def test_arideda_empty_df():
"""
Test if error occurs when repsonse type is not categorical or continuous
"""
with pytest.raises(AssertionError):
aa.arid_eda(
data.iris(),
"species",
"ORDINAL",
["sepalLength", "sepalWidth"])
def test_response_type_incorrect():
"""
Test if an error occurs when wrong response type is given
"""
with pytest.raises(AssertionError):
aa.arid_eda(
data.iris(),
"petalLength",
"categorical",
["sepalLength", "sepalWidth"]
)
def test_arideda_numfeature():
"""
Ensure data frame is appropriate size according to features
"""
features = ["sepalLength", "sepalWidth"]
out, _ = aa.arid_eda(data.iris(), "species", "categorical", features)
assert out.shape == (8, len(features))
def test_arideda_features():
"""
Test calling with valid features list
"""
out, _ = aa.arid_eda(
data.iris(), "species", "categorical", ["sepalLength", "sepalWidth"]
)
assert isinstance(out, pd.core.frame.DataFrame)
def test_arideda_return():
"""
Test return data type
"""
_, out = aa.arid_eda(
data.iris(), "species", "categorical", ["sepalLength", "sepalWidth"]
)
assert isinstance(out, alt.HConcatChart)
def test_arideda_returns_tuple():
"""
Check that function returns two items
"""
assert (
len(
aa.arid_eda(
data.iris(),
"species",
"categorical",
["sepalLength", "sepalWidth"]
)
)
== 2
)