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 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. |
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Returns: |
dropped : type of caller |
Specifying both labels
and index
or columns
will raise a ValueError.
>>> 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
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http://pandas.pydata.org/pandas-docs/version/0.22.0/generated/pandas.Series.drop.html