pandas.Series.drop

Series.drop(labels=None, axis=0, index=None, columns=None, level=None, inplace=False, errors='raise') [source]

Return new object with labels in requested axis removed.

Parameters:

labels : single label or list-like Index or column labels to drop. axis : int or axis name Whether to drop labels from the index (0 / ‘index’) or columns (1 / ‘columns’). index, columns : single label or list-like Alternative to specifying axis (labels, axis=1 is equivalent to columns=labels). New in version 0.21.0. level : int or level name, default None For MultiIndex inplace : bool, default False If True, do operation inplace and return None. errors : {‘ignore’, ‘raise’}, default ‘raise’ If ‘ignore’, suppress error and existing labels are dropped.

Returns:

dropped : type of caller

Notes

Specifying both labels and index or columns will raise a ValueError.

Examples

>>> df = pd.DataFrame(np.arange(12).reshape(3,4),
                      columns=['A', 'B', 'C', 'D'])
>>> df
   A  B   C   D
0  0  1   2   3
1  4  5   6   7
2  8  9  10  11

Drop columns

>>> df.drop(['B', 'C'], axis=1)
   A   D
0  0   3
1  4   7
2  8  11

>>> df.drop(columns=['B', 'C'])
   A   D
0  0   3
1  4   7
2  8  11

Drop a row by index

>>> df.drop([0, 1])
   A  B   C   D
2  8  9  10  11