add test for failing case

pandas-dev · jreback · Oct 29, 2021 · Oct 26, 2021 · Oct 26, 2021 · Oct 28, 2021
commit f208db4b2afc63368f69bcc94bacdee701fb39e3
diff --git a/pandas/_libs/lib.pyx b/pandas/_libs/lib.pyx
@@ -620,39 +620,30 @@ def array_equivalent_object(left: object[:], right: object[:]) -> bool:
         object x, y
 
     for i in range(n):
-        # print('in array_equivalent_object')
         x = left[i]
         y = right[i]
 
         # we are either not equal or both nan
         # I think None == None will be true here
         try:
-            # print('PyObject_RichCompareBool(x, y, Py_EQ): ' + str(PyObject_RichCompareBool(x, y, Py_EQ)))
-            # print('is_matching_na(x, y, nan_matches_none=True)' + str(is_matching_na(x, y, nan_matches_none=True)))
             if PyArray_Check(x) and PyArray_Check(y):
                 if not array_equivalent_object(x, y):
-                    # print('line 631, returning False, this is the index: ' + str(i))
                     return False
             elif (x is C_NA) ^ (y is C_NA):
-                # print('first elif')
                 return False
             elif not (
                 PyObject_RichCompareBool(x, y, Py_EQ)
                 or is_matching_na(x, y, nan_matches_none=True)
             ):
-                # print('second elif')
                 return False
         except ValueError:
-            # print('raise Value Error')
             # Avoid raising ValueError when comparing Numpy arrays to other types
             if cnp.PyArray_IsAnyScalar(x) != cnp.PyArray_IsAnyScalar(y):
                 # Only compare scalars to scalars and non-scalars to non-scalars
-                # print('cnp.PyArray_IsAnyScalar(x) != cnp.PyArray_IsAnyScalar(y)')
                 return False
             elif (not (cnp.PyArray_IsPythonScalar(x) or cnp.PyArray_IsPythonScalar(y))
                   and not (isinstance(x, type(y)) or isinstance(y, type(x)))):
                 # Check if non-scalars have the same type
-                # print('(not (cnp.PyArray_IsPythonScalar(x) or cnp.PyArray_IsPythonScalar(y)) and not (isinstance(x, type(y)) or isinstance(y, type(x)))):')
                 return False
             raise
     return True

diff --git a/pandas/_libs/missing.pyx b/pandas/_libs/missing.pyx
@@ -59,23 +59,16 @@ cpdef bint is_matching_na(object left, object right, bint nan_matches_none=False
     bool
     """
     if left is None:
-        # print('is matching na left is None')
         if nan_matches_none and util.is_nan(right):
             return True
         return right is None
     elif left is C_NA:
-        # print('is matching na left is C_NA')
         return right is C_NA
     elif left is NaT:
-        # print('is matching na left is NaT')
         return right is NaT
     elif util.is_float_object(left):
-        # print('is matching na left is float object')
         if nan_matches_none and right is None and util.is_nan(left):
-            # print('is matching na left is float and right is None: actually right is ' + str(right))
             return True
-        # print('is matching na left is float and right is NOT None')
-        # print('str(util.is_nan(left)): ' + str(str(util.is_nan(left))) + ' util.is_float_object(right) ' + str(util.is_float_object(right)) + ' util.is_nan(right) ' + str(util.is_nan(right)))
         return (
             util.is_nan(left)
             and util.is_float_object(right)

diff --git a/pandas/tests/series/methods/test_equals.py b/pandas/tests/series/methods/test_equals.py
@@ -126,6 +126,7 @@ def test_equals_none_vs_nan():
     assert Index(ser, dtype=ser.dtype).equals(Index(ser2, dtype=ser2.dtype))
     assert ser.array.equals(ser2.array)
 
+
 def test_equals_None_vs_float():
     left = Series([-np.inf, np.nan, -1.0, 0.0, 1.0, 10 / 3, np.inf], dtype=object)
     right = Series([None] * len(left))