[WIP] Relaxes matplotlib dependency

ads/common/utils.py

@@ -782,9 +782,7 @@ def default(self, obj):
             ),
         ):
             return int(obj)
-        elif isinstance(
-            obj, (np.float_, np.float16, np.float32, np.float64, np.double)
-        ):
+        elif isinstance(obj, (np.float16, np.float32, np.float64, np.double)):
             return float(obj)
         elif isinstance(obj, (np.ndarray,)):
             return obj.tolist()

ads/feature_engineering/feature_type/boolean.py

@@ -1,7 +1,6 @@
 #!/usr/bin/env python
-# -*- coding: utf-8 -*--
 
-# Copyright (c) 2021, 2022 Oracle and/or its affiliates.
+# Copyright (c) 2021, 2025 Oracle and/or its affiliates.
 # Licensed under the Universal Permissive License v 1.0 as shown at https://oss.oracle.com/licenses/upl/
 
 """
@@ -15,19 +14,21 @@
     default_handler(data: pd.Series) -> pd.Series
         Processes given data and indicates if the data matches requirements.
 """
+
 import matplotlib.pyplot as plt
 import pandas as pd
+
+from ads.common.decorator.runtime_dependency import (
+    OptionalDependency,
+    runtime_dependency,
+)
+from ads.feature_engineering import schema
 from ads.feature_engineering.feature_type.base import FeatureType
 from ads.feature_engineering.utils import (
+    SchemeTeal,
     _count_unique_missing,
-    is_boolean,
     _set_seaborn_theme,
-    SchemeTeal,
-)
-from ads.feature_engineering import schema
-from ads.common.decorator.runtime_dependency import (
-    runtime_dependency,
-    OptionalDependency,
+    is_boolean,
 )
 
 
@@ -44,7 +45,7 @@ def default_handler(data: pd.Series, *args, **kwargs) -> pd.Series:
     :class:`pandas.Series`
         The logical list indicating if the data matches requirements.
     """
-    return pd.Series((is_boolean(value) for value in data.values))
+    return pd.Series(is_boolean(value) for value in data.values)
 
 
 class Boolean(FeatureType):
@@ -74,7 +75,7 @@ class Boolean(FeatureType):
     >>> from ads.feature_engineering.feature_type.boolean import Boolean
     >>> import pandas as pd
     >>> import numpy as np
-    >>> s = pd.Series([True, False, True, False, np.NaN, None], name='bool')
+    >>> s = pd.Series([True, False, True, False, np.nan, None], name='bool')
     >>> s.ads.feature_type = ['boolean']
     >>> Boolean.validator.is_boolean(s)
     0     True
@@ -106,7 +107,7 @@ def feature_stat(x: pd.Series) -> pd.DataFrame:
 
         Examples
         --------
-        >>> s = pd.Series([True, False, True, False, np.NaN, None], name='bool')
+        >>> s = pd.Series([True, False, True, False, np.nan, None], name='bool')
         >>> s.ads.feature_type = ['boolean']
         >>> s.ads.feature_stat()
             Metric  Value
@@ -134,7 +135,7 @@ def feature_plot(x: pd.Series) -> plt.Axes:
 
         Examples
         --------
-        >>> s = pd.Series([True, False, True, False, np.NaN, None], name='bool')
+        >>> s = pd.Series([True, False, True, False, np.nan, None], name='bool')
         >>> s.ads.feature_type = ['boolean']
         >>> s.ads.feature_plot()
         """
@@ -155,7 +156,7 @@ def feature_domain(cls, x: pd.Series) -> schema.Domain:
 
