https://github.com/jeffzi/pandas-select

Supercharged pandas indexing
https://github.com/jeffzi/pandas-select

pandas pandera python scikit-learn

Last synced: 17 days ago
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Supercharged pandas indexing

• Host: GitHub
• URL: https://github.com/jeffzi/pandas-select
• Owner: jeffzi
• License: bsd-3-clause
• Created: 2020-01-14T13:10:49.000Z (almost 5 years ago)
• Default Branch: master
• Last Pushed: 2021-03-28T23:29:53.000Z (over 3 years ago)
• Last Synced: 2024-10-09T09:25:58.067Z (28 days ago)
• Topics: pandas, pandera, python, scikit-learn
• Language: Python
• Homepage: https://pandas-select.readthedocs.io/
• Size: 171 KB
• Stars: 9
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE

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README

        
==================================================

``pandas-select``: Supercharged DataFrame indexing

==================================================

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``pandas-select`` is a collection of DataFrame selectors that facilitates indexing

and selecting data, fully compatible with pandas vanilla indexing.

The selector functions can choose variables based on their

`name `_,

`data type `_,

`arbitrary conditions `_,

or any `combination of these `_.

``pandas-select`` is inspired by the excellent R library `tidyselect `_.

.. installation-start

Installation

------------

``pandas-select`` is a Python-only package `hosted on PyPI `_.

It can be installed via `pip `_:

.. code-block:: console

   pip install pandas-select

.. installation-end

Design goals

------------

* Fully compatible with the

  `pandas.DataFrame `_

  ``[]`` operator and the

  `pandas.DataFrame.loc `_

  accessor.

* Emphasise readability and conciseness by cutting boilerplate:

.. code-block:: python

   # pandas-select

   df[AllNumeric()]

   # vanilla

   df.select_dtypes("number").columns

   # pandas-select

   df[StartsWith("Type") | "Legendary"]

   # vanilla

   df.loc[:, df.columns.str.startswith("Type") | (df.columns == "Legendary")]

* Ease the challenges of `indexing with hierarchical index `_

  and offers an alternative to `slicers `_

  when the labels cannot be listed manually.

.. code-block:: python

    # pandas-select

    df_mi.loc[Contains("Jeff", axis="index", level="Name")]

    # vanilla

    df_mi.loc[df_mi.index.get_level_values("Name").str.contains("Jeff")]

* Play well with machine learning applications.

  - Respect the columns order.

  - Allow *deferred selection* when the DataFrame's columns are not known in advance,

    for example in automated machine learning applications.

  - Offer integration with `sklearn `_.

    .. code-block:: python

        from pandas_select import AnyOf, AllBool, AllNominal, AllNumeric, ColumnSelector

        from sklearn.compose import make_column_transformer

        from sklearn.preprocessing import OneHotEncoder, StandardScaler

        ct = make_column_transformer(

           (StandardScaler(), ColumnSelector(AllNumeric() & ~AnyOf("Generation"))),

           (OneHotEncoder(), ColumnSelector(AllNominal() | AllBool() | "Generation")),

        )

        ct.fit_transform(df)

Project Information

-------------------

``pandas-select`` is released under the `BS3 `_ license,

its documentation lives at `Read the Docs `_,

the code on `GitHub `_,

and the latest release on `PyPI `_.

It is tested on Python 3.6+.