Fix categorical from codes nan 21767 (pandas-dev#21775)

doc/source/whatsnew/v0.24.0.txt

@@ -479,6 +479,7 @@ Deprecations
 - :meth:`MultiIndex.to_hierarchical` is deprecated and will be removed in a future version  (:issue:`21613`)
 - :meth:`Series.ptp` is deprecated. Use ``numpy.ptp`` instead (:issue:`21614`)
 - :meth:`Series.compress` is deprecated. Use ``Series[condition]`` instead (:issue:`18262`)
+- :meth:`Categorical.from_codes` has deprecated providing float values for the ``codes`` argument. (:issue:`21767`)
 
 .. _whatsnew_0240.prior_deprecations:
 
@@ -526,9 +527,7 @@ Bug Fixes
 Categorical
 ^^^^^^^^^^^
 
--
--
--
+- Bug in :meth:`Categorical.from_codes` where ``NaN`` values in `codes` were silently converted to ``0`` (:issue:`21767`). In the future this will raise a ``ValueError``. Also changes the behavior of `.from_codes([1.1, 2.0])`.
 
 Datetimelike
 ^^^^^^^^^^^^

pandas/core/arrays/categorical.py

@@ -27,6 +27,8 @@
     is_timedelta64_dtype,
     is_categorical,
     is_categorical_dtype,
+    is_float_dtype,
+    is_integer_dtype,
     is_list_like, is_sequence,
     is_scalar, is_iterator,
     is_dict_like)
@@ -633,8 +635,21 @@ def from_codes(cls, codes, categories, ordered=False):
             categorical. If not given, the resulting categorical will be
             unordered.
         """
+        codes = np.asarray(codes)  # #21767
+        if not is_integer_dtype(codes):
+            msg = "codes need to be array-like integers"
+            if is_float_dtype(codes):
+                icodes = codes.astype('i8')
+                if (icodes == codes).all():
+                    msg = None
+                    codes = icodes
+                    warn(("float codes will be disallowed in the future and "
+                          "raise a ValueError"), FutureWarning, stacklevel=2)
+            if msg:
+                raise ValueError(msg)
+
         try:
-            codes = coerce_indexer_dtype(np.asarray(codes), categories)
+            codes = coerce_indexer_dtype(codes, categories)
         except (ValueError, TypeError):
             raise ValueError(
                 "codes need to be convertible to an arrays of integers")

pandas/tests/arrays/categorical/test_constructors.py

@@ -468,6 +468,26 @@ def test_from_codes_with_categorical_categories(self):
         with pytest.raises(ValueError):
             Categorical.from_codes([0, 1], Categorical(['a', 'b', 'a']))
 
+    def test_from_codes_with_nan_code(self):
+        # GH21767
+        codes = [1, 2, np.nan]
+        categories = ['a', 'b', 'c']
+        with pytest.raises(ValueError):
+            Categorical.from_codes(codes, categories)
+
+    def test_from_codes_with_float(self):
+        # GH21767
+        codes = [1.0, 2.0, 0]  # integer, but in float dtype
+        categories = ['a', 'b', 'c']
+
+        with tm.assert_produces_warning(FutureWarning):
+            cat = Categorical.from_codes(codes, categories)
+        tm.assert_numpy_array_equal(cat.codes, np.array([1, 2, 0], dtype='i1'))
+
+        codes = [1.1, 2.0, 0]  # non-integer
+        with pytest.raises(ValueError):
+            Categorical.from_codes(codes, categories)
+
     @pytest.mark.parametrize('dtype', [None, 'category'])
     def test_from_inferred_categories(self, dtype):
         cats = ['a', 'b']