pandas_paddles.paddles.str_join#

pandas_paddles.paddles.str_join(sep, col1, *cols)[source]#

Create expression to join multiple columns in a string.

This is similar to str.join

Parameters

  • sep (str) – The separator

  • col1 (Union[str, pandas_paddles.contexts.DataframeContext]) –

    The columns to be joined. These can be either str or DF-expressions. If a str is passed, it’s taken as column name and the respective DF-expression is created.

    In both cases the expression is first casted to str using pandas.Series.astype().

  • cols (Union[str, pandas_paddles.contexts.DataframeContext]) –

    The columns to be joined. These can be either str or DF-expressions. If a str is passed, it’s taken as column name and the respective DF-expression is created.

    In both cases the expression is first casted to str using pandas.Series.astype().

Returns

The DF-expression, a callable taking a DataFrame as argument.

Return type

DataframeContext

Examples

Reference columns with their names:

>>> df = pd.DataFrame({"a": list("abc"), "b": list("XYZ"), "c": range(3)})
>>> df.assign(a_plus_b=str_join("+", "a", "b"))
   a  b  c a_plus_b
0  a  X  0      a+X
1  b  Y  1      b+Y
2  c  Z  2      c+Z

Reference columns with DF-expressions:

>>> df.assign(a_plus_b=str_join("+", "a", DF["b"].str.lower()))
   a  b  c a_plus_b
0  a  X  0      a+x
1  b  Y  1      b+y
2  c  Z  2      c+z

Non-string columns are converted:

>>> df.assign(a_plus_c=str_join("+", "a", "c"))
   a  b  c a_plus_b
0  a  X  0      a+0
1  b  Y  1      b+1
2  c  Z  2      c+2

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