BUG: pd.cut with bins=1 and input all 0s

The special case of running pd.cut() qith bins=1 an input containing all
0s raises a ValueError

Author: luca-s

doc/source/whatsnew/v0.20.0.txt

@@ -670,7 +670,7 @@ Bug Fixes
 - Bug in ``DataFrame.loc`` with indexing a ``MultiIndex`` with a ``Series`` indexer (:issue:`14730`, :issue:`15424`)
 - Bug in ``DataFrame.loc`` with indexing a ``MultiIndex`` with a numpy array (:issue:`15434`)
 - Bug in ``Rolling.quantile`` function that caused a segmentation fault when called with a quantile value outside of the range [0, 1] (:issue:`15463`)
-
+- Bug in ``pd.cut()`` single bin on all 0s array raises ``ValueError`` (:issue:`15428`)
 
 - Bug in ``SparseSeries.reindex`` on single level with list of length 1 (:issue:`15447`)
 

pandas/tests/tools/test_tile.py

@@ -297,6 +297,11 @@ def test_single_bin(self):
         result = cut(s, 1, labels=False)
         tm.assert_series_equal(result, expected)
 
+        # issue 15428
+        s = Series([0., 0.])
+        result = cut(s, 1, labels=False)
+        tm.assert_series_equal(result, expected)
+
     def test_datetime_cut(self):
         # GH 14714
         # testing for time data to be present as series

pandas/tools/tile.py

@@ -104,8 +104,8 @@ def cut(x, bins, right=True, labels=None, retbins=False, precision=3,
         mn, mx = [mi + 0.0 for mi in rng]
 
         if mn == mx:  # adjust end points before binning
-            mn -= .001 * abs(mn)
-            mx += .001 * abs(mx)
+            mn -= .001 * abs(mn) if mn != 0 else .001
+            mx += .001 * abs(mx) if mx != 0 else .001
             bins = np.linspace(mn, mx, bins + 1, endpoint=True)
         else:  # adjust end points after binning
             bins = np.linspace(mn, mx, bins + 1, endpoint=True)