pandas.Series.str.partition

Series.str.partition(sep=' ', expand=True)

Split the string at the first occurrence of sep.

This method splits the string at the first occurrence of sep, and returns 3 elements containing the part before the separator, the separator itself, and the part after the separator. If the separator is not found, return 3 elements containing the string itself, followed by two empty strings.

Parameters:

sepstr, default whitespace

String to split on.

expandbool, default True

If True, return DataFrame/MultiIndex expanding dimensionality. If False, return Series/Index.

Returns:

DataFrame/MultiIndex or Series/Index of objects

Returns appropriate type based on expand parameter with strings split based on the sep parameter.

See also

rpartition

Split the string at the last occurrence of sep.

Series.str.split

Split strings around given separators.

str.partition

Standard library version.

Examples

>>> s = pd.Series(['Linda van der Berg', 'George Pitt-Rivers'])
>>> s
0    Linda van der Berg
1    George Pitt-Rivers
dtype: object

>>> s.str.partition()
        0  1             2
0   Linda     van der Berg
1  George      Pitt-Rivers

To partition by the last space instead of the first one:

>>> s.str.rpartition()
               0  1            2
0  Linda van der            Berg
1         George     Pitt-Rivers

To partition by something different than a space:

>>> s.str.partition('-')
                    0  1       2
0  Linda van der Berg
1         George Pitt  -  Rivers

To return a Series containing tuples instead of a DataFrame:

>>> s.str.partition('-', expand=False)
0    (Linda van der Berg, , )
1    (George Pitt, -, Rivers)
dtype: object

Also available on indices:

>>> idx = pd.Index(['X 123', 'Y 999'])
>>> idx
Index(['X 123', 'Y 999'], dtype='object')

Which will create a MultiIndex:

>>> idx.str.partition()
MultiIndex([('X', ' ', '123'),
            ('Y', ' ', '999')],
           )

Or an index with tuples with expand=False:

>>> idx.str.partition(expand=False)
Index([('X', ' ', '123'), ('Y', ' ', '999')], dtype='object')