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_()
