# vim: set encoding=utf-8

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#
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def unflatten_columns (self, columns, delimiter=","):
    """
    Compacts data from multiple rows based on cell data.

    Parameters
    ----------

    :param columns: (str or List[str]) Name of the column(s) to be used as keys for unflattening.
    :param delimiter: (Optional[str]) Separator for the data in the result columns.  Default is comma (,).

    Groups together cells in all columns (less the composite key) using "," as string delimiter.
    The original rows are deleted.
    The grouping takes place based on a composite key created from cell values.
    The column datatypes are changed to string.

    Examples
    --------


    Given a data file::

        user1 1/1/2015 1 70
        user1 1/1/2015 2 60
        user2 1/1/2015 1 65

    The commands to bring the data into a frame, where it can be worked on:

        >>> frame.inspect()
        [#]  a      b         c  d
        ===========================
        [0]  user1  1/1/2015  1  70
        [1]  user1  1/1/2015  2  60
        [2]  user2  1/1/2015  1  65


    Unflatten the data using columns a & b:

        >>> frame.unflatten_columns(['a','b'])
        [===Job Progress===]

    Check again:

        >>> frame.inspect()
        [#]  a      b         c    d
        ================================
        [0]  user1  1/1/2015  1,2  70,60
        [1]  user2  1/1/2015  1    65

    Alternatively, unflatten_columns() also accepts a single column like:


        >>> frame.unflatten_columns('a')
        [===Job Progress===]

        >>> frame.inspect()
        [#]  a      b                  c    d
        =========================================
        [0]  user1  1/1/2015,1/1/2015  1,2  70,60
        [1]  user2  1/1/2015           1    65

    """
    if not isinstance(columns, list):
        columns = [columns]
    return self._scala.unflattenColumns(self._tc.jutils.convert.to_scala_list_string(columns),
                                        delimiter)