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._repr_html_()
assert vis.mark == "bar"
def test_display_Vis():
df = pd.read_csv("lux/data/car.csv")
vis = Vis(["Horsepower", "Acceleration"], df)
vis._repr_html_()
def test_display_Vis(global_var):
df = pytest.car_df
vis = Vis(["Horsepower", "Acceleration"], df)
vis._repr_html_()
