def METHOD_NAME(num_rows, num_cols):
    # this tests an edge case where we used to select exactly num_cols / 2 + 1 columns
    # from both the front and the back of the dataframe, but the dataframe is such a
    # length that the front and back columns overlap at one column. The result is that
    # we convert one column twice to pandas, although we would never see the duplicate
    # column in the output because pandas would also only represent the num_cols / 2
    # columns from the front and back.
    df = pd.DataFrame([list(range(4)) for _ in range(4)])
    pandas_repr_df = df._build_repr_df(num_rows, num_cols)
    assert pandas_repr_df.columns.is_unique
    assert pandas_repr_df.index.is_unique