def test_remove(): from lux.view.View import View df = pd.read_csv("lux/data/car.csv") view = View(["Horsepower", "Horsepower"]) view.load(df) view.remove_column_from_spec_new("Horsepower", remove_first=False) assert (view.spec_lst == []), "Remove all instances of Horsepower" df = pd.read_csv("lux/data/car.csv") view = View(["Horsepower", "Horsepower"]) view.load(df) view.remove_column_from_spec_new("Horsepower", remove_first=True) assert (len(view.spec_lst) == 1), "Remove only 1 instances of Horsepower" assert (view.spec_lst[0].attribute == "Horsepower" ), "Remove only 1 instances of Horsepower"
def test_refresh_inplace(): df = pd.DataFrame({ 'date': ['2020-01-01', '2020-02-01', '2020-03-01', '2020-04-01'], 'value': [10.5, 15.2, 20.3, 25.2] }) assert df.data_type['nominal'][0] == 'date' from lux.view.View import View view = View(["date", "value"]) view.load(df) df['date'] = pd.to_datetime(df['date'], format="%Y-%m-%d") assert df.data_type['temporal'][0] == 'date'
def test_vary_filter_val(): df = pd.read_csv("lux/data/olympic.csv") view = View(["Height", "SportType=Ball"]) view = view.load(df) df.set_context_as_view(view) df.show_more() assert len( df.recommendation["Filter"]) == len(df["SportType"].unique()) - 1