@staticmethod
def clean_data(star_schema_df, measures):
    """measure like this: 1 349 is not numeric so we try to transform it to
        1349.

        :param star_schema_df: start schema dataframe
        :param measures: list of measures columns names

        :return: cleaned columns
        """
    if measures:
        for measure in measures:
            if star_schema_df[measure].dtype == object:
                star_schema_df[measure] = star_schema_df[measure].str.replace(
                    ' ', '')
                try:
                    star_schema_df[measure] = star_schema_df[measure].astype(
                        'float')
                except ValueError:
                    star_schema_df = star_schema_df.drop(measure, 1)
    return star_schema_df
