pandas.DataFrame.set_index¶
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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