pandas-select 0.2.0

Installation

pandas-select is a Python-only package hosted on PyPI. It can be installed via pip:

pip install pandas-select

Design goals

• Fully compatible with the pandas.DataFrame [] operator and the pandas.DataFrame.loc accessor.

• Emphasise readability and conciseness by cutting boilerplate:

# 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.

# 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.

    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+.