FIX apply with an empty dataframe

Author: hayd

pandas/core/frame.py

@@ -1693,7 +1693,9 @@ def info(self, verbose=True, buf=None, max_cols=None):
 
     @property
     def dtypes(self):
-        return self.apply(lambda x: x.dtype)
+        dtypes = self.apply(lambda x: x.dtype)
+        dtypes.name = 'dtypes'
+        return dtypes
 
     def convert_objects(self, convert_dates=True, convert_numeric=False, copy=True):
         """
@@ -4395,20 +4397,28 @@ def apply(self, func, axis=0, broadcast=False, raw=False,
             return self._constructor(data=results, index=self.index,
                                      columns=self.columns, copy=False)
         else:
+            #if not all(self.shape):
+            #    broadcast = True
+
             if not broadcast:
                 if not all(self.shape):
-                    # How to determine this better?
-                    is_reduction = False
-                    try:
-                        is_reduction = not isinstance(f(_EMPTY_SERIES),
-                                                      np.ndarray)
-                    except Exception:
-                        pass
+                    if axis:
+                        result = self._constructor([f(self.iloc[i, :])
+                                                    for i, _ in enumerate(self.index)],
+                                          index=self.index)
+                    else:
+                        result = self._constructor([f(self.iloc[:, i])
+                                                    for i, _ in enumerate(self.columns)],
+                                          index=self.columns)
+
+                    # are these the only cases when we flatten?
+                    if len(result.columns) == 1:
+                        return result.iloc[:, 0]
 
-                    if is_reduction:
-                        return Series(NA, index=self._get_agg_axis(axis))
+                    elif not len(result.index):
+                        return Series(NA, index=result.columns)
                     else:
-                        return self.copy()
+                        return result
 
                 if raw and not self._is_mixed_type:
                     return self._apply_raw(f, axis)

pandas/tests/test_frame.py

@@ -5443,6 +5443,12 @@ def test_dtypes(self):
                           index=result.index)
         assert_series_equal(result, expected)
 
+        # GH4272
+        df = DataFrame(columns=list('xyz'))
+        res = df.dtypes
+        exp = Series((df.iloc[:, i].dtype for i, _ in enumerate(df.columns)), index=df.columns, name='dtypes')
+        assert_series_equal(res, exp)
+
     def test_convert_objects(self):
 
         oops = self.mixed_frame.T.T
@@ -8017,9 +8023,16 @@ def test_apply_empty(self):
         assert_series_equal(result, expected)
 
         # 2476
-        xp = DataFrame(index=['a'])
-        rs = xp.apply(lambda x: x['a'], axis=1)
-        assert_frame_equal(xp, rs)
+        df = DataFrame(index=['a'])
+        rs = df.apply(lambda x: x['a'], axis=0)
+        xp = df.loc['a']
+        xp.name = None
+        assert_series_equal(xp, rs)
+
+        df = DataFrame(columns=['A'])
+        expected = Series(2, ['A'])
+        result = df.apply(lambda x: 2)
+        assert_series_equal(expected, result)
 
     def test_apply_standard_nonunique(self):
         df = DataFrame(