diff --git a/docs/fastexcel.html b/docs/fastexcel.html index 5e79f0e..8317b17 100644 --- a/docs/fastexcel.html +++ b/docs/fastexcel.html @@ -166,264 +166,265 @@
242def read_excel(path: Path | str) -> ExcelReader: -243 """Opens and loads an excel file. -244 -245 :param path: The path to the file -246 """ -247 return ExcelReader(_read_excel(expanduser(path))) +@@ -465,7 +468,7 @@241def read_excel(source: Path | str | bytes) -> ExcelReader: +242 """Opens and loads an excel file. +243 +244 :param source: The path to a file or its content as bytes +245 """ +246 if isinstance(source, (str, Path)): +247 source = expanduser(source) +248 return ExcelReader(_read_excel(source))
Parameters
-
- path: The path to the file
+- source: The path to a file or its content as bytes
96class ExcelReader: - 97 """A class representing an open Excel file and allowing to read its sheets""" - 98 - 99 def __init__(self, reader: _ExcelReader) -> None: -100 self._reader = reader -101 -102 @property -103 def sheet_names(self) -> list[str]: -104 """The list of sheet names""" -105 return self._reader.sheet_names -106 -107 def load_sheet_by_name( -108 self, -109 name: str, -110 *, -111 header_row: int | None = 0, -112 column_names: list[str] | None = None, -113 skip_rows: int = 0, -114 n_rows: int | None = None, -115 schema_sample_rows: int | None = 1_000, -116 use_columns: list[str] | list[int] | str | None = None, -117 ) -> ExcelSheet: -118 """Loads a sheet by name. -119 -120 :param name: The name of the sheet to load. -121 :param header_row: The index of the row containing the column labels, default index is 0. -122 If `None`, the sheet does not have any column labels. -123 :param column_names: Overrides headers found in the document. -124 If `column_names` is used, `header_row` will be ignored. -125 :param n_rows: Specifies how many rows should be loaded. -126 If `None`, all rows are loaded -127 :param skip_rows: Specifies how many rows should be skipped after the header. -128 If `header_row` is `None`, it skips the number of rows from the -129 start of the sheet. -130 :param schema_sample_rows: Specifies how many rows should be used to determine -131 the dtype of a column. -132 If `None`, all rows will be used. -133 :param use_columns: Specifies the columns to use. Can either be: -134 - `None` to select all columns -135 - a list of strings, the column names -136 - a list of ints, the column indices (starting at 0) -137 - a string, a comma separated list of Excel column letters and column -138 ranges (e.g. `“A:E”` or `“A,C,E:F”`, which would result in -139 `A,B,C,D,E` and `A,C,E,F`) -140 """ -141 return ExcelSheet( -142 self._reader.load_sheet_by_name( -143 name, -144 header_row=header_row, -145 column_names=column_names, -146 skip_rows=skip_rows, -147 n_rows=n_rows, -148 schema_sample_rows=schema_sample_rows, -149 use_columns=use_columns, -150 ) -151 ) -152 -153 def load_sheet_by_idx( -154 self, -155 idx: int, -156 *, -157 header_row: int | None = 0, -158 column_names: list[str] | None = None, -159 skip_rows: int = 0, -160 n_rows: int | None = None, -161 schema_sample_rows: int | None = 1_000, -162 use_columns: list[str] | list[int] | str | None = None, -163 ) -> ExcelSheet: -164 """Loads a sheet by index. -165 -166 :param idx: The index (starting at 0) of the sheet to load. -167 :param header_row: The index of the row containing the column labels, default index is 0. -168 If `None`, the sheet does not have any column labels. -169 :param column_names: Overrides headers found in the document. -170 If `column_names` is used, `header_row` will be ignored. -171 :param n_rows: Specifies how many rows should be loaded. -172 If `None`, all rows are loaded -173 :param skip_rows: Specifies how many rows should be skipped after the header. -174 If `header_row` is `None`, it skips the number of rows from the -175 start of the sheet. -176 :param schema_sample_rows: Specifies how many rows should be used to determine -177 the dtype of a column. -178 If `None`, all rows will be used. -179 :param use_columns: Specifies the columns to use. Can either be: -180 - `None` to select all columns -181 - a list of strings, the column names -182 - a list of ints, the column indices (starting at 0) -183 - a string, a comma separated list of Excel column letters and column -184 ranges (e.g. `“A:E”` or `“A,C,E:F”`, which would result in -185 `A,B,C,D,E` and `A,C,E,F`) -186 """ -187 if idx < 0: -188 raise ValueError(f"Expected idx to be > 0, got {idx}") -189 return ExcelSheet( -190 self._reader.load_sheet_by_idx( -191 idx, -192 header_row=header_row, -193 column_names=column_names, -194 skip_rows=skip_rows, -195 n_rows=n_rows, -196 schema_sample_rows=schema_sample_rows, -197 use_columns=use_columns, -198 ) -199 ) -200 -201 def load_sheet( -202 self, -203 idx_or_name: int | str, -204 *, -205 header_row: int | None = 0, -206 column_names: list[str] | None = None, -207 skip_rows: int = 0, -208 n_rows: int | None = None, -209 schema_sample_rows: int | None = 1_000, -210 use_columns: list[str] | list[int] | str | None = None, -211 ) -> ExcelSheet: -212 """Loads a sheet by name if a string is passed or by index if an integer is passed. -213 -214 See `load_sheet_by_idx` and `load_sheet_by_name` for parameter documentation. -215 """ -216 return ( -217 self.load_sheet_by_idx( -218 idx_or_name, -219 header_row=header_row, -220 column_names=column_names, -221 skip_rows=skip_rows, -222 n_rows=n_rows, -223 schema_sample_rows=schema_sample_rows, -224 use_columns=use_columns, -225 ) -226 if isinstance(idx_or_name, int) -227 else self.load_sheet_by_name( -228 idx_or_name, -229 header_row=header_row, -230 column_names=column_names, -231 skip_rows=skip_rows, -232 n_rows=n_rows, -233 schema_sample_rows=schema_sample_rows, -234 use_columns=use_columns, -235 ) -236 ) -237 -238 def __repr__(self) -> str: -239 return self._reader.__repr__() +@@ -643,8 +646,8 @@95class ExcelReader: + 96 """A class representing an open Excel file and allowing to read its sheets""" + 97 + 98 def __init__(self, reader: _ExcelReader) -> None: + 99 self._reader = reader +100 +101 @property +102 def sheet_names(self) -> list[str]: +103 """The list of sheet names""" +104 return self._reader.sheet_names +105 +106 def load_sheet_by_name( +107 self, +108 name: str, +109 *, +110 header_row: int | None = 0, +111 column_names: list[str] | None = None, +112 skip_rows: int = 0, +113 n_rows: int | None = None, +114 schema_sample_rows: int | None = 1_000, +115 use_columns: list[str] | list[int] | str | None = None, +116 ) -> ExcelSheet: +117 """Loads a sheet by name. +118 +119 :param name: The name of the sheet to load. +120 :param header_row: The index of the row containing the column labels, default index is 0. +121 If `None`, the sheet does not have any column labels. +122 :param column_names: Overrides headers found in the document. +123 If `column_names` is used, `header_row` will be ignored. +124 :param n_rows: Specifies how many rows should be loaded. +125 If `None`, all rows are loaded +126 :param skip_rows: Specifies how many rows should be skipped after the header. +127 If `header_row` is `None`, it skips the number of rows from the +128 start of the sheet. +129 :param schema_sample_rows: Specifies how many rows should be used to determine +130 the dtype of a column. +131 If `None`, all rows will be used. +132 :param use_columns: Specifies