DOC: Fixing EX01 - Added examples (#53336)

* Examples

* Changed Index.copy

* Corrected Float32Dtype & Float64Dtype

Author: DeaMariaLeon

ci/code_checks.sh

@@ -170,8 +170,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         pandas.Period.asfreq \
         pandas.Period.now \
         pandas.arrays.PeriodArray \
-        pandas.arrays.IntervalArray.from_arrays \
-        pandas.arrays.IntervalArray.to_tuples \
         pandas.Int8Dtype \
         pandas.Int16Dtype \
         pandas.Int32Dtype \
@@ -181,8 +179,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         pandas.UInt32Dtype \
         pandas.UInt64Dtype \
         pandas.NA \
-        pandas.Float32Dtype \
-        pandas.Float64Dtype \
         pandas.CategoricalDtype.categories \
         pandas.CategoricalDtype.ordered \
         pandas.Categorical.dtype \
@@ -258,9 +254,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         pandas.util.hash_pandas_object \
         pandas_object \
         pandas.api.interchange.from_dataframe \
-        pandas.Index.T \
-        pandas.Index.memory_usage \
-        pandas.Index.copy \
         pandas.Index.drop \
         pandas.Index.identical \
         pandas.Index.insert \

pandas/core/arrays/floating.py

@@ -134,6 +134,20 @@ class FloatingArray(NumericArray):
 Methods
 -------
 None
+
+Examples
+--------
+For Float32Dtype:
+
+>>> ser = pd.Series([2.25, pd.NA], dtype=pd.Float32Dtype())
+>>> ser.dtype
+Float32Dtype()
+
+For Float64Dtype:
+
+>>> ser = pd.Series([2.25, pd.NA], dtype=pd.Float64Dtype())
+>>> ser.dtype
+Float64Dtype()
 """
 
 # create the Dtype

pandas/core/arrays/interval.py

@@ -509,6 +509,8 @@ def from_breaks(
             "name": "",
             "examples": textwrap.dedent(
                 """\
+        Examples
+        --------
         >>> pd.arrays.IntervalArray.from_arrays([0, 1, 2], [1, 2, 3])
         <IntervalArray>
         [(0, 1], (1, 2], (2, 3]]
@@ -1635,9 +1637,8 @@ def __arrow_array__(self, type=None):
 
         return pyarrow.ExtensionArray.from_storage(interval_type, storage_array)
 
-    _interval_shared_docs[
-        "to_tuples"
-    ] = """
+    _interval_shared_docs["to_tuples"] = textwrap.dedent(
+        """
         Return an %(return_type)s of tuples of the form (left, right).
 
         Parameters
@@ -1651,9 +1652,27 @@ def __arrow_array__(self, type=None):
         tuples: %(return_type)s
         %(examples)s\
         """
+    )
 
     @Appender(
-        _interval_shared_docs["to_tuples"] % {"return_type": "ndarray", "examples": ""}
+        _interval_shared_docs["to_tuples"]
+        % {
+            "return_type": "ndarray",
+            "examples": textwrap.dedent(
+                """\
+
+         Examples
+         --------
+         >>> idx = pd.arrays.IntervalArray.from_tuples([(0, 1), (1, 2)])
+         >>> idx
+         <IntervalArray>
+         [(0, 1], (1, 2]]
+         Length: 2, dtype: interval[int64, right]
+         >>> idx.to_tuples()
+         array([(0, 1), (1, 2)], dtype=object)
+         """
+            ),
+        }
     )
     def to_tuples(self, na_tuple: bool = True) -> np.ndarray:
         tuples = com.asarray_tuplesafe(zip(self._left, self._right))

pandas/core/base.py

@@ -300,6 +300,8 @@ def transpose(self, *args, **kwargs) -> Self:
 
         Examples
         --------
+        For Series:
+
         >>> s = pd.Series(['Ant', 'Bear', 'Cow'])
         >>> s
         0     Ant
@@ -311,6 +313,12 @@ def transpose(self, *args, **kwargs) -> Self:
         1    Bear
         2     Cow
         dtype: object
+
+        For Index:
+
+        >>> idx = pd.Index([1, 2, 3])
+        >>> idx.T
+        Index([1, 2, 3], dtype='int64')
         """,
     )
 
@@ -1088,6 +1096,12 @@ def _memory_usage(self, deep: bool = False) -> int:
         -----
         Memory usage does not include memory consumed by elements that
         are not components of the array if deep=False or if used on PyPy
+
+        Examples
+        --------
+        >>> idx = pd.Index([1, 2, 3])
+        >>> idx.memory_usage()
+        24
         """
         if hasattr(self.array, "memory_usage"):
             return self.array.memory_usage(  # pyright: ignore[reportGeneralTypeIssues]

pandas/core/indexes/base.py

@@ -1221,6 +1221,13 @@ def copy(
         -----
         In most cases, there should be no functional difference from using
         ``deep``, but if ``deep`` is passed it will attempt to deepcopy.
+
+        Examples
+        --------
+        >>> idx = pd.Index(['a', 'b', 'c'])
+        >>> new_idx = idx.copy()
+        >>> idx is new_idx
+        False
         """
 
         name = self._validate_names(name=name, deep=deep)[0]