BUG: pandas.cut and negative values #14652

closes #14652

Author: Luca Scarabello <[email protected]>
Author: Luca <[email protected]>

Closes #14663 from luca-s/issue_14652 and squashes the following commits:

8db26db [Luca Scarabello] Moved new test location to pandas\tools\tests\test_tile.py
90dd07d [Luca Scarabello] Updated whatsnew
d6b3da8 [Luca Scarabello] fixed flake8 compliance
fdc55b9 [Luca Scarabello] Added test case for #14652
d5790e2 [Luca Scarabello] updated whatsnew v0.19.2
2db0c7a [Luca] BUG: pandas.cut and negative values #14652

Author: luca-s

doc/source/whatsnew/v0.19.2.txt

@@ -23,5 +23,6 @@ Performance Improvements
 Bug Fixes
 ~~~~~~~~~
 
-- compat with ``dateutil==2.6.0`` for testing (:issue:`14621`)
-- allow ``nanoseconds`` in ``Timestamp.replace`` kwargs (:issue:`14621`)
+- Compat with ``dateutil==2.6.0``; segfault reported in the testing suite (:issue:`14621`)
+- Allow ``nanoseconds`` in ``Timestamp.replace`` as a kwarg (:issue:`14621`)
+- Bug in ``pd.cut`` with negative values and a single bin (:issue:`14652`)

pandas/tools/tests/test_tile.py

@@ -271,6 +271,18 @@ def test_series_retbins(self):
                                     np.array([0, 0, 1, 1], dtype=np.int8))
         tm.assert_numpy_array_equal(bins, np.array([0, 1.5, 3]))
 
+    def test_single_bin(self):
+        # issue 14652
+        expected = Series([0, 0])
+
+        s = Series([9., 9.])
+        result = cut(s, 1, labels=False)
+        tm.assert_series_equal(result, expected)
+
+        s = Series([-9., -9.])
+        result = cut(s, 1, labels=False)
+        tm.assert_series_equal(result, expected)
+
 
 def curpath():
     pth, _ = os.path.split(os.path.abspath(__file__))

pandas/tools/tile.py

@@ -98,8 +98,8 @@ 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 * mn
-            mx += .001 * mx
+            mn -= .001 * abs(mn)
+            mx += .001 * abs(mx)
             bins = np.linspace(mn, mx, bins + 1, endpoint=True)
         else:  # adjust end points after binning
             bins = np.linspace(mn, mx, bins + 1, endpoint=True)