pandas.DataFrame.set_index

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

Set the DataFrame index (row labels) using one or more existing columns. By default yields a new object.

Parameters:

keys : column label or list of column labels / arrays drop : boolean, default True Delete columns to be used as the new index append : boolean, default False Whether to append columns to existing index inplace : boolean, default False Modify the DataFrame in place (do not create a new object) verify_integrity : boolean, 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 : DataFrame

Examples

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

Set the index to become the ‘month’ column:

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

Create a multi-index 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 multi-index using a set of values and a column:

>>> df.set_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