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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 _extract_from(raw_json, pandas_options=None):
    '''Extract tables from json.

    Args:
        raw_json (list):
            Decoded list from tabula-java JSON.
        pandas_options (dict optional):
            pandas options for `pd.DataFrame()`
    '''

    data_frames = []
    if pandas_options is None:
        pandas_options = {}

    columns = pandas_options.pop('columns', None)
    columns, header_line_number = _convert_pandas_csv_options(pandas_options, columns)

    for table in raw_json:
        list_data = [[np.nan if not e['text'] else e['text'] for e in row] for row in table['data']]
        _columns = columns

        if isinstance(header_line_number, int) and not columns:
            _columns = list_data.pop(header_line_number)
            _columns = ['' if e is np.nan else e for e in _columns]

        data_frames.append(pd.DataFrame(data=list_data, columns=_columns, **pandas_options))

    return data_frames