diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index e095d97146d03..4915997277006 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -81,20 +81,10 @@ 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.Series.backfill \
-        pandas.Series.ffill \
         pandas.Series.pad \
-        pandas.Series.str.center \
-        pandas.Series.str.decode \
-        pandas.Series.str.encode \
-        pandas.Series.str.find \
-        pandas.Series.str.fullmatch \
-        pandas.Series.str.index \
-        pandas.Series.str.ljust \
-        pandas.Series.str.match \
         pandas.Series.str.normalize \
         pandas.Series.str.rfind \
         pandas.Series.str.rindex \
-        pandas.Series.str.rjust \
         pandas.Series.str.translate \
         pandas.Series.sparse \
         pandas.DataFrame.sparse \
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 1adc331e3cd50..90a0444872ec7 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -7167,6 +7167,16 @@ def ffill(
         -------
         {klass} or None
             Object with missing values filled or None if ``inplace=True``.
+
+        Examples
+        --------
+        >>> ser = pd.Series([1, np.NaN, 2, 3])
+        >>> ser.ffill()
+        0   1.0
+        1   1.0
+        2   2.0
+        3   3.0
+        dtype: float64
         """
         return self.fillna(
             method="ffill", axis=axis, inplace=inplace, limit=limit, downcast=downcast
diff --git a/pandas/core/strings/accessor.py b/pandas/core/strings/accessor.py
index c8430b832f782..e8769370ca88d 100644
--- a/pandas/core/strings/accessor.py
+++ b/pandas/core/strings/accessor.py
@@ -1293,6 +1293,15 @@ def match(self, pat, case: bool = True, flags: int = 0, na=None):
         contains : Analogous, but less strict, relying on re.search instead of
             re.match.
         extract : Extract matched groups.
+
+        Examples
+        --------
+        >>> ser = pd.Series(["horse", "eagle", "donkey"])
+        >>> ser.str.match("e")
+        0   False
+        1   True
+        2   False
+        dtype: bool
         """
         result = self._data.array._str_match(pat, case=case, flags=flags, na=na)
         return self._wrap_result(result, fill_value=na, returns_string=False)
@@ -1324,6 +1333,15 @@ def fullmatch(self, pat, case: bool = True, flags: int = 0, na=None):
         match : Similar, but also returns `True` when only a *prefix* of the string
             matches the regular expression.
         extract : Extract matched groups.
+
+        Examples
+        --------
+        >>> ser = pd.Series(["cat", "duck", "dove"])
+        >>> ser.str.fullmatch(r'd.+')
+        0   False
+        1    True
+        2    True
+        dtype: bool
         """
         result = self._data.array._str_fullmatch(pat, case=case, flags=flags, na=na)
         return self._wrap_result(result, fill_value=na, returns_string=False)
@@ -1616,6 +1634,35 @@ def pad(
     Returns
     -------
     Series/Index of objects.
+
+    Examples
+    --------
+    For Series.str.center:
+
+    >>> ser = pd.Series(['dog', 'bird', 'mouse'])
+    >>> ser.str.center(8, fillchar='.')
+    0   ..dog...
+    1   ..bird..
+    2   .mouse..
+    dtype: object
+
+    For Series.str.ljust:
+
+    >>> ser = pd.Series(['dog', 'bird', 'mouse'])
+    >>> ser.str.ljust(8, fillchar='.')
+    0   dog.....
+    1   bird....
+    2   mouse...
+    dtype: object
+
+    For Series.str.rjust:
+
+    >>> ser = pd.Series(['dog', 'bird', 'mouse'])
+    >>> ser.str.rjust(8, fillchar='.')
+    0   .....dog
+    1   ....bird
+    2   ...mouse
+    dtype: object
     """
 
     @Appender(_shared_docs["str_pad"] % {"side": "left and right", "method": "center"})
@@ -1867,6 +1914,17 @@ def decode(self, encoding, errors: str = "strict"):
         Returns
         -------
         Series or Index
+
+        Examples
+        --------
+        For Series:
+
+        >>> ser = pd.Series([b'cow', b'123', b'()'])
+        >>> ser.str.decode('ascii')
+        0   cow
+        1   123
+        2   ()
+        dtype: object
         """
         # TODO: Add a similar _bytes interface.
         if encoding in _cpython_optimized_decoders:
@@ -1895,6 +1953,15 @@ def encode(self, encoding, errors: str = "strict"):
         Returns
         -------
         Series/Index of objects
+
+        Examples
+        --------
+        >>> ser = pd.Series(['cow', '123', '()'])
+        >>> ser.str.encode(encoding='ascii')
+        0     b'cow'
+        1     b'123'
+        2      b'()'
+        dtype: object
         """
         result = self._data.array._str_encode(encoding, errors)
         return self._wrap_result(result, returns_string=False)
@@ -2730,6 +2797,15 @@ def extractall(self, pat, flags: int = 0) -> DataFrame:
     See Also
     --------
     %(also)s
+
+    Examples
+    --------
+    >>> ser = pd.Series(["cow_", "duck_", "do_ve"])
+    >>> ser.str.find("_")
+    0   3
+    1   4
+    2   2
+    dtype: int64
     """
 
     @Appender(
@@ -2813,6 +2889,15 @@ def normalize(self, form):
     See Also
     --------
     %(also)s
+
+    Examples
+    --------
+    >>> ser = pd.Series(["horse", "eagle", "donkey"])
+    >>> ser.str.index("e")
+    0   4
+    1   0
+    2   4
+    dtype: int64
     """
 
     @Appender(