BUG: DataFrame.floordiv(ser, axis=0) not matching column-wise bheavior (#31271)

Author: jbrockmendel

doc/source/whatsnew/v1.1.0.rst

@@ -119,6 +119,7 @@ Timezones
 
 Numeric
 ^^^^^^^
+- Bug in :meth:`DataFrame.floordiv` with ``axis=0`` not treating division-by-zero like :meth:`Series.floordiv` (:issue:`31271`)
 -
 -
 

pandas/core/frame.py

@@ -5341,7 +5341,7 @@ def reorder_levels(self, order, axis=0) -> "DataFrame":
     # ----------------------------------------------------------------------
     # Arithmetic / combination related
 
-    def _combine_frame(self, other, func, fill_value=None, level=None):
+    def _combine_frame(self, other: "DataFrame", func, fill_value=None):
         # at this point we have `self._indexed_same(other)`
 
         if fill_value is None:
@@ -5368,16 +5368,18 @@ def _arith_op(left, right):
 
         return new_data
 
-    def _combine_match_index(self, other, func):
+    def _combine_match_index(self, other: Series, func):
         # at this point we have `self.index.equals(other.index)`
 
         if ops.should_series_dispatch(self, other, func):
             # operate column-wise; avoid costly object-casting in `.values`
             new_data = ops.dispatch_to_series(self, other, func)
         else:
             # fastpath --> operate directly on values
+            other_vals = other.values.reshape(-1, 1)
             with np.errstate(all="ignore"):
-                new_data = func(self.values.T, other.values).T
+                new_data = func(self.values, other_vals)
+            new_data = dispatch_fill_zeros(func, self.values, other_vals, new_data)
         return new_data
 
     def _construct_result(self, result) -> "DataFrame":

pandas/core/ops/missing.py

@@ -109,26 +109,23 @@ def mask_zero_div_zero(x, y, result):
         return result
 
     if zmask.any():
-        shape = result.shape
 
         # Flip sign if necessary for -0.0
         zneg_mask = zmask & np.signbit(y)
         zpos_mask = zmask & ~zneg_mask
 
-        nan_mask = (zmask & (x == 0)).ravel()
+        nan_mask = zmask & (x == 0)
         with np.errstate(invalid="ignore"):
-            neginf_mask = ((zpos_mask & (x < 0)) | (zneg_mask & (x > 0))).ravel()
-            posinf_mask = ((zpos_mask & (x > 0)) | (zneg_mask & (x < 0))).ravel()
+            neginf_mask = (zpos_mask & (x < 0)) | (zneg_mask & (x > 0))
+            posinf_mask = (zpos_mask & (x > 0)) | (zneg_mask & (x < 0))
 
         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=False).ravel()
-
-            np.putmask(result, nan_mask, np.nan)
-            np.putmask(result, posinf_mask, np.inf)
-            np.putmask(result, neginf_mask, -np.inf)
+            result = result.astype("float64", copy=False)
 
-            result = result.reshape(shape)
+            result[nan_mask] = np.nan
+            result[posinf_mask] = np.inf
+            result[neginf_mask] = -np.inf
 
     return result
 

pandas/tests/frame/test_arithmetic.py

@@ -332,6 +332,21 @@ def test_df_flex_cmp_constant_return_types_empty(self, opname):
 
 
 class TestFrameFlexArithmetic:
+    def test_floordiv_axis0(self):
+        # make sure we df.floordiv(ser, axis=0) matches column-wise result
+        arr = np.arange(3)
+        ser = pd.Series(arr)
+        df = pd.DataFrame({"A": ser, "B": ser})
+
+        result = df.floordiv(ser, axis=0)
+
+        expected = pd.DataFrame({col: df[col] // ser for col in df.columns})
+
+        tm.assert_frame_equal(result, expected)
+
+        result2 = df.floordiv(ser.values, axis=0)
+        tm.assert_frame_equal(result2, expected)
+
     def test_df_add_td64_columnwise(self):
         # GH 22534 Check that column-wise addition broadcasts correctly
         dti = pd.date_range("2016-01-01", periods=10)