def test_find_type(create_df, get_check_list):
expected_output = [{
'gender': [{
'percenatge': {
'male': '25.00%',
'female': '25.00%',
'Nan': '25.00%',
'null': '25.00%'
}
}, {
'nan': {
'number': 2,
'percenatge': '50.00%'
}
}]
}, {
'birthdate': [{
'nan': {
'number': 1,
'percenatge': '25.00%'
}
}]
}]
assert auditor.Auditor().find_type(create_df,
get_check_list) == expected_output
def test_compare_distributions():
expected_output = {
'ks_test': {
'statistic': 1.0,
'pvalue': 0.011065637015803861
}
}
assert auditor.Auditor().compare_distributions(
[1, 2, 3, 4], [5, 6, 9, 8]) == expected_output
def test_find_percentage():
expected_output = {
'percenatge': {
'male': '25.00%',
'female': '25.00%',
'Nan': '25.00%',
'null': '25.00%'
}
}
assert auditor.Auditor().find_percentage(
'gender', ['null', 'Nan', 'male', 'female']) == expected_output
def test_apply_predefined_distribution_check():
expected_output = {
'normal': {
'ks_test': {
'statistic': 0.8396,
'pvalue': 0.002544122126156039
}
}
}
assert auditor.Auditor().apply_predefined_distribution_check(
[1, 2, 3, 4],
dist_type="normal",
dist_charecteristics={
"mean": 1999,
"std": 2000
}) == expected_output
def test_check_total_nans(total_nans_df):
expected_output = [{
'Patient': [{
'identifier': {
'nan': {
'number': 0,
'percenatge': '0.00%'
}
}
}, {
'gender': {
'nan': {
'number': 2,
'percenatge': '50.00%'
}
}
}, {
'birthdate': {
'nan': {
'number': 1,
'percenatge': '25.00%'
}
}
}, {
'address': {
'nan': {
'number': 1,
'percenatge': '25.00%'
}
}
}]
}]
expected_output = expected_output[0]['Patient'][0]
output = auditor.Auditor().check_total_nans('Patient', total_nans_df)
output = output[0]['Patient'][0]
assert output['identifier'] == expected_output['identifier']
def test_check_nan(create_df):
expected_output = {'nan': {'number': 2, 'percenatge': '50.00%'}}
attr_value = create_df['gender'].values
assert auditor.Auditor().check_nan(attr_value) == expected_output
def test_find_mean():
assert auditor.Auditor().find_mean([2, 4, 3]) == {'mean': 3}
def test_find_mean_error():
with pytest.raises(TypeError):
auditor.Auditor().find_mean([2, "f", 3])
def test_find_maximum():
assert auditor.Auditor().find_maximum([2, nan, 3]) == {'max': 3}
def test_find_maximum_error():
with pytest.raises(TypeError):
auditor.Auditor().find_maximum([2, "f", 3])
def test_find_minimum():
assert auditor.Auditor().find_minimum([2, nan, 3]) == {'min': 2}
def test_find_frequency():
expected_output = {'female': 1, 'male': 2}
assert auditor.Auditor().find_frequency(['female', 'male',
'male']) == expected_output
