b/verticapy/sql/functions/random.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sql/functions/regexp.py b/verticapy/sql/functions/regexp.py index 7e674a10e..a8aef8a17 100755 --- a/verticapy/sql/functions/regexp.py +++ b/verticapy/sql/functions/regexp.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sql/functions/string.py b/verticapy/sql/functions/string.py index d30867bfd..a190cc9a2 100755 --- a/verticapy/sql/functions/string.py +++ b/verticapy/sql/functions/string.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sql/geo/__init__.py b/verticapy/sql/geo/__init__.py index 70e43fe98..b067d3f1e 100755 --- a/verticapy/sql/geo/__init__.py +++ b/verticapy/sql/geo/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sql/geo/functions.py b/verticapy/sql/geo/functions.py index 0473be46d..c81edd30d 100755 --- a/verticapy/sql/geo/functions.py +++ b/verticapy/sql/geo/functions.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sql/geo/index.py b/verticapy/sql/geo/index.py index 8d3e4fcc0..45b004e69 100755 --- a/verticapy/sql/geo/index.py +++ b/verticapy/sql/geo/index.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/sql/insert.py b/verticapy/sql/insert.py index da5174e75..f975de153 100755 --- a/verticapy/sql/insert.py +++ b/verticapy/sql/insert.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -108,14 +108,14 @@ def insert_into( schema = "public", data = [ [3.3, 4.5, 5.6, 7.8, "Iris-setosa"], - [4.3, 4.7, 9.6, 1.8, "Iris-virginica"] + [4.3, 4.7, 9.6, 1.8, "Iris-virginica"], ], genSQL = True, ) .. seealso:: - | :py:module:`read_json`_ - | :py:module:`read_csv`_ + | :py:func:`read_json` : Ingests a JSON file using flex tables. + | :py:func:`read_csv` : Ingests a CSV file using flex tables. """ column_names = format_type(column_names, dtype=list) if not schema: diff --git a/verticapy/sql/sys.py b/verticapy/sql/sys.py index 8338f34e2..475030a6f 100755 --- a/verticapy/sql/sys.py +++ b/verticapy/sql/sys.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/stats/__init__.py b/verticapy/stats/__init__.py index 375a1ff4f..8621be2d9 100755 --- a/verticapy/stats/__init__.py +++ b/verticapy/stats/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.stats' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.sql.functions' instead " "to ensure compatibility with upcoming versions.\n" "Note: Statistical tests have been relocated to " diff --git a/verticapy/tests/__init__.py b/verticapy/tests/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests/__init__.py +++ b/verticapy/tests/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/base.py b/verticapy/tests/base.py index 3a5737ef5..3dc9aad45 100755 --- a/verticapy/tests/base.py +++ b/verticapy/tests/base.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/conftest.py b/verticapy/tests/conftest.py index 11fa60cb4..6c04d5a65 100755 --- a/verticapy/tests/conftest.py +++ b/verticapy/tests/conftest.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/connect/__init__.py b/verticapy/tests/connect/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests/connect/__init__.py +++ b/verticapy/tests/connect/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/connect/test_connect.py b/verticapy/tests/connect/test_connect.py index e9ba998ab..89d663d5a 100755 --- a/verticapy/tests/connect/test_connect.py +++ b/verticapy/tests/connect/test_connect.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/datasets/__init__.py b/verticapy/tests/datasets/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests/datasets/__init__.py +++ b/verticapy/tests/datasets/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/datasets/test_datasets.py b/verticapy/tests/datasets/test_datasets.py index 49ae454b4..139218d87 100755 --- a/verticapy/tests/datasets/test_datasets.py +++ b/verticapy/tests/datasets/test_datasets.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/geo/__init__.py b/verticapy/tests/geo/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests/geo/__init__.py +++ b/verticapy/tests/geo/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/geo/test_geo.py b/verticapy/tests/geo/test_geo.py index e241ac0af..8d2642773 100755 --- a/verticapy/tests/geo/test_geo.py +++ b/verticapy/tests/geo/test_geo.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/hchart/__init__.py b/verticapy/tests/hchart/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests/hchart/__init__.py +++ b/verticapy/tests/hchart/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/hchart/test_hchart.py b/verticapy/tests/hchart/test_hchart.py index a778f6169..fede36e0b 100755 --- a/verticapy/tests/hchart/test_hchart.py +++ b/verticapy/tests/hchart/test_hchart.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/sql/__init__.py b/verticapy/tests/sql/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests/sql/__init__.py +++ b/verticapy/tests/sql/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/sql/test_sql.py b/verticapy/tests/sql/test_sql.py index c8cc50929..0a5b6cd63 100755 --- a/verticapy/tests/sql/test_sql.py +++ b/verticapy/tests/sql/test_sql.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/stats/__init__.py b/verticapy/tests/stats/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests/stats/__init__.py +++ b/verticapy/tests/stats/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/stats/test_stats.py b/verticapy/tests/stats/test_stats.py index b9a1eb015..0c40476f3 100755 --- a/verticapy/tests/stats/test_stats.py +++ b/verticapy/tests/stats/test_stats.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/udf/__init__.py b/verticapy/tests/udf/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests/udf/__init__.py +++ b/verticapy/tests/udf/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/udf/test_udf.py b/verticapy/tests/udf/test_udf.py index 45a40e1b6..a4920c4ac 100755 --- a/verticapy/tests/udf/test_udf.py +++ b/verticapy/tests/udf/test_udf.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/utilities/__init__.py b/verticapy/tests/utilities/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests/utilities/__init__.py +++ b/verticapy/tests/utilities/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/utilities/test_utilities.py b/verticapy/tests/utilities/test_utilities.py index 49461340e..7fc5b2149 100755 --- a/verticapy/tests/utilities/test_utilities.py +++ b/verticapy/tests/utilities/test_utilities.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/utils/__init__.py b/verticapy/tests/utils/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests/utils/__init__.py +++ b/verticapy/tests/utils/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/utils/log.py b/verticapy/tests/utils/log.py index 33ec3193b..0f7bf79e0 100755 --- a/verticapy/tests/utils/log.py +++ b/verticapy/tests/utils/log.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vDataFrame/__init__.py b/verticapy/tests/vDataFrame/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests/vDataFrame/__init__.py +++ b/verticapy/tests/vDataFrame/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vDataFrame/test_vDF_combine_join_sort.py b/verticapy/tests/vDataFrame/test_vDF_combine_join_sort.py index c0f729a35..23b328ab7 100755 --- a/verticapy/tests/vDataFrame/test_vDF_combine_join_sort.py +++ b/verticapy/tests/vDataFrame/test_vDF_combine_join_sort.