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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 make_jagged_equity_info(num_assets, start_date, first_end, frequency, periods_between_ends, auto_close_delta):
 """ Create a DataFrame representing assets that all begin at the same start date, but have cascading end dates. Parameters num_assets : int How many assets to create. start_date : pd.Timestamp The start date for all the assets. first_end : pd.Timestamp The date at which the first equity will end. frequency : str or pd.tseries.offsets.Offset (e.g. trading_day) Frequency used to interpret the next argument. periods_between_ends : int Starting after the first end date, end each asset every `frequency` * `periods_between_ends`. Returns ------- info : pd.DataFrame DataFrame representing newly-created assets. """

    frame = pd.DataFrame(
        {
            'symbol': [chr(ord('A') + i) for i in range(num_assets)],
            'start_date': start_date,
            'end_date': pd.date_range(
                first_end,
                freq=(periods_between_ends * frequency),
                periods=num_assets,
            ),
            'exchange': 'TEST',
        },
        index=range(num_assets),
    )

    # Explicitly pass None to disable setting the auto_close_date column.
    if auto_close_delta is not None:
        frame['auto_close_date'] = frame['end_date'] + auto_close_delta

    return frame