the columns to use. Can either be: +133 - `None` to select all columns +134 - a list of strings, the column names +135 - a list of ints, the column indices (starting at 0) +136 - a string, a comma separated list of Excel column letters and column +137 ranges (e.g. `“A:E”` or `“A,C,E:F”`, which would result in +138 `A,B,C,D,E` and `A,C,E,F`) +139 """ +140 return ExcelSheet( +141 self._reader.load_sheet_by_name( +142 name, +143 header_row=header_row, +144 column_names=column_names, +145 skip_rows=skip_rows, +146 n_rows=n_rows, +147 schema_sample_rows=schema_sample_rows, +148 use_columns=use_columns, +149 ) +150 ) +151 +152 def load_sheet_by_idx( +153 self, +154 idx: int, +155 *, +156 header_row: int | None = 0, +157 column_names: list[str] | None = None, +158 skip_rows: int = 0, +159 n_rows: int | None = None, +160 schema_sample_rows: int | None = 1_000, +161 use_columns: list[str] | list[int] | str | None = None, +162 ) -> ExcelSheet: +163 """Loads a sheet by index. +164 +165 :param idx: The index (starting at 0) of the sheet to load. +166 :param header_row: The index of the row containing the column labels, default index is 0. +167 If `None`, the sheet does not have any column labels. +168 :param column_names: Overrides headers found in the document. +169 If `column_names` is used, `header_row` will be ignored. +170 :param n_rows: Specifies how many rows should be loaded. +171 If `None`, all rows are loaded +172 :param skip_rows: Specifies how many rows should be skipped after the header. +173 If `header_row` is `None`, it skips the number of rows from the +174 start of the sheet. +175 :param schema_sample_rows: Specifies how many rows should be used to determine +176 the dtype of a column. +177 If `None`, all rows will be used. +178 :param use_columns: Specifies the columns to use. Can either be: +179 - `None` to select all columns +180 - a list of strings, the column names +181 - a list of ints, the column indices (starting at 0) +182 - a string, a comma separated list of Excel column letters and column +183 ranges (e.g. `“A:E”` or `“A,C,E:F”`, which would result in +184 `A,B,C,D,E` and `A,C,E,F`) +185 """ +186 if idx < 0: +187 raise ValueError(f"Expected idx to be > 0, got {idx}") +188 return ExcelSheet( +189 self._reader.load_sheet_by_idx( +190 idx, +191 header_row=header_row, +192 column_names=column_names, +193 skip_rows=skip_rows, +194 n_rows=n_rows, +195 schema_sample_rows=schema_sample_rows, +196 use_columns=use_columns, +197 ) +198 ) +199 +200 def load_sheet( +201 self, +202 idx_or_name: int | str, +203 *, +204 header_row: int | None = 0, +205 column_names: list[str] | None = None, +206 skip_rows: int = 0, +207 n_rows: int | None = None, +208 schema_sample_rows: int | None = 1_000, +209 use_columns: list[str] | list[int] | str | None = None, +210 ) -> ExcelSheet: +211 """Loads a sheet by name if a string is passed or by index if an integer is passed. +212 +213 See `load_sheet_by_idx` and `load_sheet_by_name` for parameter documentation. +214 """ +215 return ( +216 self.load_sheet_by_idx( +217 idx_or_name, +218 header_row=header_row, +219 column_names=column_names, +220 skip_rows=skip_rows, +221 n_rows=n_rows, +222 schema_sample_rows=schema_sample_rows, +223 use_columns=use_columns, +224 ) +225 if isinstance(idx_or_name, int) +226 else self.load_sheet_by_name( +227 idx_or_name, +228 header_row=header_row, +229 column_names=column_names, +230 skip_rows=skip_rows, +231 n_rows=n_rows, +232 schema_sample_rows=schema_sample_rows, +233 use_columns=use_columns, +234 ) +235 ) +236 +237 def __repr__(self) -> str: +238 return self._reader.__repr__()Parameters
99 def __init__(self, reader: _ExcelReader) -> None: -100 self._reader = reader + @@ -660,10 +663,10 @@Parameters
102 @property -103 def sheet_names(self) -> list[str]: -104 """The list of sheet names""" -105 return self._reader.sheet_names +@@ -683,51 +686,51 @@101 @property +102 def sheet_names(self) -> list[str]: +103 """The list of sheet names""" +104 return self._reader.sheet_namesParameters
107 def load_sheet_by_name( -108 self, -109 name: str, -110 *, -111 header_row: int | None = 0, -112 column_names: list[str] | None = None, -113 skip_rows: int = 0, -114 n_rows: int | None = None, -115 schema_sample_rows: int | None = 1_000, -116 use_columns: list[str] | list[int] | str | None = None, -117 ) -> ExcelSheet: -118 """Loads a sheet by name. -119 -120 :param name: The name of the sheet to load. -121 :param header_row: The index of the row containing the column labels, default index is 0. -122 If `None`, the sheet does not have any column labels. -123 :param column_names: Overrides headers found in the document. -124 If `column_names` is used, `header_row` will be ignored. -125 :param n_rows: Specifies how many rows should be loaded. -126 If `None`, all rows are loaded -127 :param skip_rows: Specifies how many rows should be skipped after the header. -128 If `header_row` is `None`, it skips the number of rows from the -129 start of the sheet. -130 :param schema_sample_rows: Specifies how many rows should be used to determine -131 the dtype of a column. -132 If `None`, all rows will be used. -133 :param use_columns: Specifies the columns to use. Can either be: -134 - `None` to select all columns -135 - a list of strings, the column names -136 - a list of ints, the column indices (starting at 0) -137 - a string, a comma separated list of Excel column letters and column -138 ranges (e.g. `“A:E”` or `“A,C,E:F”`, which would result in -139 `A,B,C,D,E` and `A,C,E,F`) -140 """ -141 return ExcelSheet( -142 self._reader.load_sheet_by_name( -143 name, -144 header_row=header_row, -145 column_names=column_names, -146 skip_rows=skip_rows, -147 n_rows=n_rows, -148 schema_sample_rows=schema_sample_rows, -149 use_columns=use_columns, -150 ) -151 ) +@@ -774,53 +777,53 @@106 def load_sheet_by_name( +107 self, +108 name: str, +109 *, +110 header_row: int | None = 0, +111 column_names: list[str] | None = None, +112 skip_rows: int = 0, +113 n_rows: int | None = None, +114 schema_sample_rows: int | None = 1_000, +115 use_columns: list[str] | list[int] | str | None = None, +116 ) -> ExcelSheet: +117 """Loads a sheet by name. +118 +119 :param name: The name of the sheet to load. +120 :param header_row: The index of the row containing the column labels, default index is 0. +121 If `None`, the sheet does not have any column labels. +122 :param column_names: Overrides headers found in the document. +123 If `column_names` is used, `header_row` will be ignored. +124 :param n_rows: Specifies how many rows should be loaded. +125 If `None`, all rows are loaded +126 :param skip_rows: Specifies how many rows should be skipped after the header. +127 If `header_row` is `None`, it skips the number of rows from the +128 start of the sheet. +129 :param schema_sample_rows: Specifies how many rows should be used to determine +130 the dtype of a column. +131 If `None`, all rows will be used. +132 :param use_columns: Specifies the columns to use. Can either be: +133 - `None` to select all columns +134 - a list of strings, the column names +135 - a list of ints, the column indices (starting at 0) +136 - a string, a comma separated list of Excel column letters and column +137 ranges (e.g. `“A:E”` or `“A,C,E:F”`, which would result in +138 `A,B,C,D,E` and `A,C,E,F`) +139 """ +140 return ExcelSheet( +141 self._reader.load_sheet_by_name( +142 name, +143 header_row=header_row, +144 column_names=column_names, +145 skip_rows=skip_rows, +146 n_rows=n_rows, +147 schema_sample_rows=schema_sample_rows, +148 use_columns=use_columns, +149 ) +150 )Parameters
