DOC: Fixing EX01 - Added examples

ci/code_checks.sh

@@ -117,7 +117,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         pandas.errors.DataError \
         pandas.errors.IncompatibilityWarning \
         pandas.errors.InvalidComparison \
-        pandas.errors.InvalidVersion \
         pandas.errors.IntCastingNaNError \
         pandas.errors.LossySetitemError \
         pandas.errors.MergeError \
@@ -165,7 +164,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         pandas.Period.asfreq \
         pandas.Period.now \
         pandas.arrays.PeriodArray \
-        pandas.NA \
         pandas.CategoricalDtype.categories \
         pandas.CategoricalDtype.ordered \
         pandas.Categorical.dtype \
@@ -241,13 +239,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         pandas.util.hash_pandas_object \
         pandas_object \
         pandas.api.interchange.from_dataframe \
-        pandas.Index.fillna \
-        pandas.Index.dropna \
-        pandas.Index.astype \
-        pandas.Index.map \
-        pandas.Index.to_list \
-        pandas.Index.append \
-        pandas.Index.join \
         pandas.Index.asof_locs \
         pandas.Index.get_slice_bound \
         pandas.RangeIndex \

pandas/_libs/missing.pyx

@@ -377,6 +377,26 @@ class NAType(C_NAType):
 
     The NA singleton is a missing value indicator defined by pandas. It is
     used in certain new extension dtypes (currently the "string" dtype).
+
+    Examples
+    --------
+    >>> pd.NA
+    <NA>
+
+    >>> True | pd.NA
+    True
+
+    >>> True & pd.NA
+    <NA>
+
+    >>> pd.NA != pd.NA
+    <NA>
+
+    >>> pd.NA == pd.NA
+    <NA>
+
+    >>> True | pd.NA
+    True
     """
 
     _instance = None

pandas/core/base.py

@@ -765,9 +765,20 @@ def tolist(self):
 
         Examples
         --------
+        For Series
+
         >>> s = pd.Series([1, 2, 3])
         >>> s.to_list()
         [1, 2, 3]
+
+        For Index:
+
+        >>> idx = pd.Index([1, 2, 3])
+        >>> idx
+        Index([1, 2, 3], dtype='int64')
+
+        >>> idx.to_list()
+        [1, 2, 3]
         """
         return self._values.tolist()
 

pandas/core/indexes/base.py

@@ -1056,6 +1056,14 @@ def astype(self, dtype, copy: bool = True):
         -------
         Index
             Index with values cast to specified dtype.
+
+        Examples
+        --------
+        >>> idx = pd.Index([1, 2, 3])
+        >>> idx
+        Index([1, 2, 3], dtype='int64')
+        >>> idx.astype('float')
+        Index([1.0, 2.0, 3.0], dtype='float64')
         """
         if dtype is not None:
             dtype = pandas_dtype(dtype)
@@ -2939,6 +2947,12 @@ def fillna(self, value=None, downcast=None):
         --------
         DataFrame.fillna : Fill NaN values of a DataFrame.
         Series.fillna : Fill NaN Values of a Series.
+
+        Examples
+        --------
+        >>> idx = pd.Index([np.nan, np.nan, 3])
+        >>> idx.fillna(0)
+        Index([0.0, 0.0, 3.0], dtype='float64')
         """
         if not is_scalar(value):
             raise TypeError(f"'value' must be a scalar, passed: {type(value).__name__}")
@@ -2969,6 +2983,12 @@ def dropna(self, how: AnyAll = "any") -> Self:
         Returns
         -------
         Index
+
+        Examples
+        --------
+        >>> idx = pd.Index([1, np.nan, 3])
+        >>> idx.dropna()
+        Index([1.0, 3.0], dtype='float64')
         """
         if how not in ("any", "all"):
             raise ValueError(f"invalid how option: {how}")
@@ -4535,6 +4555,13 @@ def join(
         Returns
         -------
         join_index, (left_indexer, right_indexer)
+
+         Examples
+        --------
+        >>> idx1 = pd.Index([1, 2, 3])
+        >>> idx2 = pd.Index([4, 5, 6])
+        >>> idx1.join(idx2, how='outer')
+        Index([1, 2, 3, 4, 5, 6], dtype='int64')
         """
         other = ensure_index(other)
 
@@ -5359,6 +5386,12 @@ def append(self, other: Index | Sequence[Index]) -> Index:
         Returns
         -------
         Index
+
+        Examples
+        --------
+        >>> idx = pd.Index([1, 2, 3])
+        >>> idx.append(pd.Index([4]))
+        Index([1, 2, 3, 4], dtype='int64')
         """
         to_concat = [self]
 
@@ -6295,6 +6328,22 @@ def map(self, mapper, na_action: Literal["ignore"] | None = None):
             The output of the mapping function applied to the index.
             If the function returns a tuple with more than one element
             a MultiIndex will be returned.
+
+        Examples
+        --------
+        >>> idx = pd.Index([1, 2, 3])
+        >>> idx.map({1: 'a', 2: 'b', 3: 'c'})
+        Index(['a', 'b', 'c'], dtype='object')
+
+        Using `map` with a function:
+
+        >>> idx = pd.Index([1, 2, 3])
+        >>> idx.map('I am a {}'.format)
+        Index(['I am a 1', 'I am a 2', 'I am a 3'], dtype='object')
+
+        >>> idx = pd.Index(['a', 'b', 'c'])
+        >>> idx.map(lambda x: x.upper())
+        Index(['A', 'B', 'C'], dtype='object')
         """
         from pandas.core.indexes.multi import MultiIndex
 

pandas/util/version/__init__.py

@@ -129,6 +129,12 @@ def parse(version: str) -> LegacyVersion | Version:
 class InvalidVersion(ValueError):
     """
     An invalid version was found, users should refer to PEP 440.
+
+    Examples
+    --------
+    >>> pd.util.version.Version('1.')
+    Traceback (most recent call last):
+    InvalidVersion: Invalid version: '1.'
     """