{"action":"created","comment":{"url":"https://api.github.com/repos/scipy/scipy/pulls/comments/33810156","id":33810156,"diff_hunk":"@@ -1793,18 +1800,42 @@ def cumfreq(a, numbins=10, defaultreallimits=None, weights=None):\n \n     Examples\n     --------\n+    >>> import matplotlib.pyplot as plt\n     >>> from scipy import stats\n     >>> x = [1, 4, 2, 1, 3, 1]\n-    >>> cumfreqs, lowlim, binsize, extrapoints = stats.cumfreq(x, numbins=4)\n-    >>> cumfreqs\n-    array([ 3.,  4.,  5.,  6.])\n-    >>> cumfreqs, lowlim, binsize, extrapoints = \\\n-    ...     stats.cumfreq(x, numbins=4, defaultreallimits=(1.5, 5))\n-    >>> cumfreqs\n+    >>> res = stats.cumfreq(x, numbins=4, defaultreallimits=(1.5, 5))\n+    >>> res.cumcount\n     array([ 1.,  2.,  3.,  3.])\n-    >>> extrapoints\n+    >>> res.extrapoints\n     3\n \n+    Create a normal distribution with 1000 random values\n+\n+    >>> rng = np.random.RandomState(seed=12345)\n+    >>> samples = stats.norm.rvs(size=1000, random_state=rng)\n+\n+    Calculate cumulative frequencies\n+\n+    >>> res = stats.cumfreq(samples, numbins=25)\n+\n+    Calculate space of values for x\n+\n+    >>> x = res.lowerlimit + np.linspace(0, res.binsize*res.cumcount.size,\n+    ... 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