Create weighted_kayraemre_karaosmanoglu.py

Week02/weighted_kayraemre_karaosmanoglu.py

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+import random
+def weighted_srs(data, n, weights, with_replacement=False):
+    w = weights if weights else [1]*len(data)
+    if with_replacement or weights:
+        return random.choices(data, weights=w, k=n)
+    res, d_c = [], list(data)
+    for _ in range(n): res.append(d_c.pop(random.randrange(len(d_c))))
+    return res
+

Week03/shifted_kayraemre_karaosmanoglu.py

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+import statistics
+
+def shifted(data):
+  mean = statistics.mean(data)
+  median = statistics.median(data)
+  return abs(mean - median) / abs(mean) * 100 if mean != 0 else 0

weighted_kayraemre_karaosmanoglu,py

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+import random
+
+def weighted_srs(data, n, weights, with_replacement=False):
+    if with_replacement: return random.choices(data, weights=weights, k=n)
+    if not weights: return random.sample(data, n)
+    return random.sample(data, n, counts=weights)