# pandas.DataFrame.set_index

DataFrame.set_index(keys, drop=True, append=False, inplace=False, verify_integrity=False)

  Set the DataFrame index using existing columns.

  Set the DataFrame index (row labels) using one or more existing columns or arrays (of the correct length). The index can replace the existing index or expand on it.

  Parameters
    keys label or array-like or list of labels/arrays

      This parameter can be either a single column key, a single array of the same length as the calling DataFrame, or a list containing an arbitrary combination of column keys and arrays. Here, “array” encompasses `Series`, `Index`, `np.ndarray`, and instances of `Iterator`.

    drop bool, default True

      Delete columns to be used as the new index.

    append bool, default False

      Whether to append columns to existing index.

    inplace bool, default False

      If True, modifies the DataFrame in place (do not create a new object).

    verify_integrity bool, default False

      Check the new index for duplicates. Otherwise defer the check until necessary. Setting to False will improve the performance of this method.

  Returns
    DataFrame or None

      Changed row labels or None if `inplace=True`.

  See also

  `DataFrame.reset_index`

    Opposite of set_index.

  `DataFrame.reindex`

    Change to new indices or expand indices.

  `DataFrame.reindex_like`

    Change to same indices as other DataFrame.

  Examples

      >>> df = pd.DataFrame({'month': [1, 4, 7, 10],
      ...                    'year': [2012, 2014, 2013, 2014],
      ...                    'sale': [55, 40, 84, 31]})
      >>> df
         month  year  sale
      0      1  2012    55
      1      4  2014    40
      2      7  2013    84
      3     10  2014    31

  Set the index to become the ‘month’ column:

      >>> df.set_index('month')
             year  sale
      month
      1      2012    55
      4      2014    40
      7      2013    84
      10     2014    31

  Create a MultiIndex using columns ‘year’ and ‘month’:

      >>> df.set_index(['year', 'month'])
                  sale
      year  month
      2012  1     55
      2014  4     40
      2013  7     84
      2014  10    31

  Create a MultiIndex using an Index and a column:

      >>> df.set_index([pd.Index([1, 2, 3, 4]), 'year'])
               month  sale
         year
      1  2012  1      55
      2  2014  4      40
      3  2013  7      84
      4  2014  10     31

  Create a MultiIndex using two Series:

      >>> s = pd.Series([1, 2, 3, 4])
      >>> df.set_index([s, s**2])
            month  year  sale
      1 1       1  2012    55
      2 4       4  2014    40
      3 9       7  2013    84
      4 16     10  2014    31