drop

skrub.selectors.drop(df, selector)

Select the columns of a dataframe that are NOT matched by the selector.

This is the complement of select(): it returns a new dataframe containing all columns except those matched by the selector.

Parameters:

dfdataframe

The dataframe to process.

selectorselector, str, or list

A selector object, single column name, or list of column names indicating which columns to drop.

Returns:

dataframe

A new dataframe with the matched columns removed, preserving the order of remaining columns.

See also

select

Return only the columns matched by a selector

inv

Create an inverted selector matching all columns except those from the input

Notes

drop is logically equivalent to select(df, ~selector) or select(df, s.all() - selector).

drop preserves the original column order of the remaining columns.

Examples

>>> from skrub import selectors as s
>>> import pandas as pd
>>> df = pd.DataFrame(
...     {
...         "height_mm": [210.0, 297.0],
...         "width_mm": [188.5, 210.0],
...         "kind": ["A5", "A4"],
...         "ID": [5, 4],
...     }
... )
>>> df
   height_mm  width_mm kind  ID
0      210.0     188.5   A5   5
1      297.0     210.0   A4   4

Drop columns matching a pattern:

>>> s.drop(df, s.glob("*_mm"))
  kind  ID
0   A5   5
1   A4   4

Drop specific columns by name (can pass names directly):

>>> s.drop(df, ['height_mm', 'width_mm'])
  kind  ID
0   A5   5
1   A4   4

Preserve only certain types (via drop):

>>> s.drop(df, s.all() - s.string())
  kind
0   A5
1   A4