DEPR: deprecate Index.is_object (#50227)

* Deprecate is_object

Co-authored-by: Terji Petersen <[email protected]>

Author: bang128

doc/source/whatsnew/v2.0.0.rst

@@ -637,6 +637,7 @@ Deprecations
 - :meth:`Index.is_floating` has been deprecated. Use :func:`pandas.api.types.is_float_dtype` instead (:issue:`50042`)
 - :meth:`Index.holds_integer` has been deprecated. Use :func:`pandas.api.types.infer_dtype` instead (:issue:`50243`)
 - :meth:`Index.is_categorical` has been deprecated. Use :func:`pandas.api.types.is_categorical_dtype` instead (:issue:`50042`)
+- :meth:`Index.is_object` has been deprecated. Use :func:`pandas.api.types.is_object_dtype` instead (:issue:`50042`)
 - :meth:`Index.is_interval` has been deprecated. Use :func:`pandas.api.types.is_intterval_dtype` instead (:issue:`50042`)
 -
 

pandas/core/indexes/base.py

@@ -1348,7 +1348,7 @@ def _format_native_types(
             return formatter.get_result_as_array()
 
         mask = isna(self)
-        if not self.is_object() and not quoting:
+        if not is_object_dtype(self) and not quoting:
             values = np.asarray(self).astype(str)
         else:
             values = np.array(self, dtype=object, copy=True)
@@ -2258,7 +2258,7 @@ def is_boolean(self) -> bool:
         is_integer : Check if the Index only consists of integers (deprecated).
         is_floating : Check if the Index is a floating type (deprecated).
         is_numeric : Check if the Index only consists of numeric data.
-        is_object : Check if the Index is of the object dtype.
+        is_object : Check if the Index is of the object dtype (deprecated).
         is_categorical : Check if the Index holds categorical data.
         is_interval : Check if the Index holds Interval objects (deprecated).
 
@@ -2302,7 +2302,7 @@ def is_integer(self) -> bool:
         is_boolean : Check if the Index only consists of booleans (deprecated).
         is_floating : Check if the Index is a floating type (deprecated).
         is_numeric : Check if the Index only consists of numeric data.
-        is_object : Check if the Index is of the object dtype.
+        is_object : Check if the Index is of the object dtype. (deprecated).
         is_categorical : Check if the Index holds categorical data (deprecated).
         is_interval : Check if the Index holds Interval objects (deprecated).
 
@@ -2350,7 +2350,7 @@ def is_floating(self) -> bool:
         is_boolean : Check if the Index only consists of booleans (deprecated).
         is_integer : Check if the Index only consists of integers (deprecated).
         is_numeric : Check if the Index only consists of numeric data.
-        is_object : Check if the Index is of the object dtype.
+        is_object : Check if the Index is of the object dtype. (deprecated).
         is_categorical : Check if the Index holds categorical data (deprecated).
         is_interval : Check if the Index holds Interval objects (deprecated).
 
@@ -2395,7 +2395,7 @@ def is_numeric(self) -> bool:
         is_boolean : Check if the Index only consists of booleans (deprecated).
         is_integer : Check if the Index only consists of integers (deprecated).
         is_floating : Check if the Index is a floating type (deprecated).
-        is_object : Check if the Index is of the object dtype.
+        is_object : Check if the Index is of the object dtype. (deprecated).
         is_categorical : Check if the Index holds categorical data (deprecated).
         is_interval : Check if the Index holds Interval objects (deprecated).
 
@@ -2428,6 +2428,9 @@ def is_object(self) -> bool:
         """
         Check if the Index is of the object dtype.
 
+        .. deprecated:: 2.0.0
+           Use `pandas.api.types.is_object_dtype` instead.
+
         Returns
         -------
         bool
@@ -2461,6 +2464,12 @@ def is_object(self) -> bool:
         >>> idx.is_object()
         False
         """
+        warnings.warn(
+            f"{type(self).__name__}.is_object is deprecated."
+            "Use pandas.api.types.is_object_dtype instead",
+            FutureWarning,
+            stacklevel=find_stack_level(),
+        )
         return is_object_dtype(self.dtype)
 
     @final
@@ -2483,7 +2492,7 @@ def is_categorical(self) -> bool:
         is_integer : Check if the Index only consists of integers (deprecated).
         is_floating : Check if the Index is a floating type (deprecated).
         is_numeric : Check if the Index only consists of numeric data.
-        is_object : Check if the Index is of the object dtype.
+        is_object : Check if the Index is of the object dtype. (deprecated).
         is_interval : Check if the Index holds Interval objects (deprecated).
 
