Series.str.cat(self, 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: |
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Returns: |
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See also
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.
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Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/0.25.0/reference/api/pandas.Series.str.cat.html