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vDataFrame/test_vDF_correlation.py b/verticapy/tests/vDataFrame/test_vDF_correlation.py index 04ff73775..4fa3d0f42 100755 --- a/verticapy/tests/vDataFrame/test_vDF_correlation.py +++ b/verticapy/tests/vDataFrame/test_vDF_correlation.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vDataFrame/test_vDF_create.py b/verticapy/tests/vDataFrame/test_vDF_create.py index 01fd8a5d7..0c1144ab0 100755 --- a/verticapy/tests/vDataFrame/test_vDF_create.py +++ b/verticapy/tests/vDataFrame/test_vDF_create.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vDataFrame/test_vDF_descriptive_statistics.py b/verticapy/tests/vDataFrame/test_vDF_descriptive_statistics.py index c11ac78c8..74182365f 100755 --- a/verticapy/tests/vDataFrame/test_vDF_descriptive_statistics.py +++ b/verticapy/tests/vDataFrame/test_vDF_descriptive_statistics.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vDataFrame/test_vDF_feature_engineering.py b/verticapy/tests/vDataFrame/test_vDF_feature_engineering.py index 771d47ee5..00245dfcc 100755 --- a/verticapy/tests/vDataFrame/test_vDF_feature_engineering.py +++ b/verticapy/tests/vDataFrame/test_vDF_feature_engineering.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vDataFrame/test_vDF_filter_sample.py b/verticapy/tests/vDataFrame/test_vDF_filter_sample.py index 7d6303fb7..603a61cd4 100755 --- a/verticapy/tests/vDataFrame/test_vDF_filter_sample.py +++ b/verticapy/tests/vDataFrame/test_vDF_filter_sample.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vDataFrame/test_vDF_plot.py b/verticapy/tests/vDataFrame/test_vDF_plot.py index 3d2d9f47a..666f979f4 100755 --- a/verticapy/tests/vDataFrame/test_vDF_plot.py +++ b/verticapy/tests/vDataFrame/test_vDF_plot.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vDataFrame/test_vDF_preprocessing.py b/verticapy/tests/vDataFrame/test_vDF_preprocessing.py index ba9bcd472..8a81a76a2 100755 --- a/verticapy/tests/vDataFrame/test_vDF_preprocessing.py +++ b/verticapy/tests/vDataFrame/test_vDF_preprocessing.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vDataFrame/test_vDF_utilities.py b/verticapy/tests/vDataFrame/test_vDF_utilities.py index 133b455e9..a9f617ff6 100755 --- a/verticapy/tests/vDataFrame/test_vDF_utilities.py +++ b/verticapy/tests/vDataFrame/test_vDF_utilities.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/__init__.py b/verticapy/tests/vModel/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests/vModel/__init__.py +++ b/verticapy/tests/vModel/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_balance.py b/verticapy/tests/vModel/test_balance.py index b92b614da..a2bfb8451 100755 --- a/verticapy/tests/vModel/test_balance.py +++ b/verticapy/tests/vModel/test_balance.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_bisecting_kmeans.py b/verticapy/tests/vModel/test_bisecting_kmeans.py index 88e020de6..8177930d0 100755 --- a/verticapy/tests/vModel/test_bisecting_kmeans.py +++ b/verticapy/tests/vModel/test_bisecting_kmeans.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_countvectorizer.py b/verticapy/tests/vModel/test_countvectorizer.py index f6fc08a6e..bb2bf439e 100755 --- a/verticapy/tests/vModel/test_countvectorizer.py +++ b/verticapy/tests/vModel/test_countvectorizer.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_dbscan.py b/verticapy/tests/vModel/test_dbscan.py index 0307be50b..2dbc97bfd 100755 --- a/verticapy/tests/vModel/test_dbscan.py +++ b/verticapy/tests/vModel/test_dbscan.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_delphi.py b/verticapy/tests/vModel/test_delphi.py index 196bc0e75..9985660b6 100755 --- a/verticapy/tests/vModel/test_delphi.py +++ b/verticapy/tests/vModel/test_delphi.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_dummy_tree_classifier.py b/verticapy/tests/vModel/test_dummy_tree_classifier.py index f97ada221..6c245bdf6 100755 --- a/verticapy/tests/vModel/test_dummy_tree_classifier.py +++ b/verticapy/tests/vModel/test_dummy_tree_classifier.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_dummy_tree_regressor.py b/verticapy/tests/vModel/test_dummy_tree_regressor.py index ad187b290..0ad7d1549 100755 --- a/verticapy/tests/vModel/test_dummy_tree_regressor.py +++ b/verticapy/tests/vModel/test_dummy_tree_regressor.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_iforest.py b/verticapy/tests/vModel/test_iforest.py index 28d45db92..d94b52ec7 100755 --- a/verticapy/tests/vModel/test_iforest.py +++ b/verticapy/tests/vModel/test_iforest.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_kde.py b/verticapy/tests/vModel/test_kde.py index 653fb0544..54d01e704 100755 --- a/verticapy/tests/vModel/test_kde.py +++ b/verticapy/tests/vModel/test_kde.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_kmeans.py b/verticapy/tests/vModel/test_kmeans.py index c59b05016..3f6107607 100755 --- a/verticapy/tests/vModel/test_kmeans.py +++ b/verticapy/tests/vModel/test_kmeans.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_knn_classifier.py b/verticapy/tests/vModel/test_knn_classifier.py index 2918d5fc7..f9131b19d 100755 --- a/verticapy/tests/vModel/test_knn_classifier.py +++ b/verticapy/tests/vModel/test_knn_classifier.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_knn_regressor.py b/verticapy/tests/vModel/test_knn_regressor.py index a96593887..d61362a57 100755 --- a/verticapy/tests/vModel/test_knn_regressor.py +++ b/verticapy/tests/vModel/test_knn_regressor.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_kprototypes.py b/verticapy/tests/vModel/test_kprototypes.py index c8681a768..2d9b476d0 100755 --- a/verticapy/tests/vModel/test_kprototypes.py +++ b/verticapy/tests/vModel/test_kprototypes.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_linear_svc.py b/verticapy/tests/vModel/test_linear_svc.py index 446e9fe74..40823b758 100755 --- a/verticapy/tests/vModel/test_linear_svc.py +++ b/verticapy/tests/vModel/test_linear_svc.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_linear_svr.py b/verticapy/tests/vModel/test_linear_svr.py index 28d5a0637..d8c589b7e 100755 --- a/verticapy/tests/vModel/test_linear_svr.py +++ b/verticapy/tests/vModel/test_linear_svr.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_lof.py b/verticapy/tests/vModel/test_lof.py index f2f586cd7..d8e1d9217 100755 --- a/verticapy/tests/vModel/test_lof.py +++ b/verticapy/tests/vModel/test_lof.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_logistic_regression.py b/verticapy/tests/vModel/test_logistic_regression.py index b30840305..f8c1c5ebd 100755 --- a/verticapy/tests/vModel/test_logistic_regression.py +++ b/verticapy/tests/vModel/test_logistic_regression.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_mca.py b/verticapy/tests/vModel/test_mca.py index 52c0bc7ae..22e769b98 100755 --- a/verticapy/tests/vModel/test_mca.py +++ b/verticapy/tests/vModel/test_mca.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_memmodel.py b/verticapy/tests/vModel/test_memmodel.py index 28fd3c639..0085839b6 100755 --- a/verticapy/tests/vModel/test_memmodel.py +++ b/verticapy/tests/vModel/test_memmodel.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_model_selection.py b/verticapy/tests/vModel/test_model_selection.py index 75446bd5c..a8cf15004 100755 --- a/verticapy/tests/vModel/test_model_selection.py +++ b/verticapy/tests/vModel/test_model_selection.