153 def load_sheet_by_idx( -154 self, -155 idx: int, -156 *, -157 header_row: int | None = 0, -158 column_names: list[str] | None = None, -159 skip_rows: int = 0, -160 n_rows: int | None = None, -161 schema_sample_rows: int | None = 1_000, -162 use_columns: list[str] | list[int] | str | None = None, -163 ) -> ExcelSheet: -164 """Loads a sheet by index. -165 -166 :param idx: The index (starting at 0) of the sheet to load. -167 :param header_row: The index of the row containing the column labels, default index is 0. -168 If `None`, the sheet does not have any column labels. -169 :param column_names: Overrides headers found in the document. -170 If `column_names` is used, `header_row` will be ignored. -171 :param n_rows: Specifies how many rows should be loaded. -172 If `None`, all rows are loaded -173 :param skip_rows: Specifies how many rows should be skipped after the header. -174 If `header_row` is `None`, it skips the number of rows from the -175 start of the sheet. -176 :param schema_sample_rows: Specifies how many rows should be used to determine -177 the dtype of a column. -178 If `None`, all rows will be used. -179 :param use_columns: Specifies the columns to use. Can either be: -180 - `None` to select all columns -181 - a list of strings, the column names -182 - a list of ints, the column indices (starting at 0) -183 - a string, a comma separated list of Excel column letters and column -184 ranges (e.g. `“A:E”` or `“A,C,E:F”`, which would result in -185 `A,B,C,D,E` and `A,C,E,F`) -186 """ -187 if idx < 0: -188 raise ValueError(f"Expected idx to be > 0, got {idx}") -189 return ExcelSheet( -190 self._reader.load_sheet_by_idx( -191 idx, -192 header_row=header_row, -193 column_names=column_names, -194 skip_rows=skip_rows, -195 n_rows=n_rows, -196 schema_sample_rows=schema_sample_rows, -197 use_columns=use_columns, -198 ) -199 ) +@@ -867,42 +870,42 @@152 def load_sheet_by_idx( +153 self, +154 idx: int, +155 *, +156 header_row: int | None = 0, +157 column_names: list[str] | None = None, +158 skip_rows: int = 0, +159 n_rows: int | None = None, +160 schema_sample_rows: int | None = 1_000, +161 use_columns: list[str] | list[int] | str | None = None, +162 ) -> ExcelSheet: +163 """Loads a sheet by index. +164 +165 :param idx: The index (starting at 0) of the sheet to load. +166 :param header_row: The index of the row containing the column labels, default index is 0. +167 If `None`, the sheet does not have any column labels. +168 :param column_names: Overrides headers found in the document. +169 If `column_names` is used, `header_row` will be ignored. +170 :param n_rows: Specifies how many rows should be loaded. +171 If `None`, all rows are loaded +172 :param skip_rows: Specifies how many rows should be skipped after the header. +173 If `header_row` is `None`, it skips the number of rows from the +174 start of the sheet. +175 :param schema_sample_rows: Specifies how many rows should be used to determine +176 the dtype of a column. +177 If `None`, all rows will be used. +178 :param use_columns: Specifies the columns to use. Can either be: +179 - `None` to select all columns +180 - a list of strings, the column names +181 - a list of ints, the column indices (starting at 0) +182 - a string, a comma separated list of Excel column letters and column +183 ranges (e.g. `“A:E”` or `“A,C,E:F”`, which would result in +184 `A,B,C,D,E` and `A,C,E,F`) +185 """ +186 if idx < 0: +187 raise ValueError(f"Expected idx to be > 0, got {idx}") +188 return ExcelSheet( +189 self._reader.load_sheet_by_idx( +190 idx, +191 header_row=header_row, +192 column_names=column_names, +193 skip_rows=skip_rows, +194 n_rows=n_rows, +195 schema_sample_rows=schema_sample_rows, +196 use_columns=use_columns, +197 ) +198 )Parameters
201 def load_sheet( -202 self, -203 idx_or_name: int | str, -204 *, -205 header_row: int | None = 0, -206 column_names: list[str] | None = None, -207 skip_rows: int = 0, -208 n_rows: int | None = None, -209 schema_sample_rows: int | None = 1_000, -210 use_columns: list[str] | list[int] | str | None = None, -211 ) -> ExcelSheet: -212 """Loads a sheet by name if a string is passed or by index if an integer is passed. -213 -214 See `load_sheet_by_idx` and `load_sheet_by_name` for parameter documentation. -215 """ -216 return ( -217 self.load_sheet_by_idx( -218 idx_or_name, -219 header_row=header_row, -220 column_names=column_names, -221 skip_rows=skip_rows, -222 n_rows=n_rows, -223 schema_sample_rows=schema_sample_rows, -224 use_columns=use_columns, -225 ) -226 if isinstance(idx_or_name, int) -227 else self.load_sheet_by_name( -228 idx_or_name, -229 header_row=header_row, -230 column_names=column_names, -231 skip_rows=skip_rows, -232 n_rows=n_rows, -233 schema_sample_rows=schema_sample_rows, -234 use_columns=use_columns, -235 ) -236 ) +@@ -925,67 +928,67 @@200 def load_sheet( +201 self, +202 idx_or_name: int | str, +203 *, +204 header_row: int | None = 0, +205 column_names: list[str] | None = None, +206 skip_rows: int = 0, +207 n_rows: int | None = None, +208 schema_sample_rows: int | None = 1_000, +209 use_columns: list[str] | list[int] | str | None = None, +210 ) -> ExcelSheet: +211 """Loads a sheet by name if a string is passed or by index if an integer is passed. +212 +213 See `load_sheet_by_idx` and `load_sheet_by_name` for parameter documentation. +214 """ +215 return ( +216 self.load_sheet_by_idx( +217 idx_or_name, +218 header_row=header_row, +219 column_names=column_names, +220 skip_rows=skip_rows, +221 n_rows=n_rows, +222 schema_sample_rows=schema_sample_rows, +223 use_columns=use_columns, +224 ) +225 if isinstance(idx_or_name, int) +226 else self.load_sheet_by_name( +227 idx_or_name, +228 header_row=header_row, +229 column_names=column_names, +230 skip_rows=skip_rows, +231 n_rows=n_rows, +232 schema_sample_rows=schema_sample_rows, +233 use_columns=use_columns, +234 ) +235 )Parameters
33class ExcelSheet: -34 """A class representing a single sheet in an Excel File""" -35 -36 def __init__(self, sheet: _ExcelSheet) -> None: -37 self._sheet = sheet -38 -39 @property -40 def name(self) -> str: -41 """The name of the sheet""" -42 return self._sheet.name -43 -44 @property -45 def width(self) -> int: -46 """The sheet's width""" -47 return self._sheet.width -48 -49 @property -50 def height(self) -> int: -51 """The sheet's height, with `skip_rows` and `nrows` applied""" -52 return self._sheet.height -53 -54 @property -55 def total_height(self) -> int: -56 """The sheet's total height""" -57 return self._sheet.total_height -58 -59 @property -60 def selected_columns(self) -> list[str] | list[int] | None: -61 """The sheet's selected columns""" -62 return self._sheet.selected_columns -63 -64 @property -65 def available_columns(self) -> list[str]: -66 """The columns available for the given sheet""" -67 return self._sheet.available_columns -68 -69 def to_arrow(self) -> pa.RecordBatch: -70 """Converts the sheet to a pyarrow `RecordBatch`""" -71 return self._sheet.to_arrow() -72 -73 def to_pandas(self) -> "pd.DataFrame": -74 """Converts the sheet to a Pandas `DataFrame`. -75 -76 Requires the `pandas` extra to be installed. -77 """ -78 # We know for sure that the sheet will yield exactly one RecordBatch -79 return self.to_arrow().to_pandas() -80 -81 def to_polars(self) -> "pl.DataFrame": -82 """Converts the sheet to a Polars `DataFrame`. -83 -84 Requires the `polars` extra to be installed. -85 """ -86 import polars as pl -87 -88 df = pl.from_arrow(data=self.to_arrow()) -89 assert isinstance(df, pl.DataFrame) -90 return df -91 -92 def __repr__(self) -> str: -93 return self._sheet.