DOC: Fixing EX01 - Added examples (#54288)

* Examples ExtensionArray._from_sequence_of_strings ...

* Moved axis to new line

Author: DeaMariaLeon

ci/code_checks.sh

@@ -63,9 +63,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
 
     MSG='Partially validate docstrings (EX01)' ;  echo $MSG
     $BASE_DIR/scripts/validate_docstrings.py --format=actions --errors=EX01 --ignore_functions \
-        pandas.errors.PyperclipException \
         pandas.errors.PyperclipWindowsException \
-        pandas.errors.UnsortedIndexError \
         pandas.errors.UnsupportedFunctionCall \
         pandas.NaT \
         pandas.io.stata.StataReader.data_label \
@@ -77,11 +75,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         pandas.api.extensions.ExtensionDtype \
         pandas.api.extensions.ExtensionArray \
         pandas.arrays.NumpyExtensionArray \
-        pandas.api.extensions.ExtensionArray._from_sequence_of_strings \
-        pandas.api.extensions.ExtensionArray._hash_pandas_object \
-        pandas.api.extensions.ExtensionArray._reduce \
-        pandas.api.extensions.ExtensionArray._values_for_factorize \
-        pandas.api.extensions.ExtensionArray.interpolate \
     RET=$(($RET + $?)) ; echo $MSG "DONE"
 
 fi

pandas/core/arrays/base.py

@@ -301,6 +301,13 @@ def _from_sequence_of_strings(
         Returns
         -------
         ExtensionArray
+
+        Examples
+        --------
+        >>> pd.arrays.IntegerArray._from_sequence_of_strings(["1", "2", "3"])
+        <IntegerArray>
+        [1, 2, 3]
+        Length: 3, dtype: Int64
         """
         raise AbstractMethodError(cls)
 
@@ -878,6 +885,22 @@ def interpolate(
     ) -> Self:
         """
         See DataFrame.interpolate.__doc__.
+
+        Examples
+        --------
+        >>> arr = pd.arrays.NumpyExtensionArray(np.array([0, 1, np.nan, 3]))
+        >>> arr.interpolate(method="linear",
+        ...                 limit=3,
+        ...                 limit_direction="forward",
+        ...                 index=pd.Index([1, 2, 3, 4]),
+        ...                 fill_value=1,
+        ...                 copy=False,
+        ...                 axis=0,
+        ...                 limit_area="inside"
+        ...                 )
+        <NumpyExtensionArray>
+        [0.0, 1.0, 2.0, 3.0]
+        Length: 4, dtype: float64
         """
         # NB: we return type(self) even if copy=False
         raise NotImplementedError(
@@ -1212,6 +1235,11 @@ def _values_for_factorize(self) -> tuple[np.ndarray, Any]:
         The values returned by this method are also used in
         :func:`pandas.util.hash_pandas_object`. If needed, this can be
         overridden in the ``self._hash_pandas_object()`` method.
+
+        Examples
+        --------
+        >>> pd.array([1, 2, 3])._values_for_factorize()
+        (array([1, 2, 3], dtype=object), nan)
         """
         return self.astype(object), np.nan
 
@@ -1714,6 +1742,11 @@ def _reduce(
         Raises
         ------
         TypeError : subclass does not define reductions
+
+        Examples
+        --------
+        >>> pd.array([1, 2, 3])._reduce("min")
+        1
         """
         meth = getattr(self, name, None)
         if meth is None:
@@ -1760,12 +1793,24 @@ def _hash_pandas_object(
         Parameters
         ----------
         encoding : str
+            Encoding for data & key when strings.
         hash_key : str
+            Hash_key for string key to encode.
         categorize : bool
+            Whether to first categorize object arrays before hashing. This is more
+            efficient when the array contains duplicate values.
 
         Returns
         -------
         np.ndarray[uint64]
+
+        Examples
+        --------
+        >>> pd.array([1, 2])._hash_pandas_object(encoding='utf-8',
+        ...                                      hash_key="1000000000000000",
+        ...                                      categorize=False
+        ...                                      )
+        array([11381023671546835630,  4641644667904626417], dtype=uint64)
         """
         from pandas.core.util.hashing import hash_array
 

pandas/errors/__init__.py

@@ -82,6 +82,25 @@ class UnsortedIndexError(KeyError):
     Error raised when slicing a MultiIndex which has not been lexsorted.
 
     Subclass of `KeyError`.
+
+    Examples
+    --------
+    >>> df = pd.DataFrame({"cat": [0, 0, 1, 1],
+    ...                    "color": ["white", "white", "brown", "black"],
+    ...                    "lives": [4, 4, 3, 7]},
+    ...                   )
+    >>> df = df.set_index(["cat", "color"])
+    >>> df
+                lives
+    cat  color
+    0    white    4
+         white    4
+    1    brown    3
+         black    7
+    >>> df.loc[(0, "black"):(1, "white")]
+    Traceback (most recent call last):
+    UnsortedIndexError: 'Key length (2) was greater
+    than MultiIndex lexsort depth (1)'
     """
 
 

scripts/validate_docstrings.py

@@ -53,6 +53,7 @@
     "errors.LossySetitemError",
     "errors.NoBufferPresent",
     "errors.IncompatibilityWarning",
+    "errors.PyperclipException",
 }
 PRIVATE_CLASSES = ["NDFrame", "IndexOpsMixin"]
 ERROR_MSGS = {