         Examples
         --------
-        >>> s = pd.Series([True, False, True, False, np.NaN, None], name='bool')
+        >>> s = pd.Series([True, False, True, False, np.nan, None], name='bool')
         >>> s.ads.feature_type = ['boolean']
         >>> s.ads.feature_domain()
         constraints:

ads/feature_engineering/feature_type/category.py

@@ -1,7 +1,6 @@
 #!/usr/bin/env python
-# -*- coding: utf-8 -*--
 
-# Copyright (c) 2021, 2022 Oracle and/or its affiliates.
+# Copyright (c) 2021, 2025 Oracle and/or its affiliates.
 # Licensed under the Universal Permissive License v 1.0 as shown at https://oss.oracle.com/licenses/upl/
 
 """
@@ -11,18 +10,20 @@
     Category
         The Category feature type.
 """
+
 import matplotlib.pyplot as plt
 import pandas as pd
+
+from ads.common.decorator.runtime_dependency import (
+    OptionalDependency,
+    runtime_dependency,
+)
+from ads.feature_engineering import schema
 from ads.feature_engineering.feature_type.base import FeatureType
 from ads.feature_engineering.utils import (
+    SchemeTeal,
     _count_unique_missing,
     _set_seaborn_theme,
-    SchemeTeal,
-)
-from ads.feature_engineering import schema
-from ads.common.decorator.runtime_dependency import (
-    runtime_dependency,
-    OptionalDependency,
 )
 
 
@@ -71,7 +72,7 @@ def feature_stat(x: pd.Series) -> pd.DataFrame:
         Examples
         --------
         >>> cat = pd.Series(['S', 'C', 'S', 'S', 'S', 'Q', 'S', 'S', 'S', 'C', 'S', 'S', 'S',
-                    'S', 'S', 'S', 'Q', 'S', 'S', '', np.NaN, None], name='сategory')
+                    'S', 'S', 'S', 'Q', 'S', 'S', '', np.nan, None], name='сategory')
         >>> cat.ads.feature_type = ['сategory']
         >>> cat.ads.feature_stat()
             Metric  Value
@@ -100,7 +101,7 @@ def feature_plot(x: pd.Series) -> plt.Axes:
         Examples
         --------
         >>> cat = pd.Series(['S', 'C', 'S', 'S', 'S', 'Q', 'S', 'S', 'S', 'C', 'S', 'S', 'S',
-                    'S', 'S', 'S', 'Q', 'S', 'S', '', np.NaN, None], name='сategory')
+                    'S', 'S', 'S', 'Q', 'S', 'S', '', np.nan, None], name='сategory')
         >>> cat.ads.feature_type = ['сategory']
         >>> cat.ads.feature_plot()
         """
@@ -121,7 +122,7 @@ def feature_domain(cls, x: pd.Series) -> schema.Domain:
         Examples
         --------
         >>> cat = pd.Series(['S', 'C', 'S', 'S', 'S', 'Q', 'S', 'S', 'S', 'C', 'S', 'S', 'S',
-                    'S', 'S', 'S', 'Q', 'S', 'S', '', np.NaN, None], name='category')
+                    'S', 'S', 'S', 'Q', 'S', 'S', '', np.nan, None], name='category')
         >>> cat.ads.feature_type = ['category']
         >>> cat.ads.feature_domain()
         constraints:

ads/feature_engineering/feature_type/continuous.py

@@ -1,7 +1,6 @@
 #!/usr/bin/env python
-# -*- coding: utf-8 -*--
 
-# Copyright (c) 2021, 2022 Oracle and/or its affiliates.
+# Copyright (c) 2021, 2025 Oracle and/or its affiliates.
 # Licensed under the Universal Permissive License v 1.0 as shown at https://oss.oracle.com/licenses/upl/
 
 """
@@ -11,19 +10,21 @@
     Continuous
         The Continuous feature type.
 """
+
 import matplotlib.pyplot as plt
 import pandas as pd
+
+from ads.common.decorator.runtime_dependency import (
+    OptionalDependency,
+    runtime_dependency,
+)
+from ads.feature_engineering import schema
 from ads.feature_engineering.feature_type.base import FeatureType
 from ads.feature_engineering.utils import (
-    _add_missing,
-    _set_seaborn_theme,
     SchemeTeal,
+    _add_missing,
     _format_stat,
-)
-from ads.feature_engineering import schema
-from ads.common.decorator.runtime_dependency import (
-    runtime_dependency,
-    OptionalDependency,
+    _set_seaborn_theme,
 )
 