__repr__() +@@ -1003,8 +1006,8 @@32class ExcelSheet: +33 """A class representing a single sheet in an Excel File""" +34 +35 def __init__(self, sheet: _ExcelSheet) -> None: +36 self._sheet = sheet +37 +38 @property +39 def name(self) -> str: +40 """The name of the sheet""" +41 return self._sheet.name +42 +43 @property +44 def width(self) -> int: +45 """The sheet's width""" +46 return self._sheet.width +47 +48 @property +49 def height(self) -> int: +50 """The sheet's height, with `skip_rows` and `nrows` applied""" +51 return self._sheet.height +52 +53 @property +54 def total_height(self) -> int: +55 """The sheet's total height""" +56 return self._sheet.total_height +57 +58 @property +59 def selected_columns(self) -> list[str] | list[int] | None: +60 """The sheet's selected columns""" +61 return self._sheet.selected_columns +62 +63 @property +64 def available_columns(self) -> list[str]: +65 """The columns available for the given sheet""" +66 return self._sheet.available_columns +67 +68 def to_arrow(self) -> pa.RecordBatch: +69 """Converts the sheet to a pyarrow `RecordBatch`""" +70 return self._sheet.to_arrow() +71 +72 def to_pandas(self) -> "pd.DataFrame": +73 """Converts the sheet to a Pandas `DataFrame`. +74 +75 Requires the `pandas` extra to be installed. +76 """ +77 # We know for sure that the sheet will yield exactly one RecordBatch +78 return self.to_arrow().to_pandas() +79 +80 def to_polars(self) -> "pl.DataFrame": +81 """Converts the sheet to a Polars `DataFrame`. +82 +83 Requires the `polars` extra to be installed. +84 """ +85 import polars as pl +86 +87 df = pl.from_arrow(data=self.to_arrow()) +88 assert isinstance(df, pl.DataFrame) +89 return df +90 +91 def __repr__(self) -> str: +92 return self._sheet.__repr__()Parameters
36 def __init__(self, sheet: _ExcelSheet) -> None: -37 self._sheet = sheet + @@ -1020,10 +1023,10 @@Parameters
39 @property -40 def name(self) -> str: -41 """The name of the sheet""" -42 return self._sheet.name + @@ -1041,10 +1044,10 @@Parameters
44 @property -45 def width(self) -> int: -46 """The sheet's width""" -47 return self._sheet.width + @@ -1062,10 +1065,10 @@Parameters
49 @property -50 def height(self) -> int: -51 """The sheet's height, with `skip_rows` and `nrows` applied""" -52 return self._sheet.height +@@ -1083,10 +1086,10 @@48 @property +49 def height(self) -> int: +50 """The sheet's height, with `skip_rows` and `nrows` applied""" +51 return self._sheet.heightParameters
54 @property -55 def total_height(self) -> int: -56 """The sheet's total height""" -57 return self._sheet.total_height +@@ -1104,10 +1107,10 @@53 @property +54 def total_height(self) -> int: +55 """The sheet's total height""" +56 return self._sheet.total_heightParameters
59 @property -60 def selected_columns(self) -> list[str] | list[int] | None: -61 """The sheet's selected columns""" -62 return self._sheet.selected_columns +@@ -1125,10 +1128,10 @@58 @property +59 def selected_columns(self) -> list[str] | list[int] | None: +60 """The sheet's selected columns""" +61 return self._sheet.selected_columnsParameters
64 @property -65 def available_columns(self) -> list[str]: -66 """The columns available for the given sheet""" -67 return self._sheet.available_columns +@@ -1148,9 +1151,9 @@63 @property +64 def available_columns(self) -> list[str]: +65 """The columns available for the given sheet""" +66 return self._sheet.available_columnsParameters
69 def to_arrow(self) -> pa.RecordBatch: -70 """Converts the sheet to a pyarrow `RecordBatch`""" -71 return self._sheet.to_arrow() +@@ -1170,13 +1173,13 @@68 def to_arrow(self) -> pa.RecordBatch: +69 """Converts the sheet to a pyarrow `RecordBatch`""" +70 return self._sheet.to_arrow()Parameters
73 def to_pandas(self) -> "pd.DataFrame": -74 """Converts the sheet to a Pandas `DataFrame`. -75 -76 Requires the `pandas` extra to be installed. -77 """ -78 # We know for sure that the sheet will yield exactly one RecordBatch -79 return self.to_arrow().to_pandas() +@@ -1198,16 +1201,16 @@72 def to_pandas(self) -> "pd.DataFrame": +73 """Converts the sheet to a Pandas `DataFrame`. +74 +75 Requires the `pandas` extra to be installed. +76 """ +77 # We know for sure that the sheet will yield exactly one RecordBatch +78 return self.to_arrow().to_pandas()Parameters
81 def to_polars(self) -> "pl.DataFrame": -82 """Converts the sheet to a Polars `DataFrame`. -83 -84 Requires the `polars` extra to be installed. -85 """ -86 import polars as pl -87 -88 df = pl.from_arrow(data=self.to_arrow()) -89 assert isinstance(df, pl.DataFrame) -90 return df +diff --git a/docs/search.js b/docs/search.js index 74fc0fb..3c57017 100644 --- a/docs/search.js +++ b/docs/search.js @@ -1,6 +1,6 @@ window.pdocSearch = (function(){ /** elasticlunr - http://weixsong.github.io * Copyright (C) 2017 Oliver Nightingale * Copyright (C) 2017 Wei Song * MIT Licensed */!function(){function e(e){if(null===e||"object"!=typeof e)return e;var t=e.constructor();for(var n in e)e.hasOwnProperty(n)&&(t[n]=e[n]);return t}var t=function(e){var n=new t.Index;return n.pipeline.add(t.trimmer,t.stopWordFilter,t.stemmer),e&&e.call(n,n),n};t.version="0.9.5",lunr=t,t.utils={},t.utils.warn=function(e){return function(t){e.console&&console.warn&&console.warn(t)}}(this),t.utils.toString=function(e){return void 0===e||null===e?"":e.toString()},t.EventEmitter=function(){this.events={}},t.EventEmitter.prototype.addListener=function(){var e=Array.prototype.slice.call(arguments),t=e.pop(),n=e;if("function"!=typeof t)throw new TypeError("last argument must be a function");n.forEach(function(e){this.hasHandler(e)||(this.events[e]=[]),this.events[e].push(t)},this)},t.EventEmitter.prototype.removeListener=function(e,t){if(this.hasHandler(e)){var n=this.events[e].indexOf(t);-1!==n&&(this.events[e].splice(n,1),0==this.events[e].length&&delete this.events[e])}},t.EventEmitter.prototype.emit=function(e){if(this.hasHandler(e)){var t=Array.prototype.slice.call(arguments,1);this.events[e].forEach(function(e){e.apply(void 0,t)},this)}},t.EventEmitter.prototype.hasHandler=function(e){return e in this.events},t.tokenizer=function(e){if(!arguments.length||null===e||void 0===e)return[];if(Array.isArray(e)){var n=e.filter(function(e){return null===e||void 0===e?!1:!0});n=n.map(function(e){return t.utils.toString(e).toLowerCase()});var i=[];return n.forEach(function(e){var n=e.split(t.tokenizer.seperator);i=i.concat(n)},this),i}return e.toString().trim().toLowerCase().split(t.tokenizer.seperator)},t.tokenizer.defaultSeperator=/[\s\-]+/,t.tokenizer.seperator=t.tokenizer.defaultSeperator,t.tokenizer.setSeperator=function(e){null!==e&&void 0!==e&&"object"==typeof e&&(t.tokenizer.seperator=e)},t.tokenizer.resetSeperator=function(){t.tokenizer.seperator=t.tokenizer.defaultSeperator},t.tokenizer.getSeperator=function(){return t.tokenizer.seperator},t.Pipeline=function(){this._queue=[]},t.Pipeline.registeredFunctions={},t.Pipeline.registerFunction=function(e,n){n in t.Pipeline.registeredFunctions&&t.utils.warn("Overwriting existing registered function: "+n),e.label=n,t.Pipeline.registeredFunctions[n]=e},t.Pipeline.getRegisteredFunction=function(e){return e in t.Pipeline.registeredFunctions!