pandas.Series.str.cat¶
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.
- param others
- Series, 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. 
 
- param sep
- str, default ‘’
- The separator between the different elements/columns. By default the empty string ‘’ is used. 
 
- param na_rep
- str 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. 
 
 
 
- param 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. 
 
- return
- str, Series or Index If others is None, str is returned, otherwise a Series/Index (same type as caller) of objects is returned. 
Warning
This feature is currently unsupported by Intel Scalable Dataframe Compiler