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# pandas.DataFrame.droplevel

DataFrame.droplevel(level, axis=0)

  Return Series/DataFrame with requested index / column level(s) removed.

  This method is useful for simplifying a MultiIndex by removing one or more levels.

  Parameters:
    level int, str, or list-like

      If a string is given, must be the name of a level If list-like, elements must be names or positional indexes of levels.

    axis{0 or ‘index’, 1 or ‘columns’}, default 0

      Axis along which the level(s) is removed:

      - 0 or ‘index’: remove level(s) in column.

      - 1 or ‘columns’: remove level(s) in row.

      For Series this parameter is unused and defaults to 0.

  Returns:
    Series/DataFrame

      Series/DataFrame with requested index / column level(s) removed.

  See also

  `DataFrame.replace`

    Replace values given in to_replace with value.

  `DataFrame.pivot`

    Return reshaped DataFrame organized by given index / column values.

  Examples

      >>> df = (
      ...     pd.DataFrame([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]])
      ...     .set_index([0, 1])
      ...     .rename_axis(["a", "b"])
      ... )

      >>> df.columns = pd.MultiIndex.from_tuples(
      ...     [("c", "e"), ("d", "f")], names=["level_1", "level_2"]
      ... )

      >>> df
      level_1   c   d
      level_2   e   f
      a b
      1 2      3   4
      5 6      7   8
      9 10    11  12

      >>> df.droplevel("a")
      level_1   c   d
      level_2   e   f
      b
      2        3   4
      6        7   8
      10      11  12

      >>> df.droplevel("level_2", axis=1)
      level_1   c   d
      a b
      1 2      3   4
      5 6      7   8
      9 10    11  12