=!0?null:t.Pipeline.registeredFunctions[e]},t.Pipeline.warnIfFunctionNotRegistered=function(e){var n=e.label&&e.label in this.registeredFunctions;n||t.utils.warn("Function is not registered with pipeline. This may cause problems when serialising the index.\n",e)},t.Pipeline.load=function(e){var n=new t.Pipeline;return e.forEach(function(e){var i=t.Pipeline.getRegisteredFunction(e);if(!i)throw new Error("Cannot load un-registered function: "+e);n.add(i)}),n},t.Pipeline.prototype.add=function(){var e=Array.prototype.slice.call(arguments);e.forEach(function(e){t.Pipeline.warnIfFunctionNotRegistered(e),this._queue.push(e)},this)},t.Pipeline.prototype.after=function(e,n){t.Pipeline.warnIfFunctionNotRegistered(n);var i=this._queue.indexOf(e);if(-1===i)throw new Error("Cannot find existingFn");this._queue.splice(i+1,0,n)},t.Pipeline.prototype.before=function(e,n){t.Pipeline.warnIfFunctionNotRegistered(n);var i=this._queue.indexOf(e);if(-1===i)throw new Error("Cannot find existingFn");this._queue.splice(i,0,n)},t.Pipeline.prototype.remove=function(e){var t=this._queue.indexOf(e);-1!==t&&this._queue.splice(t,1)},t.Pipeline.prototype.run=function(e){for(var t=[],n=e.length,i=this._queue.length,o=0;n>o;o++){for(var r=e[o],s=0;i>s&&(r=this._queue[s](r,o,e),void 0!==r&&null!==r);s++);void 0!==r&&null!==r&&t.push(r)}return t},t.Pipeline.prototype.reset=function(){this._queue=[]},t.Pipeline.prototype.get=function(){return this._queue},t.Pipeline.prototype.toJSON=function(){return this._queue.map(function(e){return t.Pipeline.warnIfFunctionNotRegistered(e),e.label})},t.Index=function(){this._fields=[],this._ref="id",this.pipeline=new t.Pipeline,this.documentStore=new t.DocumentStore,this.index={},this.eventEmitter=new t.EventEmitter,this._idfCache={},this.on("add","remove","update",function(){this._idfCache={}}.bind(this))},t.Index.prototype.on=function(){var e=Array.prototype.slice.call(arguments);return this.eventEmitter.addListener.apply(this.eventEmitter,e)},t.Index.prototype.off=function(e,t){return this.eventEmitter.removeListener(e,t)},t.Index.load=function(e){e.version!==t.version&&t.utils.warn("version mismatch: current "+t.version+" importing "+e.version);var n=new this;n._fields=e.fields,n._ref=e.ref,n.documentStore=t.DocumentStore.load(e.documentStore),n.pipeline=t.Pipeline.load(e.pipeline),n.index={};for(var i in e.index)n.index[i]=t.InvertedIndex.load(e.index[i]);return n},t.Index.prototype.addField=function(e){return this._fields.push(e),this.index[e]=new t.InvertedIndex,this},t.Index.prototype.setRef=function(e){return this._ref=e,this},t.Index.prototype.saveDocument=function(e){return this.documentStore=new t.DocumentStore(e),this},t.Index.prototype.addDoc=function(e,n){if(e){var n=void 0===n?!0:n,i=e[this._ref];this.documentStore.addDoc(i,e),this._fields.forEach(function(n){var o=this.pipeline.run(t.tokenizer(e[n]));this.documentStore.addFieldLength(i,n,o.length);var r={};o.forEach(function(e){e in r?r[e]+=1:r[e]=1},this);for(var s in r){var u=r[s];u=Math.sqrt(u),this.index[n].addToken(s,{ref:i,tf:u})}},this),n&&this.eventEmitter.emit("add",e,this)}},t.Index.prototype.removeDocByRef=function(e){if(e&&this.documentStore.isDocStored()!==!1&&this.documentStore.hasDoc(e)){var t=this.documentStore.getDoc(e);this.removeDoc(t,!1)}},t.Index.prototype.removeDoc=function(e,n){if(e){var n=void 0===n?!0:n,i=e[this._ref];this.documentStore.hasDoc(i)&&(this.documentStore.removeDoc(i),this._fields.forEach(function(n){var o=this.pipeline.run(t.tokenizer(e[n]));o.forEach(function(e){this.index[n].removeToken(e,i)},this)},this),n&&this.eventEmitter.emit("remove",e,this))}},t.Index.prototype.updateDoc=function(e,t){var t=void 0===t?!0:t;this.removeDocByRef(e[this._ref],!1),this.addDoc(e,!1),t&&this.eventEmitter.emit("update",e,this)},t.Index.prototype.idf=function(e,t){var n="@"+t+"/"+e;if(Object.prototype.hasOwnProperty.call(this._idfCache,n))return this._idfCache[n];var i=this.index[t].getDocFreq(e),o=1+Math.log(this.documentStore.length/(i+1));return this._idfCache[n]=o,o},t.Index.prototype.getFields=function(){return this._fields.slice()},t.Index.prototype.search=function(e,n){if(!e)return[];e="string"==typeof e?{any:e}:JSON.parse(JSON.stringify(e));var i=null;null!=n&&(i=JSON.stringify(n));for(var o=new t.Configuration(i,this.getFields()).get(),r={},s=Object.keys(e),u=0;u80 def to_polars(self) -> "pl.DataFrame": +81 """Converts the sheet to a Polars `DataFrame`. +82 +83 Requires the `polars` extra to be installed. +84 """ +85 import polars as pl +86 +87 df = pl.from_arrow(data=self.to_arrow()) +88 assert isinstance(df, pl.DataFrame) +89 return df0&&t.push(e);for(var i in n)"docs"!==i&&"df"!==i&&this.expandToken(e+i,t,n[i]);return t},t.InvertedIndex.prototype.toJSON=function(){return{root:this.root}},t.Configuration=function(e,n){var e=e||"";if(void 0==n||null==n)throw new Error("fields should not be null");this.config={};var i;try{i=JSON.parse(e),this.buildUserConfig(i,n)}catch(o){t.utils.warn("user configuration parse failed, will use default configuration"),this.buildDefaultConfig(n)}},t.Configuration.prototype.buildDefaultConfig=function(e){this.reset(),e.forEach(function(e){this.config[e]={boost:1,bool:"OR",expand:!1}},this)},t.Configuration.prototype.buildUserConfig=function(e,n){var i="OR",o=!1;if(this.reset(),"bool"in e&&(i=e.bool||i),"expand"in e&&(o=e.expand||o),"fields"in e)for(var r in e.fields)if(n.indexOf(r)>-1){var s=e.fields[r],u=o;void 0!=s.expand&&(u=s.expand),this.config[r]={boost:s.boost||0===s.boost?s.boost:1,bool:s.bool||i,expand:u}}else t.utils.warn("field name in user configuration not found in index instance fields");else this.addAllFields2UserConfig(i,o,n)},t.Configuration.prototype.addAllFields2UserConfig=function(e,t,n){n.forEach(function(n){this.config[n]={boost:1,bool:e,expand:t}},this)},t.Configuration.prototype.get=function(){return this.config},t.Configuration.prototype.reset=function(){this.config={}},lunr.SortedSet=function(){this.length=0,this.elements=[]},lunr.SortedSet.load=function(e){var t=new this;return t.elements=e,t.length=e.length,t},lunr.SortedSet.prototype.add=function(){var e,t;for(e=0;e 1;){if(r===e)return o;e>r&&(t=o),r>e&&(n=o),i=n-t,o=t+Math.floor(i/2),r=this.elements[o]}return r===e?o:-1},lunr.SortedSet.prototype.locationFor=function(e){for(var t=0,n=this.elements.length,i=n-t,o=t+Math.floor(i/2),r=this.elements[o];i>1;)e>r&&(t=o),r>e&&(n=o),i=n-t,o=t+Math.floor(i/2),r=this.elements[o];return r>e?o:e>r?o+1:void 0},lunr.SortedSet.prototype.intersect=function(e){for(var t=new lunr.SortedSet,n=0,i=0,o=this.length,r=e.length,s=this.elements,u=e.elements;;){if(n>o-1||i>r-1)break;s[n]!==u[i]?s[n]u[i]&&i++:(t.add(s[n]),n++,i++)}return t},lunr.SortedSet.prototype.clone=function(){var e=new lunr.SortedSet;return e.elements=this.toArray(),e.length=e.elements.length,e},lunr.SortedSet.prototype.union=function(e){var t,n,i;this.length>=e.length?(t=this,n=e):(t=e,n=this),i=t.clone();for(var o=0,r=n.toArray();o \n"}, "fastexcel.read_excel": {"fullname": "fastexcel.read_excel", "modulename": "fastexcel", "qualname": "read_excel", "kind": "function", "doc": " Opens and loads an excel file.
