Don't raise warning on merging int and float with nan (pandas-dev#21011)

Author: jorisvandenbossche

pandas/core/reshape/merge.py

@@ -955,14 +955,14 @@ def _maybe_coerce_merge_keys(self):
 
                 # check whether ints and floats
                 elif is_integer_dtype(rk) and is_float_dtype(lk):
-                    if not (lk == lk.astype(rk.dtype)).all():
+                    if not (lk == lk.astype(rk.dtype))[~np.isnan(lk)].all():
                         warnings.warn('You are merging on int and float '
                                       'columns where the float values '
                                       'are not equal to their int '
                                       'representation', UserWarning)
 
                 elif is_float_dtype(rk) and is_integer_dtype(lk):
-                    if not (rk == rk.astype(lk.dtype)).all():
+                    if not (rk == rk.astype(lk.dtype))[~np.isnan(rk)].all():
                         warnings.warn('You are merging on int and float '
                                       'columns where the float values '
                                       'are not equal to their int '

pandas/tests/reshape/merge/test_merge.py

@@ -1519,6 +1519,13 @@ def test_merge_on_ints_floats_warning(self):
             result = B.merge(A, left_on='Y', right_on='X')
             assert_frame_equal(result, expected[['Y', 'X']])
 
+        # test no warning if float has NaNs
+        B = DataFrame({'Y': [np.nan, np.nan, 3.0]})
+
+        with tm.assert_produces_warning(None):
+            result = B.merge(A, left_on='Y', right_on='X')
+            assert_frame_equal(result, expected[['Y', 'X']])
+
     @pytest.mark.parametrize('df1_vals, df2_vals', [
         ([0, 1, 2], ["0", "1", "2"]),
         ([0.0, 1.0, 2.0], ["0", "1", "2"]),