def test_drop_bad_threshold_low():
x = [1, 2, 3, np.nan]
y = [1, 2, 3, 4]
dataframe = pd.DataFrame(list(zip(x, y)))
dataframe.columns = ["x", "y"]
with pytest.raises(ValueError):
utils.drop(dataframe, threshold=-5)
def test_drop_threshold():
x = list(range(50)) + [np.nan]*50
y = [np.nan]*100
z = np.random.random(100)
dataframe = pd.DataFrame(list(zip(x, y, z)))
dataframe.columns = ["x", "y", "z"]
out = utils.drop(dataframe, threshold=0.2)
assert out.columns.tolist() == ["z"]
assert out.shape[0] == dataframe.shape[0]
def test_drop_corrrect_rows():
x = [np.nan]*50
y = np.random.random(50)
z = list(range(49)) + [np.nan]
dataframe = pd.DataFrame(list(zip(x, y, z)))
dataframe.columns = ["x", "y", "z"]
out = utils.drop(dataframe)
assert out.columns.tolist() == ["y", "z"]
assert out.shape[0] == 49
def test_drop_correct():
x = [np.nan]*10
xx = [np.nan]*10
y = list(range(10))
z = list(range(10))
dataframe = pd.DataFrame(list(zip(x, xx, y, z)))
dataframe.columns = ["x", "xx", "y", "z"]
out = utils.drop(dataframe)
assert out.shape[0] == dataframe.shape[0]
assert out.columns.tolist() == ["y", "z"]