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\n"}, "fastexcel.ExcelReader.__init__": {"fullname": "fastexcel.ExcelReader.__init__", "modulename": "fastexcel", "qualname": "ExcelReader.__init__", "kind": "function", "doc": "\n", "signature": "(reader: _ExcelReader)"}, "fastexcel.ExcelReader.sheet_names": {"fullname": "fastexcel.ExcelReader.sheet_names", "modulename": "fastexcel", "qualname": "ExcelReader.sheet_names", "kind": "variable", "doc": "The list of sheet names
\n", "annotation": ": list[str]"}, "fastexcel.ExcelReader.load_sheet_by_name": {"fullname": "fastexcel.ExcelReader.load_sheet_by_name", "modulename": "fastexcel", "qualname": "ExcelReader.load_sheet_by_name", "kind": "function", "doc": "Loads a sheet by name.
\n\nParameters
\n\n\n
\n", "signature": "(\tself,\tname: str,\t*,\theader_row: int | None = 0,\tcolumn_names: list[str] | None = None,\tskip_rows: int = 0,\tn_rows: int | None = None,\tschema_sample_rows: int | None = 1000,\tuse_columns: list[str] | list[int] | str | None = None) -> fastexcel.ExcelSheet:", "funcdef": "def"}, "fastexcel.ExcelReader.load_sheet_by_idx": {"fullname": "fastexcel.ExcelReader.load_sheet_by_idx", "modulename": "fastexcel", "qualname": "ExcelReader.load_sheet_by_idx", "kind": "function", "doc": "- name: The name of the sheet to load.
\n- header_row: The index of the row containing the column labels, default index is 0.\nIf
\nNone
, the sheet does not have any column labels.- column_names: Overrides headers found in the document.\nIf
\ncolumn_names
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\nNone
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- \n
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\n- a string, a comma separated list of Excel column letters and column\nranges (e.g.
\n\u201cA:E\u201d
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\n\n\n
\n", "signature": "(\tself,\tidx: int,\t*,\theader_row: int | None = 0,\tcolumn_names: list[str] | None = None,\tskip_rows: int = 0,\tn_rows: int | None = None,\tschema_sample_rows: int | None = 1000,\tuse_columns: list[str] | list[int] | str | None = None) -> fastexcel.ExcelSheet:", "funcdef": "def"}, "fastexcel.ExcelReader.load_sheet": {"fullname": "fastexcel.ExcelReader.load_sheet", "modulename": "fastexcel", "qualname": "ExcelReader.load_sheet", "kind": "function", "doc": "- idx: The index (starting at 0) of the sheet to load.
\n- header_row: The index of the row containing the column labels, default index is 0.\nIf
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- \n
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andA,C,E,F
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\n\nSee
\n", "signature": "(\tself,\tidx_or_name: int | str,\t*,\theader_row: int | None = 0,\tcolumn_names: list[str] | None = None,\tskip_rows: int = 0,\tn_rows: int | None = None,\tschema_sample_rows: int | None = 1000,\tuse_columns: list[str] | list[int] | str | None = None) -> fastexcel.ExcelSheet:", "funcdef": "def"}, "fastexcel.ExcelSheet": {"fullname": "fastexcel.ExcelSheet", "modulename": "fastexcel", "qualname": "ExcelSheet", "kind": "class", "doc": "load_sheet_by_idx
andload_sheet_by_name
for parameter documentation.A class representing a single sheet in an Excel File
\n"}, "fastexcel.ExcelSheet.__init__": {"fullname": "fastexcel.ExcelSheet.__init__", "modulename": "fastexcel", "qualname": "ExcelSheet.__init__", "kind": "function", "doc": "\n", "signature": "(sheet: _ExcelSheet)"}, "fastexcel.ExcelSheet.name": {"fullname": "fastexcel.ExcelSheet.name", "modulename": "fastexcel", "qualname": "ExcelSheet.name", "kind": "variable", "doc": "The name of the sheet
\n", "annotation": ": str"}, "fastexcel.ExcelSheet.width": {"fullname": "fastexcel.ExcelSheet.width", "modulename": "fastexcel", "qualname": "ExcelSheet.width", "kind": "variable", "doc": "The sheet's width
\n", "annotation": ": int"}, "fastexcel.ExcelSheet.height": {"fullname": "fastexcel.ExcelSheet.height", "modulename": "fastexcel", "qualname": "ExcelSheet.height", "kind": "variable", "doc": "The sheet's height, with
\n", "annotation": ": int"}, "fastexcel.ExcelSheet.total_height": {"fullname": "fastexcel.ExcelSheet.total_height", "modulename": "fastexcel", "qualname": "ExcelSheet.total_height", "kind": "variable", "doc": "skip_rows
andnrows
appliedThe sheet's total height
\n", "annotation": ": int"}, "fastexcel.ExcelSheet.selected_columns": {"fullname": "fastexcel.ExcelSheet.selected_columns", "modulename": "fastexcel", "qualname": "ExcelSheet.selected_columns", "kind": "variable", "doc": "The sheet's selected columns
\n", "annotation": ": list[str] | list[int] | None"}, "fastexcel.ExcelSheet.available_columns": {"fullname": "fastexcel.ExcelSheet.available_columns", "modulename": "fastexcel", "qualname": "ExcelSheet.available_columns", "kind": "variable", "doc": "The columns available for the given sheet
\n", "annotation": ": list[str]"}, "fastexcel.ExcelSheet.to_arrow": {"fullname": "fastexcel.ExcelSheet.to_arrow", "modulename": "fastexcel", "qualname": "ExcelSheet.to_arrow", "kind": "function", "doc": "Converts the sheet to a pyarrow
\n", "signature": "(self) -> pyarrow.lib.RecordBatch:", "funcdef": "def"}, "fastexcel.ExcelSheet.to_pandas": {"fullname": "fastexcel.ExcelSheet.to_pandas", "modulename": "fastexcel", "qualname": "ExcelSheet.to_pandas", "kind": "function", "doc": "RecordBatch
Converts the sheet to a Pandas
\n\nDataFrame
.Requires the
\n", "signature": "(self) -> pandas.core.frame.DataFrame:", "funcdef": "def"}, "fastexcel.ExcelSheet.to_polars": {"fullname": "fastexcel.ExcelSheet.to_polars", "modulename": "fastexcel", "qualname": "ExcelSheet.to_polars", "kind": "function", "doc": "pandas
extra to be installed.Converts the sheet to a Polars
\n\nDataFrame
.Requires the
\n", "signature": "(self) -> polars.dataframe.frame.DataFrame:", "funcdef": "def"}, "fastexcel.FastExcelError": {"fullname": "fastexcel.FastExcelError", "modulename": "fastexcel", "qualname": "FastExcelError", "kind": "class", "doc": "polars
extra to be installed.The base class for all fastexcel errors
\n", "bases": "builtins.Exception"}, "fastexcel.CannotRetrieveCellDataError": {"fullname": "fastexcel.CannotRetrieveCellDataError", "modulename": "fastexcel", "qualname": "CannotRetrieveCellDataError", "kind": "class", "doc": "Data for a given cell cannot be retrieved