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_naive_bayes.py b/verticapy/tests/vModel/test_naive_bayes.py index 09da5cf02..71d067eb2 100755 --- a/verticapy/tests/vModel/test_naive_bayes.py +++ b/verticapy/tests/vModel/test_naive_bayes.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_nearestcentroid.py b/verticapy/tests/vModel/test_nearestcentroid.py index 54aff3b5c..1dd2479b5 100755 --- a/verticapy/tests/vModel/test_nearestcentroid.py +++ b/verticapy/tests/vModel/test_nearestcentroid.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_normalizer.py b/verticapy/tests/vModel/test_normalizer.py index a64dec0f7..309b955f2 100755 --- a/verticapy/tests/vModel/test_normalizer.py +++ b/verticapy/tests/vModel/test_normalizer.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_onehotencoder.py b/verticapy/tests/vModel/test_onehotencoder.py index a165da8ae..91f32d5ea 100755 --- a/verticapy/tests/vModel/test_onehotencoder.py +++ b/verticapy/tests/vModel/test_onehotencoder.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_pca.py b/verticapy/tests/vModel/test_pca.py index 8cd3e419e..0c3ac45f8 100755 --- a/verticapy/tests/vModel/test_pca.py +++ b/verticapy/tests/vModel/test_pca.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_pipeline.py b/verticapy/tests/vModel/test_pipeline.py index 3dd9bab84..17f974c4d 100755 --- a/verticapy/tests/vModel/test_pipeline.py +++ b/verticapy/tests/vModel/test_pipeline.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_svd.py b/verticapy/tests/vModel/test_svd.py index 959fc144e..aff9d319b 100755 --- a/verticapy/tests/vModel/test_svd.py +++ b/verticapy/tests/vModel/test_svd.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_tools.py b/verticapy/tests/vModel/test_tools.py index e14b3ba58..e7d8cd530 100755 --- a/verticapy/tests/vModel/test_tools.py +++ b/verticapy/tests/vModel/test_tools.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests/vModel/test_xgb_classifier.py b/verticapy/tests/vModel/test_xgb_classifier.py index b89f94ffa..c8a5f5cd7 100755 --- a/verticapy/tests/vModel/test_xgb_classifier.py +++ b/verticapy/tests/vModel/test_xgb_classifier.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/__init__.py b/verticapy/tests_new/__init__.py index 8b80cd90b..d7cca0adc 100755 --- a/verticapy/tests_new/__init__.py +++ b/verticapy/tests_new/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/config/__init__.py b/verticapy/tests_new/config/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/config/__init__.py +++ b/verticapy/tests_new/config/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/conftest.py b/verticapy/tests_new/conftest.py index c914d864e..4ab62a176 100755 --- a/verticapy/tests_new/conftest.py +++ b/verticapy/tests_new/conftest.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/connection/__init__.py b/verticapy/tests_new/connection/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/connection/__init__.py +++ b/verticapy/tests_new/connection/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/core/parsers/__init__.py b/verticapy/tests_new/core/parsers/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/core/parsers/__init__.py +++ b/verticapy/tests_new/core/parsers/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/core/string_sql/__init__.py b/verticapy/tests_new/core/string_sql/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/core/string_sql/__init__.py +++ b/verticapy/tests_new/core/string_sql/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/core/tablesample/__init__.py b/verticapy/tests_new/core/tablesample/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/core/tablesample/__init__.py +++ b/verticapy/tests_new/core/tablesample/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/core/vdataframe/__init__.py b/verticapy/tests_new/core/vdataframe/__init__.py index 24b8032e8..6417440d0 100755 --- a/verticapy/tests_new/core/vdataframe/__init__.py +++ b/verticapy/tests_new/core/vdataframe/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/core/vdataframe/test_agg.py b/verticapy/tests_new/core/vdataframe/test_agg.py index 1c4b1d081..72d5ee9e1 100644 --- a/verticapy/tests_new/core/vdataframe/test_agg.py +++ b/verticapy/tests_new/core/vdataframe/test_agg.py @@ -1,5 +1,5 @@ """ -(c) Copyright [2018-2023] OpenText or one of its +(c) Copyright [2018-2024] OpenText or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/core/vdataframe/test_correlation.py b/verticapy/tests_new/core/vdataframe/test_correlation.py index 63d7b5b18..f006d2829 100644 --- a/verticapy/tests_new/core/vdataframe/test_correlation.py +++ b/verticapy/tests_new/core/vdataframe/test_correlation.py @@ -1,5 +1,5 @@ """ -(c) Copyright [2018-2023] OpenText or one of its +(c) Copyright [2018-2024] OpenText or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/core/vdataframe/test_encoding.py b/verticapy/tests_new/core/vdataframe/test_encoding.py index 5dedd7cc8..9d5f7db58 100644 --- a/verticapy/tests_new/core/vdataframe/test_encoding.py +++ b/verticapy/tests_new/core/vdataframe/test_encoding.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/core/vdataframe/test_fill.py b/verticapy/tests_new/core/vdataframe/test_fill.py index ebc36b6da..6dcc5b2e7 100644 --- a/verticapy/tests_new/core/vdataframe/test_fill.py +++ b/verticapy/tests_new/core/vdataframe/test_fill.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/core/vdataframe/test_math.py b/verticapy/tests_new/core/vdataframe/test_math.py index b61349db1..26b5e5d6b 100644 --- a/verticapy/tests_new/core/vdataframe/test_math.py +++ b/verticapy/tests_new/core/vdataframe/test_math.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/core/vdataframe/test_normalize.py b/verticapy/tests_new/core/vdataframe/test_normalize.py index 47ff30e0c..64c5b8d6e 100644 --- a/verticapy/tests_new/core/vdataframe/test_normalize.py +++ b/verticapy/tests_new/core/vdataframe/test_normalize.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/core/vdataframe/test_rolling.py b/verticapy/tests_new/core/vdataframe/test_rolling.py index e50ad71c7..885bc0a67 100644 --- a/verticapy/tests_new/core/vdataframe/test_rolling.py +++ b/verticapy/tests_new/core/vdataframe/test_rolling.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/core/vdataframe/test_text.py b/verticapy/tests_new/core/vdataframe/test_text.py index 81984e487..d20e164c3 100644 --- a/verticapy/tests_new/core/vdataframe/test_text.py +++ b/verticapy/tests_new/core/vdataframe/test_text.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/core/vdataframe/test_typing.py b/verticapy/tests_new/core/vdataframe/test_typing.py index 83c357e30..40dc9671b 100644 --- a/verticapy/tests_new/core/vdataframe/test_typing.py +++ b/verticapy/tests_new/core/vdataframe/test_typing.