pandas.DataFrame.drop¶

Drop specified labels from rows or columns.

Remove rows or columns by specifying label names and corresponding axis, or by specifying directly index or column names. When using a multi-index, labels on different levels can be removed by specifying the level.

param labels

single label or list-like: Index or column labels to drop.

param axis

{0 or ‘index’, 1 or ‘columns’}, default 0: Whether to drop labels from the index (0 or ‘index’) or columns (1 or ‘columns’).

param index

single label or list-like: Alternative to specifying axis (labels, axis=0 is equivalent to index=labels).

New in version 0.21.0.

param columns

single label or list-like: Alternative to specifying axis (labels, axis=1 is equivalent to columns=labels).

New in version 0.21.0.

param level

int or level name, optional: For MultiIndex, level from which the labels will be removed.

param inplace

bool, default False: If True, do operation inplace and return None.

param errors

{‘ignore’, ‘raise’}, default ‘raise’: If ‘ignore’, suppress error and only existing labels are dropped.

return

DataFrame DataFrame without the removed index or column labels.

raises

KeyError: If any of the labels is not found in the selected axis.

Limitations¶

Parameters labels, axis, index, level and inplace are currently unsupported.
Parameter columns is required and is expected to be a Literal value with one column name
or Tuple with columns names.
Supported errors can be {raise, ignore}, default raise. If ignore, suppress error and only
existing labels are dropped.

Examples¶

Drop specified columns from DataFrame.¶

import pandas as pd
from numba import njit

@njit
def dataframe_drop():
    df = pd.DataFrame({'A': [1.0, 2.0, 3.0, 1.0], 'B': [4, 5, 6, 7], 'C': ['a', 'b', 'c', 'd']})

    return df.drop(columns='A')

print(dataframe_drop())

$ python ./dataframe/dataframe_drop.py
   B  C
0  4  a
1  5  b
2  6  c
3  7  d

Navigation

pandas.DataFrame.drop¶

Limitations¶

Examples¶