Add some tests, use ABCseries, remove wrong docs for applymap

Author: alonme

pandas/core/apply.py

@@ -18,10 +18,9 @@
 
 from pandas.core.construction import create_series_with_explicit_dtype
 from pandas.core.frame import DataFrame
-from pandas.core.series import Series
 
 if TYPE_CHECKING:
-    from pandas import Index
+    from pandas import Series, Index
 
 ResType = Dict[int, Any]
 
@@ -309,7 +308,7 @@ def apply_standard(self):
                 if partial_result is None:
                     return self.obj._constructor_sliced(result, index=labels)
                 else:
-                    if isinstance(partial_result, Series):
+                    if isinstance(partial_result, ABCSeries):
                         partial_result = DataFrame.infer_objects(partial_result)
 
         # compute the result using the series generator

pandas/core/frame.py

@@ -7307,14 +7307,6 @@ def applymap(self, func) -> "DataFrame":
         --------
         DataFrame.apply : Apply a function along input axis of DataFrame.
 
-        Notes
-        -----
-        In the current implementation applymap calls `func` twice on the
-        first column/row to decide whether it can take a fast or slow
-        code path. This can lead to unexpected behavior if `func` has
-        side-effects, as they will take effect twice for the first
-        column/row.
-
         Examples
         --------
         >>> df = pd.DataFrame([[1, 2.12], [3.356, 4.567]])

pandas/tests/frame/test_apply.py

@@ -726,6 +726,38 @@ def test_apply_noreduction_tzaware_object(self):
         result = df.apply(lambda x: x.copy())
         tm.assert_frame_equal(result, df)
 
+    def test_apply_function_runs_once(self):
+        # https://github.com/pandas-dev/pandas/issues/30815
+        def non_reducing_func_with_state(row):
+            non_reducing_func_with_state.call_count = getattr(non_reducing_func_with_state, 'call_count', 0) + 1
+            return row * non_reducing_func_with_state.call_count
+
+        def reducing_func_with_state(_):
+            reducing_func_with_state.call_count = getattr(reducing_func_with_state, 'call_count', 0) + 1
+            return reducing_func_with_state.call_count
+
+        df = pd.DataFrame({'a': [1, 2, 3]})
+
+        # no reduction
+        res0 = df.apply(non_reducing_func_with_state)
+        tm.assert_frame_equal(res0, df)
+
+        # reduction
+        res1 = df.apply(reducing_func_with_state)
+        tm.assert_series_equal(res1, Series(data=[1], index=['a']))
+
+    def test_applymap_function_runs_once(self):
+
+        # This function will create the same values as in the DataFrame
+        def func_with_state(_):
+            func_with_state.call_count = getattr(func_with_state, 'call_count', 0) + 1
+            return func_with_state.call_count
+
+        df = pd.DataFrame({'a': [1, 2, 3]})
+        result = df.applymap(func_with_state)
+        tm.assert_frame_equal(result, df)
+
+
 
 class TestInferOutputShape:
     # the user has supplied an opaque UDF where