 
@@ -62,7 +63,7 @@ def feature_stat(x: pd.Series) -> pd.DataFrame:
         Examples
         --------
         >>> cts = pd.Series([13.32, 3.32, 4.3, 2.45, 6.34, 2.25,
-                            4.43, 3.26, np.NaN, None], name='continuous')
+                            4.43, 3.26, np.nan, None], name='continuous')
         >>> cts.ads.feature_type = ['continuous']
         >>> cts.ads.feature_stat()
             Metric                  Value
@@ -99,7 +100,7 @@ def feature_plot(x: pd.Series) -> plt.Axes:
         Examples
         --------
         >>> cts = pd.Series([13.32, 3.32, 4.3, 2.45, 6.34, 2.25,
-                            4.43, 3.26, np.NaN, None], name='continuous')
+                            4.43, 3.26, np.nan, None], name='continuous')
         >>> cts.ads.feature_type = ['continuous']
         >>> cts.ads.feture_plot()
 
@@ -125,7 +126,7 @@ def feature_domain(cls, x: pd.Series) -> schema.Domain:
         Examples
         --------
         >>> cts = pd.Series([13.32, 3.32, 4.3, 2.45, 6.34, 2.25,
-                            4.43, 3.26, np.NaN, None], name='continuous')
+                            4.43, 3.26, np.nan, None], name='continuous')
         >>> cts.ads.feature_type = ['continuous']
         >>> cts.ads.feature_domain()
         constraints: []

ads/feature_engineering/feature_type/datetime.py

@@ -1,7 +1,6 @@
 #!/usr/bin/env python
-# -*- coding: utf-8 -*--
 
-# Copyright (c) 2021, 2022 Oracle and/or its affiliates.
+# Copyright (c) 2021, 2025 Oracle and/or its affiliates.
 # Licensed under the Universal Permissive License v 1.0 as shown at https://oss.oracle.com/licenses/upl/
 
 """
@@ -11,21 +10,19 @@
     DateTime
         The DateTime feature type.
 """
+
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
 import pandas.api.types as pdtypes
-from ads.feature_engineering.feature_type.base import FeatureType
-from ads.feature_engineering.utils import (
-    _add_missing,
-    _set_seaborn_theme,
-    SchemeTeal,
-)
-from ads.feature_engineering import schema
+
 from ads.common.decorator.runtime_dependency import (
-    runtime_dependency,
     OptionalDependency,
+    runtime_dependency,
 )
+from ads.feature_engineering import schema
+from ads.feature_engineering.feature_type.base import FeatureType
+from ads.feature_engineering.utils import SchemeTeal, _add_missing, _set_seaborn_theme
 
 
 def default_handler(data: pd.Series, *args, **kwargs) -> pd.Series:
@@ -123,12 +120,12 @@ def feature_stat(x: pd.Series) -> pd.DataFrame:
         df_stat = pd.Series(
             {
                 "count": len(x),
-                "sample maximum": x.replace(r"", np.NaN).dropna().max(),
-                "sample minimum": x.replace(r"", np.NaN).dropna().min(),
+                "sample maximum": x.replace(r"", np.nan).dropna().max(),
+                "sample minimum": x.replace(r"", np.nan).dropna().min(),
             },
             name=x.name,
         ).to_frame()
-        return _add_missing(x.replace(r"", np.NaN), df_stat)
+        return _add_missing(x.replace(r"", np.nan), df_stat)
 