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/datasets/__init__.py b/verticapy/tests_new/datasets/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/datasets/__init__.py +++ b/verticapy/tests_new/datasets/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/jupyter/__init__.py b/verticapy/tests_new/jupyter/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/jupyter/__init__.py +++ b/verticapy/tests_new/jupyter/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/jupyter/extensions/__init__.py b/verticapy/tests_new/jupyter/extensions/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/jupyter/extensions/__init__.py +++ b/verticapy/tests_new/jupyter/extensions/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/machine_learning/__init__.py b/verticapy/tests_new/machine_learning/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/machine_learning/__init__.py +++ b/verticapy/tests_new/machine_learning/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/machine_learning/memmodel/__init__.py b/verticapy/tests_new/machine_learning/memmodel/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/machine_learning/memmodel/__init__.py +++ b/verticapy/tests_new/machine_learning/memmodel/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/machine_learning/metrics/__init__.py b/verticapy/tests_new/machine_learning/metrics/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/machine_learning/metrics/__init__.py +++ b/verticapy/tests_new/machine_learning/metrics/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/machine_learning/metrics/test_classification_metrics.py b/verticapy/tests_new/machine_learning/metrics/test_classification_metrics.py index 438184085..689d8bfe9 100644 --- a/verticapy/tests_new/machine_learning/metrics/test_classification_metrics.py +++ b/verticapy/tests_new/machine_learning/metrics/test_classification_metrics.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/machine_learning/metrics/test_regression_metrics.py b/verticapy/tests_new/machine_learning/metrics/test_regression_metrics.py index 7a74de916..3a0bf99af 100755 --- a/verticapy/tests_new/machine_learning/metrics/test_regression_metrics.py +++ b/verticapy/tests_new/machine_learning/metrics/test_regression_metrics.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/machine_learning/model_selection/__init__.py b/verticapy/tests_new/machine_learning/model_selection/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/machine_learning/model_selection/__init__.py +++ b/verticapy/tests_new/machine_learning/model_selection/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/machine_learning/vertica/__init__.py b/verticapy/tests_new/machine_learning/vertica/__init__.py index 4191b1968..f98d2f45f 100755 --- a/verticapy/tests_new/machine_learning/vertica/__init__.py +++ b/verticapy/tests_new/machine_learning/vertica/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/machine_learning/vertica/conftest.py b/verticapy/tests_new/machine_learning/vertica/conftest.py index da196a954..6cfe69da7 100644 --- a/verticapy/tests_new/machine_learning/vertica/conftest.py +++ b/verticapy/tests_new/machine_learning/vertica/conftest.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/machine_learning/vertica/test_base_model_methods.py b/verticapy/tests_new/machine_learning/vertica/test_base_model_methods.py index d93e3e967..0012422b5 100644 --- a/verticapy/tests_new/machine_learning/vertica/test_base_model_methods.py +++ b/verticapy/tests_new/machine_learning/vertica/test_base_model_methods.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/machine_learning/vertica/test_linear_model.py b/verticapy/tests_new/machine_learning/vertica/test_linear_model.py index 06dd49c46..6cf65e874 100644 --- a/verticapy/tests_new/machine_learning/vertica/test_linear_model.py +++ b/verticapy/tests_new/machine_learning/vertica/test_linear_model.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/machine_learning/vertica/test_model_management.py b/verticapy/tests_new/machine_learning/vertica/test_model_management.py index 869dfef5d..23a6a16d6 100644 --- a/verticapy/tests_new/machine_learning/vertica/test_model_management.py +++ b/verticapy/tests_new/machine_learning/vertica/test_model_management.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/machine_learning/vertica/test_tree_model.py b/verticapy/tests_new/machine_learning/vertica/test_tree_model.py index 45c939966..1e635a41c 100644 --- a/verticapy/tests_new/machine_learning/vertica/test_tree_model.py +++ b/verticapy/tests_new/machine_learning/vertica/test_tree_model.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/mlops/__init__.py b/verticapy/tests_new/mlops/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/mlops/__init__.py +++ b/verticapy/tests_new/mlops/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/mlops/test_model_tracking.py b/verticapy/tests_new/mlops/test_model_tracking.py index 3b5a4fe40..69e10e1c9 100644 --- a/verticapy/tests_new/mlops/test_model_tracking.py +++ b/verticapy/tests_new/mlops/test_model_tracking.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/mlops/test_model_versioning.py b/verticapy/tests_new/mlops/test_model_versioning.py index 82c05bf90..75819ea27 100644 --- a/verticapy/tests_new/mlops/test_model_versioning.py +++ b/verticapy/tests_new/mlops/test_model_versioning.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/__init__.py b/verticapy/tests_new/plotting/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/plotting/__init__.py +++ b/verticapy/tests_new/plotting/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/base_test_files.py b/verticapy/tests_new/plotting/base_test_files.py index 6f6a477d7..75dc0a5bf 100644 --- a/verticapy/tests_new/plotting/base_test_files.py +++ b/verticapy/tests_new/plotting/base_test_files.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/conftest.py b/verticapy/tests_new/plotting/conftest.py index ceb403e38..878f56f26 100644 --- a/verticapy/tests_new/plotting/conftest.py +++ b/verticapy/tests_new/plotting/conftest.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/__init__.py b/verticapy/tests_new/plotting/highcharts/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/plotting/highcharts/__init__.py +++ b/verticapy/tests_new/plotting/highcharts/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/conftest.py b/verticapy/tests_new/plotting/highcharts/conftest.py index 5a74184c6..1629a15a2 100644 --- a/verticapy/tests_new/plotting/highcharts/conftest.py +++ b/verticapy/tests_new/plotting/highcharts/conftest.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/machine_learning/__init__.py b/verticapy/tests_new/plotting/highcharts/machine_learning/__init__.py index 62eb0aeaa..ffcd9fb20 100644 --- a/verticapy/tests_new/plotting/highcharts/machine_learning/__init__.py +++ b/verticapy/tests_new/plotting/highcharts/machine_learning/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_champion_challenger.py b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_champion_challenger.py index 8a423a72f..4f154d002 100644 --- a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_champion_challenger.py +++ b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_champion_challenger.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_elbow.py b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_elbow.py index 9dd9c07e9..14fc26408 100644 --- a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_elbow.py +++ b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_elbow.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_importance.py b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_importance.py index 0f0789b48..6d6e73aa6 100644 --- a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_importance.py +++ b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_importance.