Step 7 - Isolate max and min salary algorithms

datastats/datastats.py

@@ -22,25 +22,27 @@ def _avg_yearly_increase(self, data, iage, isalary):
 
         return math.floor(average_salary_increase/average_age_increase)
 
-    def _stats(self, data, iage, isalary):
+    def _max_salary(self, data):
         # Compute max salary
         salaries = [int(e['salary'][1:]) for e in data]
         threshold = '£' + str(max(salaries))
 
-        max_salary = [e for e in data if e['salary'] == threshold]
+        return [e for e in data if e['salary'] == threshold]
 
+    def _min_salary(self, data):
         # Compute min salary
         salaries = [int(d['salary'][1:]) for d in data]
-        min_salary = [e for e in data if e['salary'] ==
-                      '£{}'.format(str(min(salaries)))]
+        return [e for e in data if e['salary'] ==
+                '£{}'.format(str(min(salaries)))]
 
+    def _stats(self, data, iage, isalary):
         return {
             'avg_age': self._avg_age(data),
             'avg_salary': self._avg_salary(data),
             'avg_yearly_increase': self._avg_yearly_increase(
                 data, iage, isalary),
-            'max_salary': max_salary,
-            'min_salary': min_salary
+            'max_salary': self._max_salary(data),
+            'min_salary': self._min_salary(data)
         }
 
     def stats(self, data, iage, isalary):

tests/test_datastats.py

@@ -99,3 +99,29 @@ def test__avg_yearly_increase():
     ds = DataStats()
 
     assert ds._avg_yearly_increase(test_data, 20, 20000) == 837
+
+
+def test__max_salary():
+
+    ds = DataStats()
+
+    assert ds._max_salary(test_data) == [{
+        "id": 3,
+        "name": "Garth",
+        "surname": "Fields",
+        "age": 70,
+        "salary": "£70472"
+    }]
+
+
+def test__min_salary():
+
+    ds = DataStats()
+
+    assert ds._min_salary(test_data) == [{
+        "id": 1,
+        "name": "Laith",
+        "surname": "Simmons",
+        "age": 68,
+        "salary": "£27888"
+    }]