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=1is 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