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
