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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_df_row(dimensions, naming='label', i=0, record=None):
 """Generate row dimension values for a pandas dataframe. Args: dimensions (list):
 list of pandas dataframes with dimension labels \ generated by get_dim_label or get_dim_index methods. naming (string, optional):
 dimension naming. Possible values: 'label' \ or 'id'. i (int):
 dimension list iteration index. Default is 0, it's used in the \ recursive calls to the method. record (list):
 list of values representing a pandas dataframe row, \ except for the value column. Default is empty, it's used \ in the recursive calls to the method. Yields: list: list with pandas dataframe column values except for value column """


    check_input(naming)
    if i == 0 or record is None:
        record = []
    for dimension in dimensions[i][naming]:
        record.append(dimension)
        if len(record) == len(dimensions):
            yield record

        if i + 1 < len(dimensions):
            for row in get_df_row(dimensions, naming, i + 1, record):
                yield row
        if len(record) == i + 1:
            record.pop()