         Examples
@@ -2536,7 +2545,7 @@ def is_interval(self) -> bool:
         is_integer : Check if the Index only consists of integers (deprecated).
         is_floating : Check if the Index is a floating type (deprecated).
         is_numeric : Check if the Index only consists of numeric data.
-        is_object : Check if the Index is of the object dtype.
+        is_object : Check if the Index is of the object dtype. (deprecated).
         is_categorical : Check if the Index holds categorical data (deprecated).
 
         Examples
@@ -5018,7 +5027,7 @@ def _is_memory_usage_qualified(self) -> bool:
         """
         Return a boolean if we need a qualified .info display.
         """
-        return self.is_object()
+        return is_object_dtype(self.dtype)
 
     def __contains__(self, key: Any) -> bool:
         """
@@ -5132,7 +5141,7 @@ def _can_hold_identifiers_and_holds_name(self, name) -> bool:
         https://github.com/pandas-dev/pandas/issues/19764
         """
         if (
-            self.is_object()
+            is_object_dtype(self.dtype)
             or is_string_dtype(self.dtype)
             or is_categorical_dtype(self.dtype)
         ):

pandas/io/pytables.py

@@ -72,6 +72,7 @@
     is_extension_array_dtype,
     is_integer_dtype,
     is_list_like,
+    is_object_dtype,
     is_string_dtype,
     is_timedelta64_dtype,
     needs_i8_conversion,
@@ -2560,7 +2561,7 @@ class DataIndexableCol(DataCol):
     is_data_indexable = True
 
     def validate_names(self) -> None:
-        if not Index(self.values).is_object():
+        if not is_object_dtype(Index(self.values)):
             # TODO: should the message here be more specifically non-str?
             raise ValueError("cannot have non-object label DataIndexableCol")
 

pandas/tests/indexes/common.py

@@ -829,6 +829,12 @@ def test_is_interval_is_deprecated(self, simple_index):
         with tm.assert_produces_warning(FutureWarning):
             idx.is_interval()
 
+    def test_is_object_is_deprecated(self, simple_index):
+        # GH50042
+        idx = simple_index
+        with tm.assert_produces_warning(FutureWarning):
+            idx.is_object()
+
 
 class NumericBase(Base):
     """

pandas/tests/indexes/test_base.py

@@ -18,7 +18,10 @@
 )
 from pandas.util._test_decorators import async_mark
 
-from pandas.core.dtypes.common import is_numeric_dtype
+from pandas.core.dtypes.common import (
+    is_numeric_dtype,
+    is_object_dtype,
+)
 
 import pandas as pd
 from pandas import (
@@ -677,7 +680,7 @@ def test_is_numeric(self, index, expected):
         indirect=["index"],
     )
     def test_is_object(self, index, expected):
-        assert index.is_object() is expected
+        assert is_object_dtype(index) is expected
 
     def test_summary(self, index):
         index._summary()

pandas/tests/indexing/test_indexing.py

@@ -13,6 +13,7 @@
 from pandas.core.dtypes.common import (
     is_float_dtype,
     is_integer_dtype,
+    is_object_dtype,
 )
 
 import pandas as pd
@@ -618,7 +619,7 @@ def test_index_type_coercion(self, indexer):
 
             s2 = s.copy()
             indexer(s2)["0"] = 0
-            assert s2.index.is_object()
+            assert is_object_dtype(s2.index)
 
         for s in [Series(range(5), index=np.arange(5.0))]:
 
@@ -635,7 +636,7 @@ def test_index_type_coercion(self, indexer):
 
             s2 = s.copy()
             indexer(s2)["0"] = 0
-            assert s2.index.is_object()
+            assert is_object_dtype(s2.index)
 
 
 class TestMisc:

pandas/tests/series/methods/test_drop.py

@@ -5,6 +5,7 @@
     Series,
 )
 import pandas._testing as tm
+from pandas.api.types import is_bool_dtype
 
 
 @pytest.mark.parametrize(
@@ -57,7 +58,7 @@ def test_drop_with_ignore_errors():
 
     # GH 8522
     ser = Series([2, 3], index=[True, False])
-    assert not ser.index.is_object()
+    assert is_bool_dtype(ser.index)
     assert ser.index.dtype == bool
     result = ser.drop(True)
     expected = Series([3], index=[False])