pandas.Series.str.partition#

Series.str.partition(sep=' ', expand=True)[source] #

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

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')