def pivot_samples(self, values, index="ID_REF"):
        """Pivot samples by specified column.

        Construct a table in which columns (names) are the samples, index
        is a specified column eg. ID_REF and values in the columns are of one
        specified type.

        Args:
            values (:obj:`str`): Column name present in all GSMs.
            index (:obj:`str`, optional): Column name that will become an index in
                pivoted table. Defaults to "ID_REF".

        Returns:
            :obj:`pandas.DataFrame`: Pivoted data

        """
        data = []
        for gsm in self.gsms.values():
            tmp_data = gsm.table.copy()
            tmp_data["name"] = gsm.name
            data.append(tmp_data)
        ndf = concat(data).pivot(index=index, values=values, columns="name")
        return ndf
def pivot_samples ( self , values , index = "ID_REF" ) : data = [ ] for gsm in self . gsms . values ( ) : tmp_data = gsm . table . copy ( ) tmp_data [ "name" ] = gsm . name data . append ( tmp_data ) ndf = concat ( data ) . pivot ( index = index , values = values , columns = "name" ) return ndf
Pivot samples by specified column.

        Construct a table in which columns (names) are the samples, index
        is a specified column eg. ID_REF and values in the columns are of one
        specified type.

        Args:
            values (:obj:`str`): Column name present in all GSMs.
            index (:obj:`str`, optional): Column name that will become an index in
                pivoted table. Defaults to "ID_REF".

        Returns:
            :obj:`pandas.DataFrame`: Pivoted data