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; 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