update to newer version of pandas and associated code changes

Author: bing-speech-trial

requirements.txt

@@ -1,5 +1,5 @@
-numpy>=1.20.3  # For compatibility with recent versions of Pandas
-pandas>=1.0.3
+numpy>=1.23.5  # For compatibility with recent versions of Pandas
+pandas>=2.2.3
 pyarrow>=1.0.0
 regex
 # TODO: The following dependency is to support compatibility with Python 3.6, and should be removed when that version's support is dropped

text_extensions_for_pandas/array/tensor.py

@@ -38,8 +38,8 @@
     from pandas.core.dtypes.generic import ABCIndexClass as ABCIndex
 from pandas.core.indexers import check_array_indexer, validate_indices
 
-""" Begin Patching of ExtensionArrayFormatter """
-from pandas.io.formats.format import ExtensionArrayFormatter
+""" Begin Patching of _ExtensionArrayFormatter """
+from pandas.io.formats.format import _ExtensionArrayFormatter
 
 
 def _format_strings_patched(self) -> List[str]:
@@ -147,14 +147,14 @@ def _format(x):
 _FORMATTER_ENABLED_KEY = "TEXT_EXTENSIONS_FOR_PANDAS_FORMATTER_ENABLED"
 
 if os.getenv(_FORMATTER_ENABLED_KEY, "true").lower() == "true":
-    ExtensionArrayFormatter._format_strings_orig = \
-        ExtensionArrayFormatter._format_strings
+    _ExtensionArrayFormatter._format_strings_orig = \
+        _ExtensionArrayFormatter._format_strings
     if Version("1.1.0") <= Version(pd.__version__) < Version("1.3.0"):
-        ExtensionArrayFormatter._format_strings = _format_strings_patched
+        _ExtensionArrayFormatter._format_strings = _format_strings_patched
     else:
-        ExtensionArrayFormatter._format_strings = _format_strings_patched_v1_0_0
-    ExtensionArrayFormatter._patched_by_text_extensions_for_pandas = True
-""" End Patching of ExtensionArrayFormatter """
+        _ExtensionArrayFormatter._format_strings = _format_strings_patched_v1_0_0
+    _ExtensionArrayFormatter._patched_by_text_extensions_for_pandas = True
+""" End Patching of _ExtensionArrayFormatter """
 
 
 @pd.api.extensions.register_extension_dtype

text_extensions_for_pandas/array/test_tensor.py

@@ -703,9 +703,9 @@ def test_large_display_numeric(self):
     def test_numeric_display_3D(self):
 
         # Verify using patched method
-        from pandas.io.formats.format import ExtensionArrayFormatter
+        from pandas.io.formats.format import _ExtensionArrayFormatter
         self.assertTrue(
-            ExtensionArrayFormatter._patched_by_text_extensions_for_pandas)
+            _ExtensionArrayFormatter._patched_by_text_extensions_for_pandas)
 
         # Test integer format 3D values, uses IntArrayFormatter
         df = pd.DataFrame({"foo": TensorArray([[[1, 1], [2, 2]],
@@ -737,9 +737,9 @@ def test_large_display_string(self):
 
         # Verify using patched method
         # Unpatched method doesn't work for Pandas 1.0.x but fixed in later versions
-        from pandas.io.formats.format import ExtensionArrayFormatter
+        from pandas.io.formats.format import _ExtensionArrayFormatter
         self.assertTrue(
-            ExtensionArrayFormatter._patched_by_text_extensions_for_pandas)
+            _ExtensionArrayFormatter._patched_by_text_extensions_for_pandas)
 
         # Uses the GenericArrayFormatter
         df = pd.DataFrame({"foo": TensorArray(np.array([["Hello", "world"]] * 100))})
@@ -767,9 +767,9 @@ def test_large_display_string(self):
     def test_display_time(self):
 
         # Verify using patched method
-        from pandas.io.formats.format import ExtensionArrayFormatter
+        from pandas.io.formats.format import _ExtensionArrayFormatter
         self.assertTrue(
-            ExtensionArrayFormatter._patched_by_text_extensions_for_pandas)
+            _ExtensionArrayFormatter._patched_by_text_extensions_for_pandas)
 
         # datetime64 2D, Uses Datetime64Formatter
         times = pd.date_range('2018-01-01', periods=5, freq='H').to_numpy()

text_extensions_for_pandas/util.py

@@ -76,4 +76,4 @@ def to_int_array(arr: Any) -> np.ndarray:
     if isinstance(arr, np.ndarray) and np.issubdtype(arr.dtype, np.integer):
         return arr  # Avoid making a copy even if the input is an unusual integer dtype
     else:
-        return np.array(arr, dtype=np.int32, copy=False)
+        return np.asarray(arr, dtype=np.int32)