This release encompasses all the features introduced in 1.0.0
and introduces additional functionalities along with more precise docstrings.
Options
set_option
function has more options:
max_cellwidth
: Maximum width of any VerticaPy table's cell.max_tableheight
: Maximum height of VerticaPy tables.theme
: Theme used to display the VerticaPy objects (light
,dark
orsphinx
).verbosity
: This will set the amount of information to display while executing VerticaPy functions.
There are four levels of verbosity
:
- 0 (silent)
- 1 (warning)
- 2 (info)
- 3 (debug)
Machine Learning
PLS Regression
Partial Least Squares (PLS
) regression has been added to VerticaPy.
This integration will enhance VerticaPy's analytics capabilities, particularly benefiting Vertica customers who have expressed interest in utilizing PLS regression (PLSRegression
).
Example use:
from verticapy.machine_learning.vertica import PLSRegression
model = PLSRegression()
model.fit(
train_data,
[
"col1",
"col2",
"col3",
],
"Y",
test_data,
)
Note: All the ML models that were introduced in version 1.0.x
are also supported in version 1.1.x
.
Performance
QueryProfiler
has been greatly supplemented in this release:
QueryProfilerInterface
Now we have added the functionality of a session_control_param
parameter.
This allows users to enter the alter session SQL before profiling the queries.
QueryProfilerInterface
-
Added many more metrics for the profiled queries such as:
rows_filtered_sip
container_rows_filtered_sip
container_rows_pruned_sip
and more...
-
There is a new tab which helps you select particular tooltips from any select path id.
-
A new tab also highlights if there are any non-default
SESSION PARAMETERS
. -
Improved the efficiency of plotting the tree by chaching results.
QueryProfilerComparison
QueryProfilerComparison
class offers an extended set of functionalities, enabling the creation of complex trees with multiple metrics.
from verticapy.performance.vertica import QueryProfilerInterface
qprof_interface_1 = QueryProfilerInterface(
key_id = "key_1",
target_schema = "schema_1",
)
qprof_interface_2 = QueryProfilerInterface(
key_id = "key_2",
target_schema = "schema_1",
)
from verticapy.performance.vertica import QueryProfilerComparison
qprof_compare = QueryProfilerComparison(qprof_interface_1, qprof_interface_2)
qprof_compare.get_qplan_tree()
Deprecations
Release Notes
Changelogs
- Full Changelog: 1.0.4...1.0.5
Installation
The release will be on available on the defaults and can be installed using:
python3 -m pip install verticapy
If you want to install extra features, use:
python3 -m pip install verticapy[all]
Please report any issues on our GitHub page
Contributors
We would like to extend our thanks to all the contributors who made this release possible:
- Badr Ouali @oualib
- Umar Farooq Ghumman @mail4umar
If you would like to contribute then please visit our updated contributing guidelines.