ENH: Add index param to df.to_dict

doc/source/whatsnew/v1.6.0.rst

@@ -31,6 +31,7 @@ Other enhancements
 - :meth:`.GroupBy.quantile` now preserving nullable dtypes instead of casting to numpy dtypes (:issue:`37493`)
 - :meth:`Series.add_suffix`, :meth:`DataFrame.add_suffix`, :meth:`Series.add_prefix` and :meth:`DataFrame.add_prefix` support an ``axis`` argument. If ``axis`` is set, the default behaviour of which axis to consider can be overwritten (:issue:`47819`)
 - :func:`assert_frame_equal` now shows the first element where the DataFrames differ, analogously to ``pytest``'s output (:issue:`47910`)
+- Added ``index`` parameter to :meth:`DataFrame.to_dict` (:issue:`46398`)
 -
 
 .. ---------------------------------------------------------------------------

pandas/core/frame.py

@@ -1864,6 +1864,7 @@ def to_dict(
             "dict", "list", "series", "split", "tight", "records", "index"
         ] = "dict",
         into: type[dict] = dict,
+        index: bool = True,
     ) -> dict | list[dict]:
         """
         Convert the DataFrame to a dictionary.
@@ -1900,6 +1901,13 @@ def to_dict(
             instance of the mapping type you want.  If you want a
             collections.defaultdict, you must pass it initialized.
 
+        index : bool, default True
+            Whether to include the index item (and index_names item if `orient`
+            is 'tight') in the returned dictionary. Can only be ``False``
+            when `orient` is 'split' or 'tight'.
+
+            .. versionadded:: 1.6.0
+
         Returns
         -------
         dict, list or collections.abc.Mapping
@@ -2005,6 +2013,11 @@ def to_dict(
             elif orient.startswith("i"):
                 orient = "index"
 
+        if not index and orient not in ["split", "tight"]:
+            raise ValueError(
+                "'index=False' is only valid when 'orient' is 'split' or 'tight'"
+            )
+
         if orient == "dict":
             return into_c((k, v.to_dict(into)) for k, v in self.items())
 
@@ -2015,8 +2028,8 @@ def to_dict(
 
         elif orient == "split":
             return into_c(
-                (
-                    ("index", self.index.tolist()),
+                ((("index", self.index.tolist()),) if index else ())
+                + (
                     ("columns", self.columns.tolist()),
                     (
                         "data",
@@ -2030,8 +2043,8 @@ def to_dict(
 
         elif orient == "tight":
             return into_c(
-                (
-                    ("index", self.index.tolist()),
+                ((("index", self.index.tolist()),) if index else ())
+                + (
                     ("columns", self.columns.tolist()),
                     (
                         "data",
@@ -2040,9 +2053,9 @@ def to_dict(
                             for t in self.itertuples(index=False, name=None)
                         ],
                     ),
-                    ("index_names", list(self.index.names)),
-                    ("column_names", list(self.columns.names)),
                 )
+                + ((("index_names", list(self.index.names)),) if index else ())
+                + (("column_names", list(self.columns.names)),)
             )
 
         elif orient == "series":

pandas/tests/frame/methods/test_to_dict.py

@@ -421,3 +421,31 @@ def test_to_dict_returns_native_types(self, orient, data, expected_types):
         for i, key, value in assertion_iterator:
             assert value == data[key][i]
             assert type(value) is expected_types[key][i]
+
+    @pytest.mark.parametrize("orient", ["dict", "list", "series", "records", "index"])
+    def test_to_dict_index_false_error(self, orient):
+        # GH#46398
+        df = DataFrame({"col1": [1, 2], "col2": [3, 4]}, index=["row1", "row2"])
+        msg = "'index=False' is only valid when 'orient' is 'split' or 'tight'"
+        with pytest.raises(ValueError, match=msg):
+            df.to_dict(orient=orient, index=False)
+
+    @pytest.mark.parametrize(
+        "orient, expected",
+        [
+            ("split", {"columns": ["col1", "col2"], "data": [[1, 3], [2, 4]]}),
+            (
+                "tight",
+                {
+                    "columns": ["col1", "col2"],
+                    "data": [[1, 3], [2, 4]],
+                    "column_names": [None],
+                },
+            ),
+        ],
+    )
+    def test_to_dict_index_false(self, orient, expected):
+        # GH#46398
+        df = DataFrame({"col1": [1, 2], "col2": [3, 4]}, index=["row1", "row2"])
+        result = df.to_dict(orient=orient, index=False)
+        tm.assert_dict_equal(result, expected)