BUG: DataFrame(frozenset) should raise (#40163)

Author: jbrockmendel

doc/source/whatsnew/v1.3.0.rst

@@ -405,6 +405,7 @@ Conversion
 - Bug in :meth:`Series.to_dict` with ``orient='records'`` now returns python native types (:issue:`25969`)
 - Bug in :meth:`Series.view` and :meth:`Index.view` when converting between datetime-like (``datetime64[ns]``, ``datetime64[ns, tz]``, ``timedelta64``, ``period``) dtypes (:issue:`39788`)
 - Bug in creating a :class:`DataFrame` from an empty ``np.recarray`` not retaining the original dtypes (:issue:`40121`)
+- Bug in :class:`DataFrame` failing to raise ``TypeError`` when constructing from a ``frozenset`` (:issue:`40163`)
 -
 
 Strings

pandas/core/construction.py

@@ -518,9 +518,9 @@ def sanitize_array(
 
     elif isinstance(data, (list, tuple, abc.Set, abc.ValuesView)) and len(data) > 0:
         # TODO: deque, array.array
-        if isinstance(data, set):
+        if isinstance(data, (set, frozenset)):
             # Raise only for unordered sets, e.g., not for dict_keys
-            raise TypeError("Set type is unordered")
+            raise TypeError(f"'{type(data).__name__}' type is unordered")
         data = list(data)
 
         if dtype is not None:

pandas/core/series.py

@@ -375,10 +375,8 @@ def __init__(
                         "`index` argument. `copy` must be False."
                     )
 
-            elif is_extension_array_dtype(data):
+            elif isinstance(data, ExtensionArray):
                 pass
-            elif isinstance(data, (set, frozenset)):
-                raise TypeError(f"'{type(data).__name__}' type is unordered")
             else:
                 data = com.maybe_iterable_to_list(data)
 

pandas/tests/frame/test_constructors.py

@@ -377,26 +377,31 @@ def test_constructor_dict(self):
         with pytest.raises(ValueError, match=msg):
             DataFrame({"A": {"a": "a", "b": "b"}, "B": ["a", "b", "c"]})
 
+    def test_constructor_dict_length1(self):
         # Length-one dict micro-optimization
         frame = DataFrame({"A": {"1": 1, "2": 2}})
         tm.assert_index_equal(frame.index, Index(["1", "2"]))
 
+    def test_constructor_dict_with_index(self):
         # empty dict plus index
         idx = Index([0, 1, 2])
         frame = DataFrame({}, index=idx)
         assert frame.index is idx
 
+    def test_constructor_dict_with_index_and_columns(self):
         # empty dict with index and columns
         idx = Index([0, 1, 2])
         frame = DataFrame({}, index=idx, columns=idx)
         assert frame.index is idx
         assert frame.columns is idx
         assert len(frame._series) == 3
 
+    def test_constructor_dict_of_empty_lists(self):
         # with dict of empty list and Series
         frame = DataFrame({"A": [], "B": []}, columns=["A", "B"])
         tm.assert_index_equal(frame.index, RangeIndex(0), exact=True)
 
+    def test_constructor_dict_with_none(self):
         # GH 14381
         # Dict with None value
         frame_none = DataFrame({"a": None}, index=[0])
@@ -405,6 +410,7 @@ def test_constructor_dict(self):
         assert frame_none_list._get_value(0, "a") is None
         tm.assert_frame_equal(frame_none, frame_none_list)
 
+    def test_constructor_dict_errors(self):
         # GH10856
         # dict with scalar values should raise error, even if columns passed
         msg = "If using all scalar values, you must pass an index"
@@ -560,7 +566,7 @@ def test_constructor_error_msgs(self):
         with pytest.raises(ValueError, match=msg):
             DataFrame({"a": False, "b": True})
 
-    def test_constructor_subclass_dict(self, float_frame, dict_subclass):
+    def test_constructor_subclass_dict(self, dict_subclass):
         # Test for passing dict subclass to constructor
         data = {
             "col1": dict_subclass((x, 10.0 * x) for x in range(10)),
@@ -574,6 +580,7 @@ def test_constructor_subclass_dict(self, float_frame, dict_subclass):
         df = DataFrame(data)
         tm.assert_frame_equal(refdf, df)
 
