def test_clean_testData(self):
"""
Test the test data
Data about test. I don't have the master subjects/test.Assuming all the data
valid except null or blank
TODO: Also I can put some checks if the data is normalized
"""
validData = {'student_id': [1, 2, 3, 4, 5],
'score': [1, 2, 3, 4, 5.0],
'grade': ['4', '3', 'K', '2', '1'],
'test': ['reading', 'Reading', 'Math', 'math', 'Math'],
'district': ['f', 'f', 't', 'true', 'TruE'] }
inValidData = {'student_id': [1, 2, 3, 4, 5],
'score': [1, 2, 3, 4, 5.0],
'grade': ['4', '3', 'K', '2', '1'],
'test': ['reading', 'Reading', 'Math', '', 'Math'],
'district': ['f', 'f', 't', 'true', 'TruE'] }
# Invalid Data
# conatains some blank data
res = studentData.data_import(pd.DataFrame(inValidData))
self.assertEqual(len(res), 4)
# Valid Data
res = studentData.data_import(pd.DataFrame(validData))
self.assertEqual(len(res), 5)
def test_data_fields(self):
"""
Test the file header.
This checks if we have all the field names we expect in data
"""
incompleteData = {'student_id': [1, 2, 3, 4, 5],
'score': [1, 2, 3, 4, 5.0],
'grade': ['4', '3', 'K', '2', '1']}
validData = {'student_id': [1, 2, 3, 4, 5],
'score': [1, 2, 3, 4, 5.0],
'grade': ['4', '3', 'K', '2', '1'],
'test': ['reading', 'Reading', 'Math', 'math', 'Math'],
'district': ['f', 'f', 't', 'true', 'TruE'] }
# No data
# We are unable to read data from the file
res = studentData.data_import()
self.assertEqual(isinstance(res ,pd.DataFrame),True)
# Incomplete Data
# data does not have all the fields we expect
df = pd.DataFrame(incompleteData)
res = studentData.data_import(df)
self.assertNotEqual(isinstance(res, pd.DataFrame),True)
# Valid Data
df = pd.DataFrame(validData)
res = studentData.data_import(df)
self.assertEqual(isinstance(res, pd.DataFrame),True)
def test_clean_score(self):
"""
Test the score data
Assuning valid scores are between 9 to 5.0
"""
validData = {'student_id': [1, 2, 3, 4, 5],
'score': [1, 2, 3, 4, 5.0],
'grade': ['4', '3', 'K', '2', '1'],
'test': ['reading', 'Reading', 'Math', 'math', 'Math'],
'district': ['f', 'f', 't', 'true', 'TruE'] }
inValidData = {'student_id': [1, 2, 3, 4, 5],
'score': [1, 2, 5.3, 4, 5.0],
'grade': ['4', '3', 'K', '2', '1'],
'test': ['reading', 'Reading', 'Math', 'ReAding', 'Math'],
'district': ['f', 'f', 't', 'true', 'TruE'] }
# Invalid Data
res = studentData.data_import(pd.DataFrame(inValidData))
self.assertEqual(len(res), 4)
# Valid Data
res = studentData.data_import(pd.DataFrame(validData))
self.assertEqual(len(res), 5)
def test_clean_grade(self):
"""
Test the grade data
Assuming K and then 1-12 is valid data
"""
validData = {'student_id': [1, 2, 3, 4, 5],
'score': [1, 2, 3, 4, 5.0],
'grade': ['4', '3', 'K', '2', '1'],
'test': ['reading', 'Reading', 'Math', 'math', 'Math'],
'district': ['f', 'f', 't', 'true', 'TruE'] }
inValidData = {'student_id': [1, 2, 3, 4, 5],
'score': [1, 2, 3, 4, 5.0],
'grade': ['4', '3', 'K', '2', '13'],
'test': ['reading', 'Reading', 'Math', 'ReAding', 'Math'],
'district': ['f', 'f', 't', 'true', 'TruE'] }
# Invalid Data
res = studentData.data_import(pd.DataFrame(inValidData))
self.assertEqual(len(res), 4)
# Valid Data
res = studentData.data_import(pd.DataFrame(validData))
self.assertEqual(len(res), 5)
def test_duplicate_date(self):
"""
Test the duplicate data
Assuming student id, grade and test are keys to determine the unique record
"""
validData = {'student_id': [1, 2, 3, 4, 5],
'score': [1, 2, 3, 4, 5.0],
'grade': ['4', '3', 'K', '2', '1'],
'test': ['reading', 'Reading', 'Math', 'math', 'Math'],
'district': ['f', 'f', 't', 'true', 'TruE'] }
inValidData = {'student_id': [1, 1, 3, 4, 5],
'score': [1, 2, 1.2, 4, 5.0],
'grade': ['4', '4', 'K', '2', '1'],
'test': ['reading', 'Reading', 'Math', 'ReAding', 'Math'],
'district': ['f', 'f', 't', 'true', 'TruE'] }
# Invalid Data
res = studentData.data_import(pd.DataFrame(inValidData))
self.assertEqual(len(res), 4)
# Valid Data
res = studentData.data_import(pd.DataFrame(validData))
self.assertEqual(len(res), 5)