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_lof.py b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_lof.py index 9d675fac3..ea2191d2b 100644 --- a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_lof.py +++ b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_lof.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_logistic_reg.py b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_logistic_reg.py index b693a6a3a..c29af2dc3 100644 --- a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_logistic_reg.py +++ b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_logistic_reg.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_model_evaluation.py b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_model_evaluation.py index 426e4c752..27d183a57 100644 --- a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_model_evaluation.py +++ b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_model_evaluation.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_pca.py b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_pca.py index 78d47089b..5c55b8a94 100644 --- a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_pca.py +++ b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_pca.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_regression.py b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_regression.py index 92f7416b0..e9d964656 100644 --- a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_regression.py +++ b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_regression.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_regression_tree.py b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_regression_tree.py index 469e1b900..e1f6392d3 100644 --- a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_regression_tree.py +++ b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_regression_tree.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_stepwise.py b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_stepwise.py index dd4eccb85..6fcfdec1b 100644 --- a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_stepwise.py +++ b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_stepwise.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_svm.py b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_svm.py index 02f4a9915..6dfbcabb2 100644 --- a/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_svm.py +++ b/verticapy/tests_new/plotting/highcharts/machine_learning/test_highcharts_svm.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/test_highcharts_acf.py b/verticapy/tests_new/plotting/highcharts/test_highcharts_acf.py index d851bc717..13b76db4b 100644 --- a/verticapy/tests_new/plotting/highcharts/test_highcharts_acf.py +++ b/verticapy/tests_new/plotting/highcharts/test_highcharts_acf.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/test_highcharts_bar.py b/verticapy/tests_new/plotting/highcharts/test_highcharts_bar.py index 7addb84fc..b1f30d3b5 100644 --- a/verticapy/tests_new/plotting/highcharts/test_highcharts_bar.py +++ b/verticapy/tests_new/plotting/highcharts/test_highcharts_bar.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/test_highcharts_barh.py b/verticapy/tests_new/plotting/highcharts/test_highcharts_barh.py index 7d4d2f000..2999b80b6 100644 --- a/verticapy/tests_new/plotting/highcharts/test_highcharts_barh.py +++ b/verticapy/tests_new/plotting/highcharts/test_highcharts_barh.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/test_highcharts_base.py b/verticapy/tests_new/plotting/highcharts/test_highcharts_base.py index 62eb0aeaa..ffcd9fb20 100644 --- a/verticapy/tests_new/plotting/highcharts/test_highcharts_base.py +++ b/verticapy/tests_new/plotting/highcharts/test_highcharts_base.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/test_highcharts_boxplot.py b/verticapy/tests_new/plotting/highcharts/test_highcharts_boxplot.py index 616836460..727ce4e4c 100644 --- a/verticapy/tests_new/plotting/highcharts/test_highcharts_boxplot.py +++ b/verticapy/tests_new/plotting/highcharts/test_highcharts_boxplot.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/test_highcharts_candlestick.py b/verticapy/tests_new/plotting/highcharts/test_highcharts_candlestick.py index 303dc60eb..bb4b0325b 100644 --- a/verticapy/tests_new/plotting/highcharts/test_highcharts_candlestick.py +++ b/verticapy/tests_new/plotting/highcharts/test_highcharts_candlestick.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/test_highcharts_contour.py b/verticapy/tests_new/plotting/highcharts/test_highcharts_contour.py index 51f826ff3..5a9fa811a 100644 --- a/verticapy/tests_new/plotting/highcharts/test_highcharts_contour.py +++ b/verticapy/tests_new/plotting/highcharts/test_highcharts_contour.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/test_highcharts_density.py b/verticapy/tests_new/plotting/highcharts/test_highcharts_density.py index e5c483b0a..f24a4618e 100644 --- a/verticapy/tests_new/plotting/highcharts/test_highcharts_density.py +++ b/verticapy/tests_new/plotting/highcharts/test_highcharts_density.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/test_highcharts_heatmap.py b/verticapy/tests_new/plotting/highcharts/test_highcharts_heatmap.py index f69002cbc..2a92b3fd8 100644 --- a/verticapy/tests_new/plotting/highcharts/test_highcharts_heatmap.py +++ b/verticapy/tests_new/plotting/highcharts/test_highcharts_heatmap.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/test_highcharts_hist.py b/verticapy/tests_new/plotting/highcharts/test_highcharts_hist.py index 86e4560e1..37678165b 100644 --- a/verticapy/tests_new/plotting/highcharts/test_highcharts_hist.py +++ b/verticapy/tests_new/plotting/highcharts/test_highcharts_hist.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/test_highcharts_line.py b/verticapy/tests_new/plotting/highcharts/test_highcharts_line.py index 95e20fc22..ee5411764 100644 --- a/verticapy/tests_new/plotting/highcharts/test_highcharts_line.py +++ b/verticapy/tests_new/plotting/highcharts/test_highcharts_line.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/test_highcharts_outliers.py b/verticapy/tests_new/plotting/highcharts/test_highcharts_outliers.py index 7ddb686e1..65c3030b1 100644 --- a/verticapy/tests_new/plotting/highcharts/test_highcharts_outliers.py +++ b/verticapy/tests_new/plotting/highcharts/test_highcharts_outliers.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/test_highcharts_pie.py b/verticapy/tests_new/plotting/highcharts/test_highcharts_pie.py index 479e06fc9..6aeb5fd45 100644 --- a/verticapy/tests_new/plotting/highcharts/test_highcharts_pie.py +++ b/verticapy/tests_new/plotting/highcharts/test_highcharts_pie.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/test_highcharts_range.py b/verticapy/tests_new/plotting/highcharts/test_highcharts_range.py index 83ae99d1e..33ccb62cf 100644 --- a/verticapy/tests_new/plotting/highcharts/test_highcharts_range.py +++ b/verticapy/tests_new/plotting/highcharts/test_highcharts_range.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/test_highcharts_scatter.py b/verticapy/tests_new/plotting/highcharts/test_highcharts_scatter.py index 3b34a8213..731fd59a6 100644 --- a/verticapy/tests_new/plotting/highcharts/test_highcharts_scatter.py +++ b/verticapy/tests_new/plotting/highcharts/test_highcharts_scatter.