def METHOD_NAME():
    int_values = [3, 1, 1, 2, 1, 1, 1, 1, 6, 5]
    cat_values = ["a", "d", "b", "c", "d", "d", "d", "c", "b", "c"]
    df = cudf.DataFrame({"filter_col": int_values, "cat_col": cat_values})
    df_filter = df[df["filter_col"] == 1]
    df_filter["cat_col"] = LabelEncoder().fit_transform(df_filter["cat_col"])
    filtered_int_values = [
        int_values[i] for i in range(len(int_values)) if int_values[i] == 1
    ]
    filtered_cat_values = [
        cat_values[i] for i in range(len(int_values)) if int_values[i] == 1
    ]
    df_test = cudf.DataFrame(
        {"filter_col": filtered_int_values, "cat_col": filtered_cat_values}
    )
    df_test["cat_col"] = LabelEncoder().fit_transform(df_test["cat_col"])
    assert (df_filter["cat_col"].values == df_test["cat_col"].values).all()