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# pandas.DataFrame.swaplevel

DataFrame.swaplevel(i=-2, j=-1, axis=0)

  Swap levels i and j in a `MultiIndex`.

  Default is to swap the two innermost levels of the index.

  Parameters:
    i, j int or str

      Levels of the indices to be swapped. Can pass level name as string.

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

      The axis to swap levels on. 0 or ‘index’ for row-wise, 1 or ‘columns’ for column-wise.

  Returns:
    DataFrame

      DataFrame with levels swapped in MultiIndex.

  See also

  `DataFrame.reorder_levels`

    Reorder levels of MultiIndex.

  `DataFrame.sort_index`

    Sort MultiIndex.

  Examples

      >>> df = pd.DataFrame(
      ...     {"Grade": ["A", "B", "A", "C"]},
      ...     index=[
      ...         ["Final exam", "Final exam", "Coursework", "Coursework"],
      ...         ["History", "Geography", "History", "Geography"],
      ...         ["January", "February", "March", "April"],
      ...     ],
      ... )
      >>> df
                                          Grade
      Final exam  History     January      A
                  Geography   February     B
      Coursework  History     March        A
                  Geography   April        C

  In the following example, we will swap the levels of the indices. Here, we will swap the levels column-wise, but levels can be swapped row-wise in a similar manner. Note that column-wise is the default behaviour. By not supplying any arguments for i and j, we swap the last and second to last indices.

      >>> df.swaplevel()
                                          Grade
      Final exam  January     History         A
                  February    Geography       B
      Coursework  March       History         A
                  April       Geography       C

  By supplying one argument, we can choose which index to swap the last index with. We can for example swap the first index with the last one as follows.

      >>> df.swaplevel(0)
                                          Grade
      January     History     Final exam      A
      February    Geography   Final exam      B
      March       History     Coursework      A
      April       Geography   Coursework      C

  We can also define explicitly which indices we want to swap by supplying values for both i and j. Here, we for example swap the first and second indices.

      >>> df.swaplevel(0, 1)
                                          Grade
      History     Final exam  January         A
      Geography   Final exam  February        B
      History     Coursework  March           A
      Geography   Coursework  April           C