Task

TEMA8/Task.md

@@ -27,29 +27,19 @@ def mod1(filename):
 __Модуль2__
 _Код:_
 ```py
+import statistics
+
 def mod2(list1, list2):
     n = min(len(list1), len(list2))
     if n == 0:
         return 0.0
+    x = list1[:n]
+    y = list2[:n]
     
-    avg1 = sum(list1[:n]) / n
-    avg2 = sum(list2[:n]) / n
-    
-    numerator = 0
-    denom1 = 0
-    denom2 = 0
-    
-    for i in range(n):
-        diff1 = list1[i] - avg1
-        diff2 = list2[i] - avg2
-        numerator += diff1 * diff2
-        denom1 += diff1 * diff1
-        denom2 += diff2 * diff2
-
-    if denom1 == 0 or denom2 == 0:
-        return 0.0
-
-    correlation = numerator / ((denom1 * denom2) ** 0.5)
+    try:
+        correlation = statistics.correlation(x, y)
+    except statistics.StatisticsError:
+        correlation = 0.0
     
     return correlation
 ```

TEMA8/TaskMod2.py

@@ -1,25 +1,15 @@
+import statistics
+
 def mod2(list1, list2):
     n = min(len(list1), len(list2))
     if n == 0:
         return 0.0
+    x = list1[:n]
+    y = list2[:n]
     
-    avg1 = sum(list1[:n]) / n
-    avg2 = sum(list2[:n]) / n
-    
-    numerator = 0
-    denom1 = 0
-    denom2 = 0
-    
-    for i in range(n):
-        diff1 = list1[i] - avg1
-        diff2 = list2[i] - avg2
-        numerator += diff1 * diff2
-        denom1 += diff1 * diff1
-        denom2 += diff2 * diff2
-
-    if denom1 == 0 or denom2 == 0:
-        return 0.0
-
-    correlation = numerator / ((denom1 * denom2) ** 0.5)
+    try:
+        correlation = statistics.correlation(x, y)
+    except statistics.StatisticsError:
+        correlation = 0.0
     
     return correlation