pandas.Series.str.partition#

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

Split the string at the first occurrence ofsep.

This method splits the string at the first occurrence ofsep,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 ofsep.

Series.str.split

Split strings around given separators.

str.partition

Standard library version.

Examples

>>>s=pd.Series(['Linda van der Berg','George Pitt-Rivers'])>>>s0    Linda van der Berg1    George Pitt-Riversdtype: object

>>>s.str.partition()        0  1             20   Linda     van der Berg1  George      Pitt-Rivers

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

>>>s.str.rpartition()               0  1            20  Linda van der            Berg1         George     Pitt-Rivers

To partition by something different than a space:

>>>s.str.partition('-')                    0  1       20  Linda van der Berg1         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'])>>>idxIndex(['X 123', 'Y 999'], dtype='object')

Which will create a MultiIndex:

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

Or an index with tuples withexpand=False:

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