pandas.DataFrame.pivot

DataFrame.pivot(index=None, columns=None, values=None)

Reshape data (produce a “pivot” table) based on column values. Uses unique values from index / columns to form axes of the resulting DataFrame.

Parameters:

index : string or object, optional

Column name to use to make new frame’s index. If None, uses existing index.

columns : string or object

Column name to use to make new frame’s columns

values : string or object, optional

Column name to use for populating new frame’s values. If not specified, all remaining columns will be used and the result will have hierarchically indexed columns

Returns:

pivoted : DataFrame

See also

DataFrame.pivot_table

generalization of pivot that can handle duplicate values for one index/column pair

DataFrame.unstack

pivot based on the index values instead of a column

Notes

For finer-tuned control, see hierarchical indexing documentation along with the related stack/unstack methods

Examples

>>> df = pd.DataFrame({'foo': ['one','one','one','two','two','two'],
                       'bar': ['A', 'B', 'C', 'A', 'B', 'C'],
                       'baz': [1, 2, 3, 4, 5, 6]})
>>> df
    foo   bar  baz
0   one   A    1
1   one   B    2
2   one   C    3
3   two   A    4
4   two   B    5
5   two   C    6

>>> df.pivot(index='foo', columns='bar', values='baz')
     A   B   C
one  1   2   3
two  4   5   6

>>> df.pivot(index='foo', columns='bar')['baz']
     A   B   C
one  1   2   3
two  4   5   6