Esempio n. 1
0
def test_replace_output(test_input):
    outlier = HandleOutlier()
    outlier.handle_outliers(params=test_input)
    assert test_input["train_df"].shape == train_df.shape
    assert -999 in test_input["train_df"]["Distance"].values
    assert "-999" not in test_input["train_df"]["Capitals"].values
    assert "-999" not in test_input["train_df"]["Other Capitals"].values
def test_incorrect_input_key():
    with pytest.raises(KeyError):
        outlier = HandleOutlier()
        outlier.handle_outliers(params={
            "train_df": train_df,
            "cols": ["Place"]
        })
def test_true_arguments():
    with pytest.raises(ArgumentsError):
        outlier = HandleOutlier()
        outlier.handle_outliers(params={
            "train_df": train_df,
            "cols": ["Distance"],
            "replace": True,
        })
Esempio n. 4
0
def test_true_arguments():
    with pytest.raises(ArgumentsError):
        outlier = HandleOutlier()
        outlier.handle_outliers(
            params={
                "train_df": train_df,
                "cat_cols": ["Capitals", "Other Capitals"],
                "replace": True,
            })
def test_false_arguments():
    with pytest.warns(UserWarning):
        outlier = HandleOutlier()
        outlier.handle_outliers(
            params={
                "train_df": train_df,
                "cols": ["Distance"],
                "remove_outliers": False,
                "replace": False,
            })
Esempio n. 6
0
def test_incorrect_input_type(test_input):
    with pytest.raises(TypeError):
        outlier = HandleOutlier()
        outlier.handle_outliers(params=test_input)
Esempio n. 7
0
def test_all(test_input):
    outlier = HandleOutlier()
    outlier.handle_outliers(params=test_input)
    assert -999 in test_input["train_df"]["Distance"].values
    assert -999 in test_input["test_df"]["Distance"].values
    assert test_input["train_df"].equals(test_input["test_df"])
Esempio n. 8
0
def test_removeoutliers_output(test_input):
    outlier = HandleOutlier()
    outlier.handle_outliers(params=test_input)
    assert test_input["train_df"].shape != train_df.shape