+    def test_constructor_defaultdict(self, float_frame):
         # try with defaultdict
         from collections import defaultdict
 
@@ -608,6 +615,7 @@ def test_constructor_dict_cast(self):
         assert frame["B"].dtype == np.object_
         assert frame["A"].dtype == np.float64
 
+    def test_constructor_dict_cast2(self):
         # can't cast to float
         test_data = {
             "A": dict(zip(range(20), tm.makeStringIndex(20))),
@@ -623,6 +631,7 @@ def test_constructor_dict_dont_upcast(self):
         df = DataFrame(d)
         assert isinstance(df["Col1"]["Row2"], float)
 
+    def test_constructor_dict_dont_upcast2(self):
         dm = DataFrame([[1, 2], ["a", "b"]], index=[1, 2], columns=[1, 2])
         assert isinstance(dm[1][1], int)
 
@@ -1195,6 +1204,7 @@ def __len__(self, n):
         expected = DataFrame([[1, "a"], [2, "b"]], columns=columns)
         tm.assert_frame_equal(result, expected, check_dtype=False)
 
+    def test_constructor_stdlib_array(self):
         # GH 4297
         # support Array
         import array
@@ -2427,11 +2437,16 @@ def test_from_2d_ndarray_with_dtype(self):
         expected = DataFrame(array_dim2).astype("datetime64[ns, UTC]")
         tm.assert_frame_equal(df, expected)
 
-    def test_construction_from_set_raises(self):
+    @pytest.mark.parametrize("typ", [set, frozenset])
+    def test_construction_from_set_raises(self, typ):
         # https://github.com/pandas-dev/pandas/issues/32582
-        msg = "Set type is unordered"
+        values = typ({1, 2, 3})
+        msg = f"'{typ.__name__}' type is unordered"
         with pytest.raises(TypeError, match=msg):
-            DataFrame({"a": {1, 2, 3}})
+            DataFrame({"a": values})
+
+        with pytest.raises(TypeError, match=msg):
+            Series(values)
 
 
 def get1(obj):

pandas/tests/series/test_constructors.py

@@ -69,6 +69,7 @@ class TestSeriesConstructors:
         ],
     )
     def test_empty_constructor(self, constructor, check_index_type):
+        # TODO: share with frame test of the same name
         with tm.assert_produces_warning(DeprecationWarning, check_stacklevel=False):
             expected = Series()
             result = constructor()
@@ -310,6 +311,7 @@ def test_constructor_generator(self):
         exp = Series(range(10))
         tm.assert_series_equal(result, exp)
 
+        # same but with non-default index
         gen = (i for i in range(10))
         result = Series(gen, index=range(10, 20))
         exp.index = range(10, 20)
@@ -323,6 +325,7 @@ def test_constructor_map(self):
         exp = Series(range(10))
         tm.assert_series_equal(result, exp)
 
+        # same but with non-default index
         m = map(lambda x: x, range(10))
         result = Series(m, index=range(10, 20))
         exp.index = range(10, 20)
@@ -386,6 +389,7 @@ def test_constructor_categorical_with_coercion(self):
         str(df.values)
         str(df)
 
+    def test_constructor_categorical_with_coercion2(self):
         # GH8623
         x = DataFrame(
             [[1, "John P. Doe"], [2, "Jane Dove"], [1, "John P. Doe"]],
@@ -747,6 +751,7 @@ def test_constructor_datelike_coercion(self):
         assert s.iloc[1] == "NOV"
         assert s.dtype == object
 
+    def test_constructor_datelike_coercion2(self):
         # the dtype was being reset on the slicing and re-inferred to datetime
         # even thought the blocks are mixed
         belly = "216 3T19".split()
@@ -798,6 +803,7 @@ def test_constructor_dtype_datetime64(self):
         assert isna(s[1])
         assert s.dtype == "M8[ns]"
 
+    def test_constructor_dtype_datetime64_10(self):
         # GH3416
         dates = [
             np.datetime64(datetime(2013, 1, 1)),
@@ -850,18 +856,21 @@ def test_constructor_dtype_datetime64(self):
             expected = Series(dts.astype(np.int64))
         tm.assert_series_equal(result, expected)
 
+    def test_constructor_dtype_datetime64_9(self):
         # invalid dates can be help as object
         result = Series([datetime(2, 1, 1)])
         assert result[0] == datetime(2, 1, 1, 0, 0)
 
         result = Series([datetime(3000, 1, 1)])
         assert result[0] == datetime(3000, 1, 1, 0, 0)
 
