pandas.Series.str.cat

Series.str.cat(others=None, sep=None, na_rep=None, join=None) [source]

Concatenate strings in the Series/Index with given separator.

If others is specified, this function concatenates the Series/Index and elements of others element-wise. If others is not passed, then all values in the Series/Index are concatenated into a single string with a given sep.

Parameters:

others : Series, Index, DataFrame, np.ndarrary or list-like Series, Index, DataFrame, np.ndarray (one- or two-dimensional) and other list-likes of strings must have the same length as the calling Series/Index, with the exception of indexed objects (i.e. Series/Index/DataFrame) if join is not None. If others is a list-like that contains a combination of Series, np.ndarray (1-dim) or list-like, then all elements will be unpacked and must satisfy the above criteria individually. If others is None, the method returns the concatenation of all strings in the calling Series/Index. sep : string or None, default None If None, concatenates without any separator. na_rep : string or None, default None Representation that is inserted for all missing values: If na_rep is None, and others is None, missing values in the Series/Index are omitted from the result. If na_rep is None, and others is not None, a row containing a missing value in any of the columns (before concatenation) will have a missing value in the result. join : {‘left’, ‘right’, ‘outer’, ‘inner’}, default None Determines the join-style between the calling Series/Index and any Series/Index/DataFrame in others (objects without an index need to match the length of the calling Series/Index). If None, alignment is disabled, but this option will be removed in a future version of pandas and replaced with a default of ‘left’. To disable alignment, use .values on any Series/Index/DataFrame in others. New in version 0.23.0.

Returns:

concat : str or Series/Index of objects If others is None, str is returned, otherwise a Series/Index (same type as caller) of objects is returned.

See also

split

Split each string in the Series/Index

Examples

When not passing others, all values are concatenated into a single string:

>>> s = pd.Series(['a', 'b', np.nan, 'd'])
>>> s.str.cat(sep=' ')
'a b d'

By default, NA values in the Series are ignored. Using na_rep, they can be given a representation:

>>> s.str.cat(sep=' ', na_rep='?')
'a b ? d'

If others is specified, corresponding values are concatenated with the separator. Result will be a Series of strings.

>>> s.str.cat(['A', 'B', 'C', 'D'], sep=',')
0    a,A
1    b,B
2    NaN
3    d,D
dtype: object

Missing values will remain missing in the result, but can again be represented using na_rep

>>> s.str.cat(['A', 'B', 'C', 'D'], sep=',', na_rep='-')
0    a,A
1    b,B
2    -,C
3    d,D
dtype: object

If sep is not specified, the values are concatenated without separation.

>>> s.str.cat(['A', 'B', 'C', 'D'], na_rep='-')
0    aA
1    bB
2    -C
3    dD
dtype: object

Series with different indexes can be aligned before concatenation. The join-keyword works as in other methods.

>>> t = pd.Series(['d', 'a', 'e', 'c'], index=[3, 0, 4, 2])
>>> s.str.cat(t, join=None, na_rep='-')
0    ad
1    ba
2    -e
3    dc
dtype: object
>>>
>>> s.str.cat(t, join='left', na_rep='-')
0    aa
1    b-
2    -c
3    dd
dtype: object
>>>
>>> s.str.cat(t, join='outer', na_rep='-')
0    aa
1    b-
2    -c
3    dd
4    -e
dtype: object
>>>
>>> s.str.cat(t, join='inner', na_rep='-')
0    aa
2    -c
3    dd
dtype: object
>>>
>>> s.str.cat(t, join='right', na_rep='-')
3    dd
0    aa
4    -e
2    -c
dtype: object

For more examples, see here.