def extract_merged_dataframe(df, num_col_df1, num_col_df2, col_df1, col_df2, joinkey_df1=None, joinkey_df2=None):
    """Extract data in some columns from the merged dataframe. Check for different pandas merged result formats.

    :param df: merged dataframe.
    :param num_col_df1:
    :param num_col_df2:
    :param col_df1: (list of int) column position in df1 to keep (0-based).
    :param col_df2: (list of int) column position in df2 to keep (0-based).
    :param joinkey_df1:  (list of int) column position (0-based).
    :param joinkey_df2:  (list of int) column position (0-based).
    :return: extracted data from df.
    """

    col_df1 = np.array(col_df1)
    col_df2 = np.array(col_df2)

    if df.shape[1] == num_col_df1 + num_col_df2: # merging keeps same old columns
        col_df2 += num_col_df1
    elif df.shape[1] == num_col_df1 + num_col_df2 + 1: # merging add column 'key_0' to the head
        col_df1 += 1
        col_df2 += num_col_df1 + 1
    elif df.shape[1] <= num_col_df1 + num_col_df2 - 1: # merging deletes (possibly many) duplicated "join-key" columns in df2, keep and do not change order columns in df1.
        raise ValueError('Format for merged result is too complicated.')
    else:
        raise ValueError('Undefined format for merged result.')

    return df.iloc[:, np.concatenate((col_df1, col_df2))]