Fix deprecation warnings with is_categorical_dtype (#2641)

* update pandas calls * update release notes * update woodwork * update woodwork * update woodwork * update reqs * more reqs * fix isinstance check --------- Co-authored-by: Nate Parsons <[email protected]> Co-authored-by: Nate Parsons <[email protected]>
alteryx · Feb 14, 2024 · 18e5c41 · 18e5c41
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commit 18e5c41
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Showing 6 changed files with 10 additions and 14 deletions.
diff --git a/docs/source/release_notes.rst b/docs/source/release_notes.rst
@@ -10,6 +10,7 @@ Future Release
         * Fix dependency issues (:pr:`2644`, :pr:`2656`)
         * Add workaround for pandas 2.2.0 bug with nunique and unpin pandas (:pr:`2657`)
     * Changes
+        * Fix deprecation warnings with is_categorical_dtype (:pr:`2641`)
     * Documentation Changes
         * Update Featuretools logo to display properly in dark mode (:pr:`2632`)
     * Testing Changes
@@ -21,7 +22,6 @@ Future Release
         * Fix minimum dependency checker action (:pr:`2664`)
         * Fix Slack alert for tests with Woodwork main branch (:pr:`2668`)
 
-
     Thanks to the following people for contributing to this release:
     :user:`gsheni`, :user:`thehomebrewnerd`, :user:`tamargrey`, :user:`LakshmanKishore`
 

diff --git a/featuretools/computational_backends/feature_set_calculator.py b/featuretools/computational_backends/feature_set_calculator.py
@@ -835,7 +835,7 @@ def last_n(df):
                 #
                 # Pandas claims that bug is fixed but it still shows up in some
                 # cases.  More investigation needed.
-                if pdtypes.is_categorical_dtype(frame.index):
+                if isinstance(frame.index, pd.CategoricalDtype):
                     categories = pdtypes.CategoricalDtype(
                         categories=frame.index.categories,
                     )

diff --git a/featuretools/primitives/standard/transform/binary/greater_than.py b/featuretools/primitives/standard/transform/binary/greater_than.py
@@ -1,6 +1,5 @@
 import numpy as np
 import pandas as pd
-import pandas.api.types as pdtypes
 from woodwork.column_schema import ColumnSchema
 from woodwork.logical_types import BooleanNullable, Datetime, Ordinal
 
@@ -37,8 +36,8 @@ class GreaterThan(TransformPrimitive):
 
     def get_function(self):
         def greater_than(val1, val2):
-            val1_is_categorical = pdtypes.is_categorical_dtype(val1)
-            val2_is_categorical = pdtypes.is_categorical_dtype(val2)
+            val1_is_categorical = isinstance(val1.dtype, pd.CategoricalDtype)
+            val2_is_categorical = isinstance(val2.dtype, pd.CategoricalDtype)
             if val1_is_categorical and val2_is_categorical:
                 if not all(val1.cat.categories == val2.cat.categories):
                     return val1.where(pd.isnull, np.nan)

diff --git a/featuretools/primitives/standard/transform/binary/greater_than_equal_to.py b/featuretools/primitives/standard/transform/binary/greater_than_equal_to.py
@@ -1,6 +1,5 @@
 import numpy as np
 import pandas as pd
-import pandas.api.types as pdtypes
 from woodwork.column_schema import ColumnSchema
 from woodwork.logical_types import BooleanNullable, Datetime, Ordinal
 
@@ -37,8 +36,8 @@ class GreaterThanEqualTo(TransformPrimitive):
 
     def get_function(self):
         def greater_than_equal(val1, val2):
-            val1_is_categorical = pdtypes.is_categorical_dtype(val1)
-            val2_is_categorical = pdtypes.is_categorical_dtype(val2)
+            val1_is_categorical = isinstance(val1.dtype, pd.CategoricalDtype)
+            val2_is_categorical = isinstance(val2.dtype, pd.CategoricalDtype)
             if val1_is_categorical and val2_is_categorical:
                 if not all(val1.cat.categories == val2.cat.categories):
                     return val1.where(pd.isnull, np.nan)

diff --git a/featuretools/primitives/standard/transform/binary/less_than.py b/featuretools/primitives/standard/transform/binary/less_than.py
@@ -1,6 +1,5 @@
 import numpy as np
 import pandas as pd
-import pandas.api.types as pdtypes
 from woodwork.column_schema import ColumnSchema
 from woodwork.logical_types import BooleanNullable, Datetime, Ordinal
 
@@ -37,8 +36,8 @@ class LessThan(TransformPrimitive):
 
     def get_function(self):
         def less_than(val1, val2):
-            val1_is_categorical = pdtypes.is_categorical_dtype(val1)
-            val2_is_categorical = pdtypes.is_categorical_dtype(val2)
+            val1_is_categorical = isinstance(val1.dtype, pd.CategoricalDtype)
+            val2_is_categorical = isinstance(val2.dtype, pd.CategoricalDtype)
             if val1_is_categorical and val2_is_categorical:
                 if not all(val1.cat.categories == val2.cat.categories):
                     return val1.where(pd.isnull, np.nan)

diff --git a/featuretools/primitives/standard/transform/binary/less_than_equal_to.py b/featuretools/primitives/standard/transform/binary/less_than_equal_to.py
@@ -1,6 +1,5 @@
 import numpy as np
 import pandas as pd
-import pandas.api.types as pdtypes
 from woodwork.column_schema import ColumnSchema
 from woodwork.logical_types import BooleanNullable, Datetime, Ordinal
 
@@ -37,8 +36,8 @@ class LessThanEqualTo(TransformPrimitive):
 
     def get_function(self):
         def less_than_equal(val1, val2):
-            val1_is_categorical = pdtypes.is_categorical_dtype(val1)
-            val2_is_categorical = pdtypes.is_categorical_dtype(val2)
+            val1_is_categorical = isinstance(val1.dtype, pd.CategoricalDtype)
+            val2_is_categorical = isinstance(val2.dtype, pd.CategoricalDtype)
             if val1_is_categorical and val2_is_categorical:
                 if not all(val1.cat.categories == val2.cat.categories):
                     return val1.where(pd.isnull, np.nan)