filter_names

skrub.selectors.filter_names(predicate, *args, **kwargs)

Select columns based on their name.

For a column whose name is col_name, predicate is called as predicate(col_name, *args, **kwargs) and the column is selected if returns True. Note this is different from filter, because here the predicate is passed the column name whereas with filter, the predicate is passed the actual column (pandas or polars Series).

args and kwargs are extra parameters for the predicate. Storing parameters like this rather than in a closure can help using an importable function as the predicate rather than a local one, which is necessary to pickle the selector. (An alternative is to use functools.partial).

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.filter_names(lambda name: name.endswith('_mm'))
>>> s.select(df, selector)
   height_mm  width_mm
0      297.0     210.0
1      420.0     297.0

If we want to pickle the selector, we’re better off using an importable function and passing the arguments separately:

>>> selector = s.filter_names(str.endswith, '_mm')
>>> selector
filter_names(str.endswith, '_mm')

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

>>> import pickle
>>> _ = pickle.dumps(selector) # OK