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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 merge_data(*data_frames, **kwargs):
 """ Merge DataFrames by column. Number of rows in tables must be the same. This method can be called both outside and as a DataFrame method. :param list[DataFrame] data_frames: DataFrames to be merged. :param bool auto_rename: if True, fields in source DataFrames will be renamed in the output. :return: merged data frame. :rtype: DataFrame :Example: """

    from .specialized import build_merge_expr
    from ..utils import ML_ARG_PREFIX

    if len(data_frames) <= 1:
        raise ValueError('Count of DataFrames should be at least 2.')

    norm_data_pairs = []
    df_tuple = collections.namedtuple('MergeTuple', 'df cols exclude')
    for pair in data_frames:
        if isinstance(pair, tuple):
            if len(pair) == 2:
                df, cols = pair
                exclude = False
            else:
                df, cols, exclude = pair
            if isinstance(cols, six.string_types):
                cols = cols.split(',')
        else:
            df, cols, exclude = pair, None, False
        norm_data_pairs.append(df_tuple(df, cols, exclude))

    auto_rename = kwargs.get('auto_rename', False)

    sel_cols_dict = dict((idx, tp.cols) for idx, tp in enumerate(norm_data_pairs) if tp.cols and not tp.exclude)
    ex_cols_dict = dict((idx, tp.cols) for idx, tp in enumerate(norm_data_pairs) if tp.cols and tp.exclude)

    merge_expr = build_merge_expr(len(norm_data_pairs))
    arg_dict = dict(_params={'autoRenameCol': str(auto_rename)},
                    selected_cols=sel_cols_dict, excluded_cols=ex_cols_dict)
    for idx, dp in enumerate(norm_data_pairs):
        arg_dict[ML_ARG_PREFIX + 'input%d' % (1 + idx)] = dp.df

    out_df = merge_expr(register_expr=True, _exec_id=uuid.uuid4(), _output_name='output', **arg_dict)

    out_df._ml_uplink = [dp.df for dp in norm_data_pairs]
    out_df._perform_operation(op.MergeFieldsOperation(auto_rename, sel_cols_dict, ex_cols_dict))
    out_df._rebuild_df_schema()
    return out_df