def test_RHDI_wrong_type(self):
"""
Negative test
data: Series (unsupported type)
Checks that the random_hot_deck_imputation raises a TypeError if the
data is passed as a series.
"""
# 1. Arrange
data = generate_example_series()
# 2. Act & 3. Assert
with self.assertRaises(TypeError):
random_hot_deck_imputation(data,
incomplete_variable='a',
deck_variables=['b'],
inplace=True)
def test_RHDI_wrong_incomplete_variable(self):
"""
Negative test
data: Correct dataframe (hotdeck)
incomplete_variable: 'z' (doesn't exist in the data)
Checks that random_hot_deck_imputation raises a ValueError if the
given incomplete variable doesn't exist in the data.
"""
# 1. Arrange
data = generate_example_df_hotdeck()
# 2. Act & 3. Assert
with self.assertRaises(ValueError):
random_hot_deck_imputation(data,
incomplete_variable='z',
deck_variables=['b'],
inplace=True)
def test_RHDI_inplace(self):
"""
Positive test
data: Correct dataframe (hotdeck)
Checks that random_hot_deck_imputation removes 2 NA values from the
dataframe.
"""
# 1. Arrange
df = generate_example_df_hotdeck()
# 2. Act
random_hot_deck_imputation(df,
incomplete_variable='a',
deck_variables=['b'],
inplace=True)
# 3. Assert
self.assertEqual(df.isna().sum().sum(), 1)
def test_RHDI_returning(self):
"""
Positive test
data: Correct dataframe (hotdeck)
Checks that the original dataframe remains unmodified and that the
returned dataframe contains 1 NA value, 2 less than the original.
"""
# 1. Arrange
df = generate_example_df_hotdeck()
# 2. Act
df2 = random_hot_deck_imputation(df,
incomplete_variable='a',
deck_variables=['b'],
inplace=False)
# 3. Assert
self.assertEqual(df.isna().sum().sum(), 3)
self.assertEqual(df2.isna().sum().sum(), 1)
def test_RHDI_no_donors(self):
"""
Negative test
data: Correct dataframe (hotdeck)
incomplete_variable: a
deck_variables: ['b', 'c']
Checks that no NA value gets removed because no row coincides in
value for the variable c.
"""
# 1. Arrange
df = generate_example_df_hotdeck()
# 2. Act
df2 = random_hot_deck_imputation(df,
incomplete_variable='a',
deck_variables=['b', 'c'],
inplace=False)
# 3. Assert
self.assertEqual(df.isna().sum().sum(), 3)
self.assertEqual(df2.isna().sum().sum(), 3)