ENH: Add MultiIndex.dtypes

doc/source/reference/indexing.rst

@@ -290,6 +290,7 @@ MultiIndex properties
    MultiIndex.codes
    MultiIndex.nlevels
    MultiIndex.levshape
+   MultiIndex.dtypes
 
 MultiIndex components
 ~~~~~~~~~~~~~~~~~~~~~

doc/source/whatsnew/v1.2.0.rst

@@ -240,6 +240,7 @@ Other enhancements
 - Calling a NumPy ufunc on a ``DataFrame`` with extension types now preserves the extension types when possible (:issue:`23743`).
 - Calling a binary-input NumPy ufunc on multiple ``DataFrame`` objects now aligns, matching the behavior of binary operations and ufuncs on ``Series`` (:issue:`23743`).
 - Where possible :meth:`RangeIndex.difference` and :meth:`RangeIndex.symmetric_difference` will return :class:`RangeIndex` instead of :class:`Int64Index` (:issue:`36564`)
+- Added :meth:`MultiIndex.dtypes` (:issue:`37062`)
 - :meth:`DataFrame.to_parquet` now supports :class:`MultiIndex` for columns in parquet format (:issue:`34777`)
 - Added :meth:`.Rolling.sem` and :meth:`Expanding.sem` to compute the standard error of the mean (:issue:`26476`)
 - :meth:`.Rolling.var` and :meth:`.Rolling.std` use Kahan summation and Welford's Method to avoid numerical issues (:issue:`37051`)

pandas/core/indexes/multi.py

@@ -701,6 +701,15 @@ def array(self):
             "'MultiIndex.to_numpy()' to get a NumPy array of tuples."
         )
 
+    @cache_readonly
+    def dtypes(self):
+        """
+        Return the dtypes as a Series for the underlying MultiIndex
+        """
+        from pandas import Series
+
+        return Series({level.name: level.dtype for level in self.levels})
+
     @property
     def shape(self) -> Shape:
         """

pandas/tests/indexes/multi/conftest.py

@@ -24,6 +24,18 @@ def idx():
     return mi
 
 
+@pytest.fixture
+def idx_multitype():
+    # a MultiIndex with several dtypes
+    first_axis = [1, 2, 3]
+    second_axis = list("abc")
+    third_axis = pd.date_range("20200101", periods=2, tz="UTC")
+    mi = MultiIndex.from_product(
+        [first_axis, second_axis, third_axis], names=["int", "string", "dt"]
+    )
+    return mi
+
+
 @pytest.fixture
 def idx_dup():
     # compare tests/indexes/multi/conftest.py

pandas/tests/indexes/multi/test_get_set.py

@@ -1,6 +1,8 @@
 import numpy as np
 import pytest
 
+from pandas.core.dtypes.dtypes import DatetimeTZDtype as DateTimeTZDtype
+
 import pandas as pd
 from pandas import CategoricalIndex, MultiIndex
 import pandas._testing as tm
@@ -27,6 +29,18 @@ def test_get_level_number_integer(idx):
         idx._get_level_number("fourth")
 
 
+def test_get_dtypes(idx_multitype):
+    # Test MultiIndex.dtypes (GH-37062)
+    expected = pd.Series(
+        {
+            "int": np.dtype("int64"),
+            "string": np.dtype("O"),
+            "dt": DateTimeTZDtype(tz="utc"),
+        }
+    )
+    assert expected.equals(idx_multitype.dtypes)
+
+
 def test_get_level_number_out_of_bounds(multiindex_dataframe_random_data):
     frame = multiindex_dataframe_random_data