Add is_type_compatible for Index & MultiIndex

databricks/koalas/indexes.py

@@ -927,6 +927,24 @@ def is_object(self):
         """
         return is_object_dtype(self.dtype)
 
+    def is_type_compatible(self, kind):
+        """
+        Whether the index type is compatible with the provided type.
+
+        Examples
+        --------
+        >>> kidx = ks.Index([1, 2, 3])
+        >>> kidx.is_type_compatible('integer')
+        True
+
+        >>> kidx = ks.Index([1.0, 2.0, 3.0])
+        >>> kidx.is_type_compatible('integer')
+        False
+        >>> kidx.is_type_compatible('floating')
+        True
+        """
+        return kind == self.inferred_type
+
     def dropna(self):
         """
         Return Index or MultiIndex without NA/NaN values

databricks/koalas/missing/indexes.py

@@ -53,7 +53,6 @@ class MissingPandasLikeIndex(object):
     intersection = _unsupported_function("intersection")
     is_ = _unsupported_function("is_")
     is_lexsorted_for_tuple = _unsupported_function("is_lexsorted_for_tuple")
-    is_type_compatible = _unsupported_function("is_type_compatible")
     join = _unsupported_function("join")
     map = _unsupported_function("map")
     putmask = _unsupported_function("putmask")
@@ -124,7 +123,6 @@ class MissingPandasLikeMultiIndex(object):
     is_ = _unsupported_function("is_")
     is_lexsorted = _unsupported_function("is_lexsorted")
     is_lexsorted_for_tuple = _unsupported_function("is_lexsorted_for_tuple")
-    is_type_compatible = _unsupported_function("is_type_compatible")
     join = _unsupported_function("join")
     map = _unsupported_function("map")
     putmask = _unsupported_function("putmask")

databricks/koalas/tests/test_indexes.py

@@ -1446,6 +1446,38 @@ def test_inferred_type(self):
         kmidx = ks.from_pandas(pmidx)
         self.assert_eq(pmidx.inferred_type, kmidx.inferred_type)
 
+    def test_is_type_compatible(self):
+        data_types = ["integer", "floating", "string", "boolean"]
+        # Integer
+        pidx = pd.Index([1, 2, 3])
+        kidx = ks.from_pandas(pidx)
+        for data_type in data_types:
+            self.assert_eq(pidx.is_type_compatible(data_type), kidx.is_type_compatible(data_type))
+
+        # Floating
+        pidx = pd.Index([1.0, 2.0, 3.0])
+        kidx = ks.from_pandas(pidx)
+        for data_type in data_types:
+            self.assert_eq(pidx.is_type_compatible(data_type), kidx.is_type_compatible(data_type))
+
+        # String
+        pidx = pd.Index(["a", "b", "c"])
+        kidx = ks.from_pandas(pidx)
+        for data_type in data_types:
+            self.assert_eq(pidx.is_type_compatible(data_type), kidx.is_type_compatible(data_type))
+
+        # Boolean
+        pidx = pd.Index([True, False, True, False])
+        kidx = ks.from_pandas(pidx)
+        for data_type in data_types:
+            self.assert_eq(pidx.is_type_compatible(data_type), kidx.is_type_compatible(data_type))
+
+        # MultiIndex
+        pmidx = pd.MultiIndex.from_tuples([("a", "x")])
+        kmidx = ks.from_pandas(pmidx)
+        for data_type in data_types:
+            self.assert_eq(pmidx.is_type_compatible(data_type), kmidx.is_type_compatible(data_type))
+
     def test_asi8(self):
         # Integer
         pidx = pd.Index([1, 2, 3])