pandas.Series.str.cat#

Series.str.cat(others=None, sep=None, na_rep=None, join='left')[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:

othersSeries, Index, DataFrame, np.ndarray 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, Index or np.ndarray (1-dim), 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.

sepstr, default ‘’

The separator between the different elements/columns. By default the empty string ‘’ is used.

na_repstr 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 ‘left’

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). To disable alignment, use .values on any Series/Index/DataFrame in others.

Returns:

str, Series or Index: 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.
join: Join lists contained as elements 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="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.