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/highcharts/test_highcharts_spider.py b/verticapy/tests_new/plotting/highcharts/test_highcharts_spider.py index 25ac78af5..2742a582f 100644 --- a/verticapy/tests_new/plotting/highcharts/test_highcharts_spider.py +++ b/verticapy/tests_new/plotting/highcharts/test_highcharts_spider.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/__init__.py b/verticapy/tests_new/plotting/matplotlib/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/plotting/matplotlib/__init__.py +++ b/verticapy/tests_new/plotting/matplotlib/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/conftest.py b/verticapy/tests_new/plotting/matplotlib/conftest.py index 78a6e0706..7e6fdee53 100644 --- a/verticapy/tests_new/plotting/matplotlib/conftest.py +++ b/verticapy/tests_new/plotting/matplotlib/conftest.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/machine_learning/__init__.py b/verticapy/tests_new/plotting/matplotlib/machine_learning/__init__.py index 62eb0aeaa..ffcd9fb20 100644 --- a/verticapy/tests_new/plotting/matplotlib/machine_learning/__init__.py +++ b/verticapy/tests_new/plotting/matplotlib/machine_learning/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_champion_challenger.py b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_champion_challenger.py index 0f36fc9db..e9815f4d7 100644 --- a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_champion_challenger.py +++ b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_champion_challenger.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_elbow.py b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_elbow.py index 9dd9c07e9..14fc26408 100644 --- a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_elbow.py +++ b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_elbow.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_importance.py b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_importance.py index 151f7c43d..feca0a48e 100644 --- a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_importance.py +++ b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_importance.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_kmeans.py b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_kmeans.py index a82ea8a34..6df775f23 100644 --- a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_kmeans.py +++ b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_kmeans.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_lof.py b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_lof.py index 2caf5d619..8e5d928dd 100644 --- a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_lof.py +++ b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_lof.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_logistic_reg.py b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_logistic_reg.py index 983d8b97f..4dc252128 100644 --- a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_logistic_reg.py +++ b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_logistic_reg.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_model_evaluation.py b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_model_evaluation.py index e05e19f1b..2d70b2add 100644 --- a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_model_evaluation.py +++ b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_model_evaluation.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_pca.py b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_pca.py index f26640f0c..cc7a158e0 100644 --- a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_pca.py +++ b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_pca.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_regression.py b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_regression.py index 06a2db9c5..d46d93b2e 100644 --- a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_regression.py +++ b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_regression.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_regression_tree.py b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_regression_tree.py index 80075059a..2c659be7b 100644 --- a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_regression_tree.py +++ b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_regression_tree.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_stepwise.py b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_stepwise.py index fedeaec7d..0ff6ad53b 100644 --- a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_stepwise.py +++ b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_stepwise.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_svm.py b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_svm.py index 0c4454a33..d635490de 100644 --- a/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_svm.py +++ b/verticapy/tests_new/plotting/matplotlib/machine_learning/test_matplotlib_svm.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_acf.py b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_acf.py index b93c949d1..b25889309 100644 --- a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_acf.py +++ b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_acf.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_bar.py b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_bar.py index 27e24e257..e519c58aa 100644 --- a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_bar.py +++ b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_bar.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_barh.py b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_barh.py index 24007abfc..f4ef910f3 100644 --- a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_barh.py +++ b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_barh.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_base.py b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_base.py index 76e75739e..bcb386d2c 100644 --- a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_base.py +++ b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_base.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_boxplot.py b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_boxplot.py index 45b376dc3..e14e7a8f7 100644 --- a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_boxplot.py +++ b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_boxplot.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_candlestick.py b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_candlestick.py index e827dac4b..5f5abca2d 100644 --- a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_candlestick.py +++ b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_candlestick.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_contour.py b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_contour.py index 0af75c78a..847a63094 100644 --- a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_contour.py +++ b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_contour.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_density.py b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_density.py index ac52b33b7..3bd98930d 100644 --- a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_density.py +++ b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_density.