\n", "bases": "_fastexcel.FastExcelError"}, "fastexcel.CalamineCellError": {"fullname": "fastexcel.CalamineCellError", "modulename": "fastexcel", "qualname": "CalamineCellError", "kind": "class", "doc": "calamine returned an error regarding the content of the cell
\n", "bases": "_fastexcel.FastExcelError"}, "fastexcel.CalamineError": {"fullname": "fastexcel.CalamineError", "modulename": "fastexcel", "qualname": "CalamineError", "kind": "class", "doc": "Generic calamine error
\n", "bases": "_fastexcel.FastExcelError"}, "fastexcel.SheetNotFoundError": {"fullname": "fastexcel.SheetNotFoundError", "modulename": "fastexcel", "qualname": "SheetNotFoundError", "kind": "class", "doc": "Sheet was not found
\n", "bases": "_fastexcel.FastExcelError"}, "fastexcel.ColumnNotFoundError": {"fullname": "fastexcel.ColumnNotFoundError", "modulename": "fastexcel", "qualname": "ColumnNotFoundError", "kind": "class", "doc": "Column was not found
\n", "bases": "_fastexcel.FastExcelError"}, "fastexcel.ArrowError": {"fullname": "fastexcel.ArrowError", "modulename": "fastexcel", "qualname": "ArrowError", "kind": "class", "doc": "Generic arrow error
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"h": {"docs": {"fastexcel.ExcelReader.load_sheet_by_name": {"tf": 1}, "fastexcel.ExcelReader.load_sheet_by_idx": {"tf": 1}}, "df": 2}}}}, "o": {"docs": {}, "df": 0, "u": {"docs": {}, "df": 0, "l": {"docs": {}, "df": 0, "d": {"docs": {"fastexcel.ExcelReader.load_sheet_by_name": {"tf": 1}, "fastexcel.ExcelReader.load_sheet_by_idx": {"tf": 1}}, "df": 2}}}}, "a": {"docs": {}, "df": 0, "s": {"docs": {"fastexcel.SheetNotFoundError": {"tf": 1}, "fastexcel.ColumnNotFoundError": {"tf": 1}}, "df": 2}}}, "m": {"docs": {}, "df": 0, "a": {"docs": {}, "df": 0, "n": {"docs": {}, "df": 0, "y": {"docs": {"fastexcel.ExcelReader.load_sheet_by_name": {"tf": 1.7320508075688772}, "fastexcel.ExcelReader.load_sheet_by_idx": {"tf": 1.7320508075688772}}, "df": 2}}}}, "g": {"docs": {"fastexcel.ExcelReader.load_sheet_by_name": {"tf": 1}, "fastexcel.ExcelReader.load_sheet_by_idx": {"tf": 1}}, "df": 2, "i": {"docs": {}, "df": 0, "v": {"docs": {}, "df": 0, "e": {"docs": {}, "df": 0, "n": {"docs": {"fastexcel.ExcelSheet.available_columns": {"tf": 1}, "fastexcel.CannotRetrieveCellDataError": {"tf": 1}}, "df": 2}}}}, "e": {"docs": {}, "df": 0, "n": {"docs": {}, "df": 0, "e": {"docs": {}, "df": 0, "r": {"docs": {}, "df": 0, "i": {"docs": {}, "df": 0, "c": {"docs": {"fastexcel.CalamineError": {"tf": 1}, "fastexcel.ArrowError": {"tf": 1}}, "df": 2}}}}}}}}}}, "pipeline": ["trimmer"], "_isPrebuiltIndex": true}; + /** pdoc search index */const docs = {"version": "0.9.5", "fields": ["qualname", "fullname", "annotation", "default_value", "signature", "bases", "doc"], "ref": "fullname", "documentStore": {"docs": {"fastexcel": {"fullname": "fastexcel", "modulename": "fastexcel", "kind": "module", "doc": "\n"}, "fastexcel.read_excel": {"fullname": "fastexcel.read_excel", "modulename": "fastexcel", "qualname": "read_excel", "kind": "function", "doc": "Opens and loads an excel file.
\n\nParameters
\n\n\n
\n", "signature": "(source: pathlib.Path | str | bytes) -> fastexcel.ExcelReader:", "funcdef": "def"}, "fastexcel.ExcelReader": {"fullname": "fastexcel.ExcelReader", "modulename": "fastexcel", "qualname": "ExcelReader", "kind": "class", "doc": "- source: The path to a file or its content as bytes
\nA class representing an open Excel file and allowing to read its sheets
\n"}, "fastexcel.ExcelReader.__init__": {"fullname": "fastexcel.ExcelReader.__init__", "modulename": "fastexcel", "qualname": "ExcelReader.__init__", "kind": "function", "doc": "\n", "signature": "(reader: _ExcelReader)"}, "fastexcel.ExcelReader.sheet_names": {"fullname": "fastexcel.ExcelReader.sheet_names", "modulename": "fastexcel", "qualname": "ExcelReader.sheet_names", "kind": "variable", "doc": "The list of sheet names
\n", "annotation": ": list[str]"}, "fastexcel.ExcelReader.load_sheet_by_name": {"fullname": "fastexcel.ExcelReader.load_sheet_by_name", "modulename": "fastexcel", "qualname": "ExcelReader.load_sheet_by_name", "kind": "function", "doc": "Loads a sheet by name.
\n\nParameters
\n\n\n
\n", "signature": "(\tself,\tname: str,\t*,\theader_row: int | None = 0,\tcolumn_names: list[str] | None = None,\tskip_rows: int = 0,\tn_rows: int | None = None,\tschema_sample_rows: int | None = 1000,\tuse_columns: list[str] | list[int] | str | None = None) -> fastexcel.ExcelSheet:", "funcdef": "def"}, "fastexcel.ExcelReader.load_sheet_by_idx": {"fullname": "fastexcel.ExcelReader.load_sheet_by_idx", "modulename": "fastexcel", "qualname": "ExcelReader.load_sheet_by_idx", "kind": "function", "doc": "- name: The name of the sheet to load.
\n- header_row: The index of the row containing the column labels, default index is 0.\nIf
\nNone
, the sheet does not have any column labels.- column_names: Overrides headers found in the document.\nIf
\ncolumn_names
is used,header_row
will be ignored.- n_rows: Specifies how many rows should be loaded.\nIf
\nNone
, all rows are loaded- skip_rows: Specifies how many rows should be skipped after the header.\nIf
\nheader_row
isNone
, it skips the number of rows from the\nstart of the sheet.- schema_sample_rows: Specifies how many rows should be used to determine\nthe dtype of a column.\nIf
\nNone
, all rows will be used.- use_columns: Specifies the columns to use. Can either be: \n
\n\n
- \n
None
to select all columns- a list of strings, the column names
\n- a list of ints, the column indices (starting at 0)
\n- a string, a comma separated list of Excel column letters and column\nranges (e.g.
\n\u201cA:E\u201d
or\u201cA,C,E:F\u201d
, which would result in\nA,B,C,D,E
andA,C,E,F
)Loads a sheet by index.
\n\nParameters
\n\n\n
\n", "signature": "(\tself,\tidx: int,\t*,\theader_row: int | None = 0,\tcolumn_names: list[str] | None = None,\tskip_rows: int = 0,\tn_rows: int | None = None,\tschema_sample_rows: int | None = 1000,\tuse_columns: list[str] | list[int] | str | None = None) -> fastexcel.ExcelSheet:", "funcdef": "def"}, "fastexcel.ExcelReader.load_sheet": {"fullname": "fastexcel.ExcelReader.load_sheet", "modulename": "fastexcel", "qualname": "ExcelReader.load_sheet", "kind": "function", "doc": "- idx: The index (starting at 0) of the sheet to load.
