bpo-40855: Fix ignored mu and xbar parameters (GH-20835)
diff --git a/Lib/statistics.py b/Lib/statistics.py
index c76a6ca..93a4633 100644
--- a/Lib/statistics.py
+++ b/Lib/statistics.py
@@ -682,8 +682,10 @@
calculated from ``c`` as given. Use the second case with care, as it can
lead to garbage results.
"""
- if c is None:
- c = mean(data)
+ if c is not None:
+ T, total, count = _sum((x-c)**2 for x in data)
+ return (T, total)
+ c = mean(data)
T, total, count = _sum((x-c)**2 for x in data)
# The following sum should mathematically equal zero, but due to rounding
# error may not.
diff --git a/Lib/test/test_statistics.py b/Lib/test/test_statistics.py
index 5c3b1fd..bf415dd 100644
--- a/Lib/test/test_statistics.py
+++ b/Lib/test/test_statistics.py
@@ -2089,6 +2089,10 @@
self.assertEqual(result, exact)
self.assertIsInstance(result, Decimal)
+ def test_center_not_at_mean(self):
+ data = (1.0, 2.0)
+ self.assertEqual(self.func(data), 0.5)
+ self.assertEqual(self.func(data, xbar=2.0), 1.0)
class TestPStdev(VarianceStdevMixin, NumericTestCase):
# Tests for population standard deviation.
@@ -2101,6 +2105,11 @@
expected = math.sqrt(statistics.pvariance(data))
self.assertEqual(self.func(data), expected)
+ def test_center_not_at_mean(self):
+ # See issue: 40855
+ data = (3, 6, 7, 10)
+ self.assertEqual(self.func(data), 2.5)
+ self.assertEqual(self.func(data, mu=0.5), 6.5)
class TestStdev(VarianceStdevMixin, NumericTestCase):
# Tests for sample standard deviation.
@@ -2118,6 +2127,9 @@
expected = math.sqrt(statistics.variance(data))
self.assertEqual(self.func(data), expected)
+ def test_center_not_at_mean(self):
+ data = (1.0, 2.0)
+ self.assertEqual(self.func(data, xbar=2.0), 1.0)
class TestGeometricMean(unittest.TestCase):
diff --git a/Misc/NEWS.d/next/Library/2020-06-12-10-44-15.bpo-40855.jSot83.rst b/Misc/NEWS.d/next/Library/2020-06-12-10-44-15.bpo-40855.jSot83.rst
new file mode 100644
index 0000000..201d510
--- /dev/null
+++ b/Misc/NEWS.d/next/Library/2020-06-12-10-44-15.bpo-40855.jSot83.rst
@@ -0,0 +1,2 @@
+The standard deviation and variance functions in the statistics module were
+ignoring their mu and xbar arguments.