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_heatmap.py b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_heatmap.py index 084a9cfa4..2b9fcde8a 100644 --- a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_heatmap.py +++ b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_heatmap.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_hexbin.py b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_hexbin.py index ea82cc58e..1151e2924 100644 --- a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_hexbin.py +++ b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_hexbin.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_hist.py b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_hist.py index 40e14289b..a81269ea8 100644 --- a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_hist.py +++ b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_hist.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_line.py b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_line.py index c8009a9fe..3f5ab7b67 100644 --- a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_line.py +++ b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_line.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_outliers.py b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_outliers.py index 5d1ad843c..53f389089 100644 --- a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_outliers.py +++ b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_outliers.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_pie.py b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_pie.py index 2904ba85d..88f324b84 100644 --- a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_pie.py +++ b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_pie.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_range.py b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_range.py index b1b111573..a42dcd70b 100644 --- a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_range.py +++ b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_range.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_scatter.py b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_scatter.py index fc5e6058a..dc31629c8 100644 --- a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_scatter.py +++ b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_scatter.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_spider.py b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_spider.py index ad901c354..c83d95647 100644 --- a/verticapy/tests_new/plotting/matplotlib/test_matplotlib_spider.py +++ b/verticapy/tests_new/plotting/matplotlib/test_matplotlib_spider.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/__init__.py b/verticapy/tests_new/plotting/plotly/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/plotting/plotly/__init__.py +++ b/verticapy/tests_new/plotting/plotly/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/conftest.py b/verticapy/tests_new/plotting/plotly/conftest.py index db9402407..7784916ea 100644 --- a/verticapy/tests_new/plotting/plotly/conftest.py +++ b/verticapy/tests_new/plotting/plotly/conftest.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/machine_learning/__init__.py b/verticapy/tests_new/plotting/plotly/machine_learning/__init__.py index 62eb0aeaa..ffcd9fb20 100644 --- a/verticapy/tests_new/plotting/plotly/machine_learning/__init__.py +++ b/verticapy/tests_new/plotting/plotly/machine_learning/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_champion_challenger.py b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_champion_challenger.py index a79de9672..d88ed3987 100644 --- a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_champion_challenger.py +++ b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_champion_challenger.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_elbow.py b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_elbow.py index ef74b5904..cf4dae15b 100644 --- a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_elbow.py +++ b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_elbow.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_importance.py b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_importance.py index afa57ee74..a7a772ba6 100644 --- a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_importance.py +++ b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_importance.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_kmeans.py b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_kmeans.py index 9fab420e5..408cf3bd5 100644 --- a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_kmeans.py +++ b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_kmeans.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_lof.py b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_lof.py index 80f0bfda9..84fb8469e 100644 --- a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_lof.py +++ b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_lof.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_logistic_reg.py b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_logistic_reg.py index 60fbc7222..4c587e93d 100644 --- a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_logistic_reg.py +++ b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_logistic_reg.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_model_evaluation.py b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_model_evaluation.py index 046b0358d..bae313db6 100644 --- a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_model_evaluation.py +++ b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_model_evaluation.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_pca.py b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_pca.py index 6e1178521..5a1f873af 100644 --- a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_pca.py +++ b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_pca.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_regression.py b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_regression.py index 371d481c4..ef8f8352b 100644 --- a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_regression.py +++ b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_regression.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_regression_tree.py b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_regression_tree.py index 6a066dbfb..18cbe9acd 100644 --- a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_regression_tree.py +++ b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_regression_tree.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_stepwise.py b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_stepwise.py index 16db4b008..6a91e213d 100644 --- a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_stepwise.py +++ b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_stepwise.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_svm.py b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_svm.py index 2c1065b96..6153ff011 100644 --- a/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_svm.py +++ b/verticapy/tests_new/plotting/plotly/machine_learning/test_plotly_svm.