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')