cat(self, others=None, sep=None, na_rep=None, join='left') -> 'str | Series | Index'
If :None:None:`others` is specified, this function concatenates the Series/Index and elements of :None:None:`others` element-wise. If :None:None:`others` is not passed, then all values in the Series/Index are concatenated into a single string with a given sep
.
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.
The separator between the different elements/columns. By default the empty string :None:None:`''` is used.
Representation that is inserted for all missing values:
Determines the join-style between the calling Series/Index and any Series/Index/DataFrame in :None:None:`others` (objects without an index need to match the length of the calling Series/Index). To disable alignment, use :None:None:`.values` on any Series/Index/DataFrame in :None:None:`others`.
Changed default of :None:None:`join` from None to :None:None:`'left'`.
If :None:None:`others` is None, :None:None:`str` is returned, otherwise a :None:None:`Series/Index` (same type as caller) of objects is returned.
Concatenate strings in the Series/Index with given separator.
join
Join lists contained as elements in the Series/Index.
split
Split each string in the Series/Index.
When not passing :None:None:`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 :None:None:`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])This example is valid syntax, but we were not able to check execution
... 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 >>>This example is valid syntax, but we were not able to check execution
>>> s.str.cat(t, join='inner', na_rep='-') 0 aa 2 -c 3 dd dtype: object >>>This example is valid syntax, but we were not able to check execution
>>> s.str.cat(t, join='right', na_rep='-') 3 dd 0 aa 4 -e 2 -c dtype: object
For more examples, see here <text.concatenate>
.
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