     @staticmethod
     @runtime_dependency(module="seaborn", install_from=OptionalDependency.VIZ)

ads/feature_engineering/feature_type/gis.py

@@ -1,7 +1,6 @@
 #!/usr/bin/env python
-# -*- coding: utf-8 -*--
 
-# Copyright (c) 2021, 2022 Oracle and/or its affiliates.
+# Copyright (c) 2021, 2025 Oracle and/or its affiliates.
 # Licensed under the Universal Permissive License v 1.0 as shown at https://oss.oracle.com/licenses/upl/
 
 """
@@ -11,20 +10,23 @@
     GIS
         The GIS feature type.
 """
+
+import re
+
 import matplotlib.pyplot as plt
 import pandas as pd
-import re
+
+from ads.common.decorator.runtime_dependency import (
+    OptionalDependency,
+    runtime_dependency,
+)
+from ads.feature_engineering import schema
 from ads.feature_engineering.feature_type.base import FeatureType
 from ads.feature_engineering.utils import (
-    _count_unique_missing,
-    _str_lat_long_to_point,
     SchemeNeutral,
     SchemeTeal,
-)
-from ads.feature_engineering import schema
-from ads.common.decorator.runtime_dependency import (
-    runtime_dependency,
-    OptionalDependency,
+    _count_unique_missing,
+    _str_lat_long_to_point,
 )
 
 PATTERN = re.compile(r"^[(]?(\-?\d+\.\d+?),\s*(\-?\d+\.\d+?)[)]?$", re.VERBOSE)
@@ -126,7 +128,7 @@ def feature_stat(x: pd.Series) -> pd.DataFrame:
             "-44.510428,-169.269477",
             "-56.3344375,-166.407038",
             "",
-            np.NaN,
+            np.nan,
             None
             ],
             name='gis'
@@ -165,7 +167,7 @@ def feature_plot(x: pd.Series) -> plt.Axes:
             "-44.510428,-169.269477",
             "-56.3344375,-166.407038",
             "",
-            np.NaN,
+            np.nan,
             None
             ],
             name='gis'
@@ -221,7 +223,7 @@ def feature_domain(cls, x: pd.Series) -> schema.Domain:
             "-44.510428,-169.269477",
             "-56.3344375,-166.407038",
             "",
-            np.NaN,
+            np.nan,
             None
             ],
             name='gis'

ads/feature_engineering/feature_type/integer.py

@@ -1,7 +1,6 @@
 #!/usr/bin/env python
-# -*- coding: utf-8 -*--
 
-# Copyright (c) 2021, 2022 Oracle and/or its affiliates.
+# Copyright (c) 2021, 2025 Oracle and/or its affiliates.
 # Licensed under the Universal Permissive License v 1.0 as shown at https://oss.oracle.com/licenses/upl/
 
 """
@@ -11,19 +10,21 @@
     Integer
         The Integer feature type.
 """
+
 import matplotlib.pyplot as plt
 import pandas as pd
+
+from ads.common.decorator.runtime_dependency import (
+    OptionalDependency,
+    runtime_dependency,
+)
+from ads.feature_engineering import schema
 from ads.feature_engineering.feature_type.base import FeatureType
 from ads.feature_engineering.utils import (
-    _add_missing,
-    _set_seaborn_theme,
     SchemeTeal,
+    _add_missing,
     _format_stat,
-)
-from ads.feature_engineering import schema
-from ads.common.decorator.runtime_dependency import (
-    runtime_dependency,
-    OptionalDependency,
+    _set_seaborn_theme,
 )
 
 
@@ -120,7 +121,7 @@ def feature_domain(cls, x: pd.Series) -> schema.Domain:
 
         Examples
         --------
-        >>> s = pd.Series([True, False, True, False, np.NaN, None], name='integer')
+        >>> s = pd.Series([True, False, True, False, np.nan, None], name='integer')
         >>> s.ads.feature_type = ['integer']
         >>> s.ads.feature_domain()
         constraints: []