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/test_plotly_acf.py b/verticapy/tests_new/plotting/plotly/test_plotly_acf.py index 420d2733c..4e8f4af12 100644 --- a/verticapy/tests_new/plotting/plotly/test_plotly_acf.py +++ b/verticapy/tests_new/plotting/plotly/test_plotly_acf.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/test_plotly_bar.py b/verticapy/tests_new/plotting/plotly/test_plotly_bar.py index b2948267d..0698563d8 100644 --- a/verticapy/tests_new/plotting/plotly/test_plotly_bar.py +++ b/verticapy/tests_new/plotting/plotly/test_plotly_bar.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/test_plotly_barh.py b/verticapy/tests_new/plotting/plotly/test_plotly_barh.py index 14aa5eacf..1bdae8bc8 100644 --- a/verticapy/tests_new/plotting/plotly/test_plotly_barh.py +++ b/verticapy/tests_new/plotting/plotly/test_plotly_barh.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/test_plotly_base.py b/verticapy/tests_new/plotting/plotly/test_plotly_base.py index 00fe18d2d..391f0cf01 100644 --- a/verticapy/tests_new/plotting/plotly/test_plotly_base.py +++ b/verticapy/tests_new/plotting/plotly/test_plotly_base.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/test_plotly_boxplot.py b/verticapy/tests_new/plotting/plotly/test_plotly_boxplot.py index fcb9fc6ad..1cc014484 100644 --- a/verticapy/tests_new/plotting/plotly/test_plotly_boxplot.py +++ b/verticapy/tests_new/plotting/plotly/test_plotly_boxplot.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/test_plotly_candlestick.py b/verticapy/tests_new/plotting/plotly/test_plotly_candlestick.py index e827dac4b..5f5abca2d 100644 --- a/verticapy/tests_new/plotting/plotly/test_plotly_candlestick.py +++ b/verticapy/tests_new/plotting/plotly/test_plotly_candlestick.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/test_plotly_contour.py b/verticapy/tests_new/plotting/plotly/test_plotly_contour.py index 70fb445a5..3d007638a 100644 --- a/verticapy/tests_new/plotting/plotly/test_plotly_contour.py +++ b/verticapy/tests_new/plotting/plotly/test_plotly_contour.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/test_plotly_density.py b/verticapy/tests_new/plotting/plotly/test_plotly_density.py index e96d4cdc1..d98adb116 100644 --- a/verticapy/tests_new/plotting/plotly/test_plotly_density.py +++ b/verticapy/tests_new/plotting/plotly/test_plotly_density.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/test_plotly_heatmap.py b/verticapy/tests_new/plotting/plotly/test_plotly_heatmap.py index 92f7689b2..f4a92930c 100644 --- a/verticapy/tests_new/plotting/plotly/test_plotly_heatmap.py +++ b/verticapy/tests_new/plotting/plotly/test_plotly_heatmap.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/test_plotly_hist.py b/verticapy/tests_new/plotting/plotly/test_plotly_hist.py index bffcf580f..5e22a8375 100644 --- a/verticapy/tests_new/plotting/plotly/test_plotly_hist.py +++ b/verticapy/tests_new/plotting/plotly/test_plotly_hist.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/test_plotly_line.py b/verticapy/tests_new/plotting/plotly/test_plotly_line.py index 51828c509..1ce37322d 100644 --- a/verticapy/tests_new/plotting/plotly/test_plotly_line.py +++ b/verticapy/tests_new/plotting/plotly/test_plotly_line.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/test_plotly_outliers.py b/verticapy/tests_new/plotting/plotly/test_plotly_outliers.py index e3c1ee7ee..15f865023 100644 --- a/verticapy/tests_new/plotting/plotly/test_plotly_outliers.py +++ b/verticapy/tests_new/plotting/plotly/test_plotly_outliers.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/test_plotly_pie.py b/verticapy/tests_new/plotting/plotly/test_plotly_pie.py index c9bdee2e1..d6dc56308 100644 --- a/verticapy/tests_new/plotting/plotly/test_plotly_pie.py +++ b/verticapy/tests_new/plotting/plotly/test_plotly_pie.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/test_plotly_range.py b/verticapy/tests_new/plotting/plotly/test_plotly_range.py index 6587b452d..bb18d5438 100644 --- a/verticapy/tests_new/plotting/plotly/test_plotly_range.py +++ b/verticapy/tests_new/plotting/plotly/test_plotly_range.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/test_plotly_scatter.py b/verticapy/tests_new/plotting/plotly/test_plotly_scatter.py index b7dfc165b..e51aea470 100644 --- a/verticapy/tests_new/plotting/plotly/test_plotly_scatter.py +++ b/verticapy/tests_new/plotting/plotly/test_plotly_scatter.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/plotting/plotly/test_plotly_spider.py b/verticapy/tests_new/plotting/plotly/test_plotly_spider.py index 5962e9d62..29fe407b5 100644 --- a/verticapy/tests_new/plotting/plotly/test_plotly_spider.py +++ b/verticapy/tests_new/plotting/plotly/test_plotly_spider.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/sdk/__init__.py b/verticapy/tests_new/sdk/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/sdk/__init__.py +++ b/verticapy/tests_new/sdk/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/sql/__init__.py b/verticapy/tests_new/sql/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/sql/__init__.py +++ b/verticapy/tests_new/sql/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/sql/functions/__init__.py b/verticapy/tests_new/sql/functions/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/sql/functions/__init__.py +++ b/verticapy/tests_new/sql/functions/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/sql/geo/__init__.py b/verticapy/tests_new/sql/geo/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/sql/geo/__init__.py +++ b/verticapy/tests_new/sql/geo/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/tests_new/utils/__init__.py b/verticapy/tests_new/utils/__init__.py index 62eb0aeaa..ffcd9fb20 100755 --- a/verticapy/tests_new/utils/__init__.py +++ b/verticapy/tests_new/utils/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. diff --git a/verticapy/udf/__init__.py b/verticapy/udf/__init__.py index 2c5543d98..b81c55f6f 100755 --- a/verticapy/udf/__init__.py +++ b/verticapy/udf/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.udf' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.sdk.vertica.udf' instead " "to ensure compatibility with upcoming versions." ) diff --git a/verticapy/utilities/__init__.py b/verticapy/utilities/__init__.py index 7fb28c85c..428a474b7 100755 --- a/verticapy/utilities/__init__.py +++ b/verticapy/utilities/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.utilities' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy' instead to ensure compatibility " "with upcoming versions." ) diff --git a/verticapy/vdataframe/__init__.py b/verticapy/vdataframe/__init__.py index a001a9736..5ee13b4e2 100755 --- a/verticapy/vdataframe/__init__.py +++ b/verticapy/vdataframe/__init__.py @@ -1,5 +1,5 @@ """ -Copyright (c) 2018-2023 Open Text or one of its +Copyright (c) 2018-2024 Open Text or one of its affiliates. Licensed under the Apache License, Version 2.0 (the "License"); You may not use this file except in compliance with the License. @@ -18,7 +18,7 @@ warning_message = ( "Importing from 'verticapy.vdataframe' is deprecated, " - "and it will no longer be possible in the next release. " + "and it will no longer be possible in the next minor release. " "Please use 'verticapy.core' instead " "to ensure compatibility with upcoming versions." )