+    def test_constructor_dtype_datetime64_8(self):
         # don't mix types
         result = Series([Timestamp("20130101"), 1], index=["a", "b"])
         assert result["a"] == Timestamp("20130101")
         assert result["b"] == 1
 
+    def test_constructor_dtype_datetime64_7(self):
         # GH6529
         # coerce datetime64 non-ns properly
         dates = date_range("01-Jan-2015", "01-Dec-2015", freq="M")
@@ -887,6 +896,7 @@ def test_constructor_dtype_datetime64(self):
         tm.assert_numpy_array_equal(series1.values, dates2)
         assert series1.dtype == object
 
+    def test_constructor_dtype_datetime64_6(self):
         # these will correctly infer a datetime
         s = Series([None, NaT, "2013-08-05 15:30:00.000001"])
         assert s.dtype == "datetime64[ns]"
@@ -897,6 +907,7 @@ def test_constructor_dtype_datetime64(self):
         s = Series([NaT, np.nan, "2013-08-05 15:30:00.000001"])
         assert s.dtype == "datetime64[ns]"
 
+    def test_constructor_dtype_datetime64_5(self):
         # tz-aware (UTC and other tz's)
         # GH 8411
         dr = date_range("20130101", periods=3)
@@ -906,18 +917,21 @@ def test_constructor_dtype_datetime64(self):
         dr = date_range("20130101", periods=3, tz="US/Eastern")
         assert str(Series(dr).iloc[0].tz) == "US/Eastern"
 
+    def test_constructor_dtype_datetime64_4(self):
         # non-convertible
         s = Series([1479596223000, -1479590, NaT])
         assert s.dtype == "object"
         assert s[2] is NaT
         assert "NaT" in str(s)
 
+    def test_constructor_dtype_datetime64_3(self):
         # if we passed a NaT it remains
         s = Series([datetime(2010, 1, 1), datetime(2, 1, 1), NaT])
         assert s.dtype == "object"
         assert s[2] is NaT
         assert "NaT" in str(s)
 
+    def test_constructor_dtype_datetime64_2(self):
         # if we passed a nan it remains
         s = Series([datetime(2010, 1, 1), datetime(2, 1, 1), np.nan])
         assert s.dtype == "object"
@@ -980,6 +994,7 @@ def test_constructor_with_datetime_tz(self):
         result = DatetimeIndex(s, freq="infer")
         tm.assert_index_equal(result, dr)
 
+    def test_constructor_with_datetime_tz4(self):
         # inference
         s = Series(
             [
@@ -990,6 +1005,7 @@ def test_constructor_with_datetime_tz(self):
         assert s.dtype == "datetime64[ns, US/Pacific]"
         assert lib.infer_dtype(s, skipna=True) == "datetime64"
 
+    def test_constructor_with_datetime_tz3(self):
         s = Series(
             [
                 Timestamp("2013-01-01 13:00:00-0800", tz="US/Pacific"),
@@ -999,6 +1015,7 @@ def test_constructor_with_datetime_tz(self):
         assert s.dtype == "object"
         assert lib.infer_dtype(s, skipna=True) == "datetime"
 
+    def test_constructor_with_datetime_tz2(self):
         # with all NaT
         s = Series(NaT, index=[0, 1], dtype="datetime64[ns, US/Eastern]")
         expected = Series(DatetimeIndex(["NaT", "NaT"], tz="US/Eastern"))
@@ -1231,14 +1248,6 @@ def test_constructor_dict_of_tuples(self):
         expected = Series([3, 6], index=MultiIndex.from_tuples([(1, 2), (None, 5)]))
         tm.assert_series_equal(result, expected)
 
-    def test_constructor_set(self):
-        values = {1, 2, 3, 4, 5}
-        with pytest.raises(TypeError, match="'set' type is unordered"):
-            Series(values)
-        values = frozenset(values)
-        with pytest.raises(TypeError, match="'frozenset' type is unordered"):
-            Series(values)
-
     # https://github.com/pandas-dev/pandas/issues/22698
     @pytest.mark.filterwarnings("ignore:elementwise comparison:FutureWarning")
     def test_fromDict(self):