def METHOD_NAME(currency_df):
    """Checks that the remove_non_numeric parameter is correctly applied
    with the default cleaning style.
    Note that originally empty strings are retained, and always remain
    as NaN.
    """
    result = currency_df.currency_column_to_numeric(
        "d_col",
        cast_non_numeric={"non-existent-col": 10},
        remove_non_numeric=True,
    )
    expected = pd.DataFrame(
        {
            "a_col": [" 24.56", "(12.12)", "1,000,000"],
            "d_col": [np.nan, 1.23, -1_000],
        },
        index=[0, 2, 3],
    )
    assert_frame_equal(result, expected)