BUG: Fixed DataFrame.describe percentiles are ndarray w/ no median

Explicit conversion to list for `percentiles`. Fixes the case where
`percentiles` is passed as a numpy with no median (0.5) present.
Closes #14908.

Author: pbreach <[email protected]>

Closes #14914 from pbreach/df-describe-percentile-ndarray-no-median and squashes the following commits:

5c8199b [pbreach] Minor test fix
b5d09a6 [pbreach] Added test for median insertion with ndarray
72fe0cb [pbreach] Added what's new entry
f954392 [pbreach] Moved conversion to if percentiles is not None
d192ac7 [pbreach] Fixed whitespace issue
a06794d [pbreach] BUG: Fixed bug in DataFrame.describe when percentiles are passed as array with no median

Author: pbreach

doc/source/whatsnew/v0.20.0.txt

@@ -245,7 +245,7 @@ Bug Fixes
 - Bug in ``TimedeltaIndex`` addition where overflow was being allowed without error (:issue:`14816`)
 - Bug in ``DataFrame`` construction in which unsigned 64-bit integer elements were being converted to objects (:issue:`14881`)
 - Bug in ``astype()`` where ``inf`` values were incorrectly converted to integers. Now raises error now with ``astype()`` for Series and DataFrames (:issue:`14265`)
-
+- Bug in ``describe()`` when passing a numpy array which does not contain the median to the ``percentiles`` keyword argument (:issue:`14908`)
 
 
 

pandas/core/generic.py

@@ -5262,6 +5262,9 @@ def describe(self, percentiles=None, include=None, exclude=None):
             raise ValueError("Cannot describe a DataFrame without columns")
 
         if percentiles is not None:
+            # explicit conversion of `percentiles` to list
+            percentiles = list(percentiles)
+
             # get them all to be in [0, 1]
             self._check_percentile(percentiles)
 

pandas/tests/test_generic.py

@@ -996,6 +996,13 @@ def test_describe_percentiles_insert_median(self):
         self.assertTrue('0%' in d1.index)
         self.assertTrue('100%' in d2.index)
 
+    def test_describe_percentiles_insert_median_ndarray(self):
+        # GH14908
+        df = tm.makeDataFrame()
+        result = df.describe(percentiles=np.array([.25, .75]))
+        expected = df.describe(percentiles=[.25, .75])
+        assert_frame_equal(result, expected)
+
     def test_describe_percentiles_unique(self):
         # GH13104
         df = tm.makeDataFrame()