# pandas.Series.drop

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

  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

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