def test_text_not_overridden(): from lux.vis.Vis import Vis df = pd.read_csv("lux/data/college.csv") vis = Vis(["Region", "Geography"], df) vis._ipython_display_() code = vis.to_altair() assert 'color = "#ff8e04"' in code
def test_vis_set_intent(global_var): from lux.vis.Vis import Vis df = pytest.car_df vis = Vis(["Weight", "Horsepower"], df) vis._ipython_display_() assert "Horsepower" in str(vis._code) vis.intent = ["Weight", "MilesPerGal"] vis._ipython_display_() assert "MilesPerGal" in str(vis._code)
def test_vis_private_properties(global_var): from lux.vis.Vis import Vis df = pytest.car_df vis = Vis(["Horsepower", "Weight"], df) vis._ipython_display_() assert isinstance(vis.data, lux.core.frame.LuxDataFrame) with pytest.raises(AttributeError, match="can't set attribute"): vis.data = "some val" assert isinstance(vis.code, dict) with pytest.raises(AttributeError, match="can't set attribute"): vis.code = "some val" assert isinstance(vis.min_max, dict) with pytest.raises(AttributeError, match="can't set attribute"): vis.min_max = "some val" assert vis.mark == "scatter" with pytest.raises(AttributeError, match="can't set attribute"): vis.mark = "some val"
def test_apply_nan_filter(): from lux.vis.Vis import Vis import numpy as np dataset = [ {"fully_nan": np.nan, "some_nan": 3.0, "some_nan2": np.nan}, {"fully_nan": np.nan, "some_nan": 15.0, "some_nan2": 3.0}, {"fully_nan": np.nan, "some_nan": np.nan, "some_nan2": 3.0}, {"fully_nan": np.nan, "some_nan": 7.0, "some_nan2": 0.0}, {"fully_nan": np.nan, "some_nan": 2.0, "some_nan2": 2.0}, {"fully_nan": np.nan, "some_nan": 3.0, "some_nan2": np.nan}, {"fully_nan": np.nan, "some_nan": 1.0, "some_nan2": 1.0}, {"fully_nan": np.nan, "some_nan": 1.0, "some_nan2": 1.0}, {"fully_nan": np.nan, "some_nan": 2.0, "some_nan2": 0.0}, {"fully_nan": np.nan, "some_nan": 11.0, "some_nan2": 0.0}, ] test = pd.DataFrame(dataset) vis = Vis(["some_nan", "some_nan2=nan"], test) vis._ipython_display_() assert vis.mark == "bar"
def test_display_Vis(global_var): df = pytest.car_df vis = Vis(["Horsepower", "Acceleration"], df) vis._ipython_display_()