\n- header_row: The index of the row containing the column labels, default index is 0.\nIf
\nNone
, the sheet does not have any column labels.- column_names: Overrides headers found in the document.\nIf
\ncolumn_names
is used,header_row
will be ignored.- n_rows: Specifies how many rows should be loaded.\nIf
\nNone
, all rows are loaded- skip_rows: Specifies how many rows should be skipped after the header.\nIf
\nheader_row
isNone
, it skips the number of rows from the\nstart of the sheet.- schema_sample_rows: Specifies how many rows should be used to determine\nthe dtype of a column.\nIf
\nNone
, all rows will be used.- use_columns: Specifies the columns to use. Can either be: \n
\n\n
- \n
None
to select all columns- a list of strings, the column names
\n- a list of ints, the column indices (starting at 0)
\n- a string, a comma separated list of Excel column letters and column\nranges (e.g.
\n\u201cA:E\u201d
or\u201cA,C,E:F\u201d
, which would result in\nA,B,C,D,E
andA,C,E,F
)Loads a sheet by name if a string is passed or by index if an integer is passed.
\n\nSee
\n", "signature": "(\tself,\tidx_or_name: int | str,\t*,\theader_row: int | None = 0,\tcolumn_names: list[str] | None = None,\tskip_rows: int = 0,\tn_rows: int | None = None,\tschema_sample_rows: int | None = 1000,\tuse_columns: list[str] | list[int] | str | None = None) -> fastexcel.ExcelSheet:", "funcdef": "def"}, "fastexcel.ExcelSheet": {"fullname": "fastexcel.ExcelSheet", "modulename": "fastexcel", "qualname": "ExcelSheet", "kind": "class", "doc": "load_sheet_by_idx
andload_sheet_by_name
for parameter documentation.A class representing a single sheet in an Excel File
\n"}, "fastexcel.ExcelSheet.__init__": {"fullname": "fastexcel.ExcelSheet.__init__", "modulename": "fastexcel", "qualname": "ExcelSheet.__init__", "kind": "function", "doc": "\n", "signature": "(sheet: _ExcelSheet)"}, "fastexcel.ExcelSheet.name": {"fullname": "fastexcel.ExcelSheet.name", "modulename": "fastexcel", "qualname": "ExcelSheet.name", "kind": "variable", "doc": "The name of the sheet
\n", "annotation": ": str"}, "fastexcel.ExcelSheet.width": {"fullname": "fastexcel.ExcelSheet.width", "modulename": "fastexcel", "qualname": "ExcelSheet.width", "kind": "variable", "doc": "The sheet's width
\n", "annotation": ": int"}, "fastexcel.ExcelSheet.height": {"fullname": "fastexcel.ExcelSheet.height", "modulename": "fastexcel", "qualname": "ExcelSheet.height", "kind": "variable", "doc": "The sheet's height, with
\n", "annotation": ": int"}, "fastexcel.ExcelSheet.total_height": {"fullname": "fastexcel.ExcelSheet.total_height", "modulename": "fastexcel", "qualname": "ExcelSheet.total_height", "kind": "variable", "doc": "skip_rows
andnrows
appliedThe sheet's total height
\n", "annotation": ": int"}, "fastexcel.ExcelSheet.selected_columns": {"fullname": "fastexcel.ExcelSheet.selected_columns", "modulename": "fastexcel", "qualname": "ExcelSheet.selected_columns", "kind": "variable", "doc": "The sheet's selected columns
\n", "annotation": ": list[str] | list[int] | None"}, "fastexcel.ExcelSheet.available_columns": {"fullname": "fastexcel.ExcelSheet.available_columns", "modulename": "fastexcel", "qualname": "ExcelSheet.available_columns", "kind": "variable", "doc": "The columns available for the given sheet
\n", "annotation": ": list[str]"}, "fastexcel.ExcelSheet.to_arrow": {"fullname": "fastexcel.ExcelSheet.to_arrow", "modulename": "fastexcel", "qualname": "ExcelSheet.to_arrow", "kind": "function", "doc": "Converts the sheet to a pyarrow
\n", "signature": "(self) -> pyarrow.lib.RecordBatch:", "funcdef": "def"}, "fastexcel.ExcelSheet.to_pandas": {"fullname": "fastexcel.ExcelSheet.to_pandas", "modulename": "fastexcel", "qualname": "ExcelSheet.to_pandas", "kind": "function", "doc": "RecordBatch
Converts the sheet to a Pandas
\n\nDataFrame
.Requires the
\n", "signature": "(self) -> pandas.core.frame.DataFrame:", "funcdef": "def"}, "fastexcel.ExcelSheet.to_polars": {"fullname": "fastexcel.ExcelSheet.to_polars", "modulename": "fastexcel", "qualname": "ExcelSheet.to_polars", "kind": "function", "doc": "pandas
extra to be installed.Converts the sheet to a Polars
\n\nDataFrame
.Requires the
\n", "signature": "(self) -> polars.dataframe.frame.DataFrame:", "funcdef": "def"}, "fastexcel.FastExcelError": {"fullname": "fastexcel.FastExcelError", "modulename": "fastexcel", "qualname": "FastExcelError", "kind": "class", "doc": "polars
extra to be installed.The base class for all fastexcel errors
\n", "bases": "builtins.Exception"}, "fastexcel.CannotRetrieveCellDataError": {"fullname": "fastexcel.CannotRetrieveCellDataError", "modulename": "fastexcel", "qualname": "CannotRetrieveCellDataError", "kind": "class", "doc": "Data for a given cell cannot be retrieved
\n", "bases": "_fastexcel.FastExcelError"}, "fastexcel.CalamineCellError": {"fullname": "fastexcel.CalamineCellError", "modulename": "fastexcel", "qualname": "CalamineCellError", "kind": "class", "doc": "calamine returned an error regarding the content of the cell
\n", "bases": "_fastexcel.FastExcelError"}, "fastexcel.CalamineError": {"fullname": "fastexcel.CalamineError", "modulename": "fastexcel", "qualname": "CalamineError", "kind": "class", "doc": "Generic calamine error
\n", "bases": "_fastexcel.FastExcelError"}, "fastexcel.SheetNotFoundError": {"fullname": "fastexcel.SheetNotFoundError", "modulename": "fastexcel", "qualname": "SheetNotFoundError", "kind": "class", "doc": "Sheet was not found
\n", "bases": "_fastexcel.FastExcelError"}, "fastexcel.ColumnNotFoundError": {"fullname": "fastexcel.ColumnNotFoundError", "modulename": "fastexcel", "qualname": "ColumnNotFoundError", "kind": "class", "doc": "Column was not found
\n", "bases": "_fastexcel.FastExcelError"}, "fastexcel.ArrowError": {"fullname": "fastexcel.ArrowError", "modulename": "fastexcel", "qualname": "ArrowError", "kind": "class", "doc": "Generic arrow error
\n", "bases": "_fastexcel.FastExcelError"}, "fastexcel.InvalidParametersError": {"fullname": "fastexcel.InvalidParametersError", "modulename": "fastexcel", "qualname": "InvalidParametersError", "kind": "class", "doc": "Provided parameters are invalid
\n", "bases": "_fastexcel.FastExcelError"}, "fastexcel.UnsupportedColumnTypeCombinationError": {"fullname": "fastexcel.UnsupportedColumnTypeCombinationError", "modulename": "fastexcel", "qualname": "UnsupportedColumnTypeCombinationError", "kind": "class", "doc": "Column contains an unsupported type combination
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"pipeline": ["trimmer"], "_isPrebuiltIndex": true}; // mirrored in build-search-index.js (part 1) // Also split on html tags. this is a cheap heuristic, but good enough.