select

skrub.selectors.select(df, selector)

Apply a selector to a dataframe and return the resulting dataframe.

selector can be anything accepted by make_selector i.e. a selector, column name or list of column names.

Examples

>>> from skrub import selectors as s
>>> import pandas as pd
>>> df = pd.DataFrame(
...     {
...         "height_mm": [297.0, 420.0],
...         "width_mm": [210.0, 297.0],
...         "kind": ["A4", "A3"],
...         "ID": [4, 3],
...     }
... )
>>> df
   height_mm  width_mm kind  ID
0      297.0     210.0   A4   4
1      420.0     297.0   A3   3

>>> selector = s.all() - 'ID'
>>> selector
(all() - cols('ID'))

>>> selector.expand(df)
['height_mm', 'width_mm', 'kind']

>>> s.select(df, selector)
   height_mm  width_mm kind
0      297.0     210.0   A4
1      420.0     297.0   A3

We can also pass column names directly:

>>> s.select(df, ['kind', 'ID'])
  kind  ID
0   A4   4
1   A3   3

Gallery examples

AggJoiner on a credit fraud dataset

AggJoiner on a credit fraud dataset