partition(self, sep=' ', expand=True)

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

sep : str, default whitespace

String to split on.

expand : bool, default True

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

Returns

DataFrame/MultiIndex or Series/Index of objects

Split the string at the first occurrence of sep .

See Also

Series.str.split

Split strings around given separators.

rpartition

Split the string at the last occurrence of :None:None:`sep`.

str.partition

Standard library version.

Examples

This example is valid syntax, but we were not able to check execution

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

This example is valid syntax, but we were not able to check execution

>>> 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:

This example is valid syntax, but we were not able to check execution

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

To partition by something different than a space:

This example is valid syntax, but we were not able to check execution

>>> 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:

This example is valid syntax, but we were not able to check execution

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

Also available on indices:

This example is valid syntax, but we were not able to check execution

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

Which will create a MultiIndex:

This example is valid syntax, but we were not able to check execution

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

Or an index with tuples with expand=False :

This example is valid syntax, but we were not able to check execution

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

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

pandas.core.strings.accessor.StringMethods.rpartition

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