DEPR: Series/DataFrame/HDFStore.iteritems()

doc/source/user_guide/scale.rst

@@ -275,6 +275,7 @@ column names and dtypes. That's because Dask hasn't actually read the data yet.
 Rather than executing immediately, doing operations build up a **task graph**.
 
 .. ipython:: python
+   :okwarning:
 
    ddf
    ddf["name"]
@@ -333,6 +334,7 @@ known automatically. In this case, since we created the parquet files manually,
 we need to supply the divisions manually.
 
 .. ipython:: python
+   :okwarning:
 
    N = 12
    starts = [f"20{i:>02d}-01-01" for i in range(N)]

doc/source/whatsnew/v1.5.0.rst

@@ -95,6 +95,7 @@ Other API changes
 Deprecations
 ~~~~~~~~~~~~
 - Deprecated the keyword ``line_terminator`` in :meth:`DataFrame.to_csv` and :meth:`Series.to_csv`, use ``lineterminator`` instead; this is for consistency with :func:`read_csv` and the standard library 'csv' module (:issue:`9568`)
+- Deprecated :meth:`DataFrame.iteritems`, :meth:`Series.iteritems`, :meth:`HDFStore.iteritems` in favor of :meth:`DataFrame.items`, :meth:`Series.items`, :meth:`HDFStore.items`  (:issue:`45321`)
 -
 
 .. ---------------------------------------------------------------------------

pandas/core/arrays/sparse/accessor.py

@@ -339,7 +339,7 @@ def to_coo(self):
             dtype = dtype.subtype
 
         cols, rows, data = [], [], []
-        for col, (_, ser) in enumerate(self._parent.iteritems()):
+        for col, (_, ser) in enumerate(self._parent.items()):
             sp_arr = ser.array
             if sp_arr.fill_value != 0:
                 raise ValueError("fill value must be 0 when converting to COO matrix")

pandas/core/frame.py

@@ -1276,6 +1276,12 @@ def items(self) -> Iterable[tuple[Hashable, Series]]:
 
     @Appender(_shared_docs["items"])
     def iteritems(self) -> Iterable[tuple[Hashable, Series]]:
+        warnings.warn(
+            "iteritems is deprecated and will be removed in a future version. "
+            "Use .items instead.",
+            FutureWarning,
+            stacklevel=find_stack_level(),
+        )
         yield from self.items()
 
     def iterrows(self) -> Iterable[tuple[Hashable, Series]]:

pandas/core/generic.py

@@ -1989,10 +1989,6 @@ def items(self):
         for h in self._info_axis:
             yield h, self[h]
 
-    @doc(items)
-    def iteritems(self):
-        return self.items()
-
     def __len__(self) -> int:
         """Returns length of info axis"""
         return len(self._info_axis)
@@ -5855,19 +5851,20 @@ def astype(
                 new_type = dtype[self.name]
                 return self.astype(new_type, copy, errors)
 
-            for col_name in dtype.keys():
+            # GH#44417 cast to Series so we can use .iat below, which will be
+            #  robust in case we
+            from pandas import Series
+
+            dtype_ser = Series(dtype, dtype=object)
+
+            for col_name in dtype_ser.index:
                 if col_name not in self:
                     raise KeyError(
                         "Only a column name can be used for the "
                         "key in a dtype mappings argument. "
                         f"'{col_name}' not found in columns."
                     )
 
-            # GH#44417 cast to Series so we can use .iat below, which will be
-            #  robust in case we
-            from pandas import Series
-
-            dtype_ser = Series(dtype, dtype=object)
             dtype_ser = dtype_ser.reindex(self.columns, fill_value=None, copy=False)
 
             results = []

pandas/core/series.py

@@ -1705,6 +1705,12 @@ def items(self) -> Iterable[tuple[Hashable, Any]]:
 
     @Appender(items.__doc__)
     def iteritems(self) -> Iterable[tuple[Hashable, Any]]:
+        warnings.warn(
+            "iteritems is deprecated and will be removed in a future version. "
+            "Use .items instead.",
+            FutureWarning,
+            stacklevel=find_stack_level(),
+        )
         return self.items()
 
     # ----------------------------------------------------------------------

pandas/io/pytables.py

@@ -692,7 +692,17 @@ def items(self):
         for g in self.groups():
             yield g._v_pathname, g
 
-    iteritems = items
+    def iteritems(self):
+        """
+        iterate on key->group
+        """
+        warnings.warn(
+            "iteritems is deprecated and will be removed in a future version. "
+            "Use .items instead.",
+            FutureWarning,
+            stacklevel=find_stack_level(),
+        )
+        yield from self.items()
 
     def open(self, mode: str = "a", **kwargs):
         """

pandas/tests/frame/test_api.py

@@ -366,3 +366,8 @@ def test_inspect_getmembers(self):
         df = DataFrame()
         with tm.assert_produces_warning(None):
             inspect.getmembers(df)
+
+    def test_dataframe_iteritems_deprecated(self):
+        df = DataFrame([1])
+        with tm.assert_produces_warning(FutureWarning):
+            next(df.iteritems())

pandas/tests/groupby/test_apply.py

@@ -843,7 +843,7 @@ def test_apply_series_return_dataframe_groups():
     )
 
     def most_common_values(df):
-        return Series({c: s.value_counts().index[0] for c, s in df.iteritems()})
+        return Series({c: s.value_counts().index[0] for c, s in df.items()})
 
     result = tdf.groupby("day").apply(most_common_values)["userId"]
     expected = Series(

pandas/tests/io/pytables/test_store.py

@@ -1011,3 +1011,12 @@ def test_to_hdf_with_object_column_names(setup_path):
                 df.to_hdf(path, "df", format="table", data_columns=True)
                 result = read_hdf(path, "df", where=f"index = [{df.index[0]}]")
                 assert len(result)
+
+
+def test_hdfstore_iteritems_deprecated(setup_path):
+    with ensure_clean_path(setup_path) as path:
+        df = DataFrame({"a": [1]})
+        with HDFStore(path, mode="w") as hdf:
+            hdf.put("table", df)
+            with tm.assert_produces_warning(FutureWarning):
+                next(hdf.iteritems())

pandas/tests/series/test_api.py

@@ -203,3 +203,8 @@ def test_series_datetimelike_attribute_access_invalid(self):
         msg = "'Series' object has no attribute 'weekday'"
         with pytest.raises(AttributeError, match=msg):
             ser.weekday
+
+    def test_series_iteritems_deprecated(self):
+        ser = Series([1])
+        with tm.assert_produces_warning(FutureWarning):
+            next(ser.iteritems())

pandas/tests/series/test_iteration.py

@@ -11,15 +11,15 @@ def test_iter_strings(self, string_series):
             assert val == string_series[i]
 
     def test_iteritems_datetimes(self, datetime_series):
-        for idx, val in datetime_series.iteritems():
+        for idx, val in datetime_series.items():
             assert val == datetime_series[idx]
 
     def test_iteritems_strings(self, string_series):
-        for idx, val in string_series.iteritems():
+        for idx, val in string_series.items():
             assert val == string_series[idx]
 
         # assert is lazy (generators don't define reverse, lists do)
-        assert not hasattr(string_series.iteritems(), "reverse")
+        assert not hasattr(string_series.items(), "reverse")
 
     def test_items_datetimes(self, datetime_series):
         for idx, val in datetime_series.items():