Revert "ERR: Raise ValueError when setting scalars in a dataframe with no index ( #16823) (#16968)"

doc/source/whatsnew/v0.21.0.txt

@@ -791,8 +791,6 @@ Other API Changes
 - Restricted DateOffset keyword arguments.  Previously, ``DateOffset`` subclasses allowed arbitrary keyword arguments which could lead to unexpected behavior.  Now, only valid arguments will be accepted. (:issue:`17176`).
 - Pandas no longer registers matplotlib converters on import. The converters
   will be registered and used when the first plot is draw (:issue:`17710`)
-- Setting on a column with a scalar value and 0-len index now raises a ``ValueError`` (:issue:`16823`)
-
 
 .. _whatsnew_0210.deprecations:
 

pandas/core/frame.py

@@ -2557,17 +2557,13 @@ def _ensure_valid_index(self, value):
         passed value
         """
         # GH5632, make sure that we are a Series convertible
-        if not len(self.index):
-            if not is_list_like(value):
-                # GH16823, Raise an error due to loss of information
-                raise ValueError('If using all scalar values, you must pass'
-                                 ' an index')
+        if not len(self.index) and is_list_like(value):
             try:
                 value = Series(value)
             except:
-                raise ValueError('Cannot set a frame with no defined'
-                                 'index and a value that cannot be '
-                                 'converted to a Series')
+                raise ValueError('Cannot set a frame with no defined index '
+                                 'and a value that cannot be converted to a '
+                                 'Series')
 
             self._data = self._data.reindex_axis(value.index.copy(), axis=1,
                                                  fill_value=np.nan)

pandas/core/reshape/pivot.py

@@ -454,9 +454,6 @@ def crosstab(index, columns, values=None, rownames=None, colnames=None,
 
     from pandas import DataFrame
     df = DataFrame(data, index=common_idx)
-    if not len(df):
-        return DataFrame(index=common_idx)
-
     if values is None:
         df['__dummy__'] = 0
         kwargs = {'aggfunc': len, 'fill_value': 0}

pandas/tests/frame/test_indexing.py

@@ -722,9 +722,11 @@ def test_setitem_empty_frame_with_boolean(self):
                 assert_frame_equal(df, df2)
 
     def test_setitem_scalars_no_index(self):
-        # GH16823
+        # GH16823 / 17894
         df = DataFrame()
-        pytest.raises(ValueError, df.__setitem__, 'foo', 1)
+        df['foo'] = 1
+        expected = DataFrame(columns=['foo']).astype(np.int64)
+        assert_frame_equal(df, expected)
 
     def test_getitem_empty_frame_with_boolean(self):
         # Test for issue #11859

pandas/tests/indexing/test_loc.py

@@ -423,14 +423,15 @@ def test_loc_setitem_consistency(self):
 
     def test_loc_setitem_consistency_empty(self):
         # empty (essentially noops)
-        # GH16823
+        expected = DataFrame(columns=['x', 'y'])
+        expected['x'] = expected['x'].astype(np.int64)
         df = DataFrame(columns=['x', 'y'])
-        with tm.assert_raises_regex(ValueError, 'If using all scalar values'):
-            df.loc[:, 'x'] = 1
+        df.loc[:, 'x'] = 1
+        tm.assert_frame_equal(df, expected)
 
         df = DataFrame(columns=['x', 'y'])
-        with tm.assert_raises_regex(ValueError, 'If using all scalar values'):
-            df['x'] = 1
+        df['x'] = 1
+        tm.assert_frame_equal(df, expected)
 
     def test_loc_setitem_consistency_slice_column_len(self):
         # .loc[:,column] setting with slice == len of the column

pandas/tests/indexing/test_partial.py

@@ -575,16 +575,24 @@ def f():
     def test_partial_set_empty_frame_row(self):
         # GH5720, GH5744
         # don't create rows when empty
+        expected = DataFrame(columns=['A', 'B', 'New'],
+                             index=pd.Index([], dtype='int64'))
+        expected['A'] = expected['A'].astype('int64')
+        expected['B'] = expected['B'].astype('float64')
+        expected['New'] = expected['New'].astype('float64')
+
         df = DataFrame({"A": [1, 2, 3], "B": [1.2, 4.2, 5.2]})
         y = df[df.A > 5]
-        # GH16823
-        # Setting a column with a scalar and no index should raise
-        with tm.assert_raises_regex(ValueError, 'If using all scalar values'):
-            y['New'] = np.nan
+        y['New'] = np.nan
+        tm.assert_frame_equal(y, expected)
+        # tm.assert_frame_equal(y,expected)
 
+        expected = DataFrame(columns=['a', 'b', 'c c', 'd'])
+        expected['d'] = expected['d'].astype('int64')
         df = DataFrame(columns=['a', 'b', 'c c'])
-        with tm.assert_raises_regex(ValueError, 'If using all scalar values'):
-            df['d'] = 3
+        df['d'] = 3
+        tm.assert_frame_equal(df, expected)
+        tm.assert_series_equal(df['c c'], Series(name='c c', dtype=object))
 
         # reindex columns is ok
         df = DataFrame({"A": [1, 2, 3], "B": [1.2, 4.2, 5.2]})

pandas/tests/reshape/test_pivot.py

@@ -1228,8 +1228,7 @@ def test_crosstab_no_overlap(self):
         s2 = pd.Series([4, 5, 6], index=[4, 5, 6])
 
         actual = crosstab(s1, s2)
-        expected = pd.DataFrame(
-            index=pd.Index([], dtype='int64')).astype('int64')
+        expected = pd.DataFrame()
 
         tm.assert_frame_equal(actual, expected)