requested edits

Author: jbrockmendel

doc/source/whatsnew/v0.23.0.txt

@@ -187,36 +187,29 @@ Previous Behavior:
 
 .. code-block:: ipython
 
-    In [6]: index = pd.Index([-1, 0, 1])
+    In [6]: index = pd.Int64Index([-1, 0, 1])
 
     In [7]: index / 0
     Out[7]: Int64Index([0, 0, 0], dtype='int64')
 
-    In [8]: index = pd.UInt64Index([0, 1])
+    # Previous behavior yielded different results depending on the type of zero in the divisor
+    In [8]: index / 0.0
+    Out[8]: Float64Index([-inf, nan, inf], dtype='float64')
 
-    In [9]: index / np.array([0, 0], dtype=np.uint64)
-    Out[9]: UInt64Index([0, 0], dtype='uint64')
+    In [9]: index = pd.UInt64Index([0, 1])
 
-    In [10]: pd.RangeIndex(1, 5) / 0
-    ---------------------------------------------------------------------------
-    ZeroDivisionError                         Traceback (most recent call last)
-    <ipython-input-10-4c5e91d516f3> in <module>()
-    ----> 1 pd.RangeIndex(1, 5) / 0
-
-    /usr/local/lib/python2.7/site-packages/pandas/core/indexes/range.pyc in _evaluate_numeric_binop(self, other)
-        592                     if step:
-        593                         with np.errstate(all='ignore'):
-    --> 594                             rstep = step(self._step, other)
-        595 
-        596                         # we don't have a representable op
+    In [10]: index / np.array([0, 0], dtype=np.uint64)
+    Out[10]: UInt64Index([0, 0], dtype='uint64')
 
+    In [11]: pd.RangeIndex(1, 5) / 0
     ZeroDivisionError: integer division or modulo by zero
 
 Current Behavior:
 
 .. ipython:: python
 
-    index = pd.Index([-1, 0, 1])
+    index = pd.Int64Index([-1, 0, 1])
+    # division by zero gives -infinity where negative, +infinity where positive, and NaN for 0 / 0
     index / 0
 
     # The result of division by zero should not depend on whether the zero is int or float

pandas/core/missing.py

@@ -686,6 +686,7 @@ def mask_zero_div_zero(x, y, result, copy=False):
         posinf_mask = (zmask & (x > 0)).ravel()
 
         if nan_mask.any() or neginf_mask.any() or posinf_mask.any():
+            # Fill negative/0 with -inf, positive/0 with +inf, 0/0 with NaN
             result = result.astype('float64', copy=copy).ravel()
 
             np.putmask(result, nan_mask, np.nan)