diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 64bcde23ce34d..5ab1aae01910d 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -193,7 +193,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Series.list.flatten SA01" \
         -i "pandas.Series.list.len SA01" \
         -i "pandas.Series.lt PR07,SA01" \
-        -i "pandas.Series.mod PR07" \
         -i "pandas.Series.mode SA01" \
         -i "pandas.Series.ne PR07,SA01" \
         -i "pandas.Series.pad PR01,SA01" \
diff --git a/pandas/core/series.py b/pandas/core/series.py
index 5e7c9be083a0d..1ab9aa068fa25 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -6084,8 +6084,64 @@ def rfloordiv(self, other, level=None, fill_value=None, axis: Axis = 0) -> Serie
             other, roperator.rfloordiv, level=level, fill_value=fill_value, axis=axis
         )
 
-    @Appender(ops.make_flex_doc("mod", "series"))
     def mod(self, other, level=None, fill_value=None, axis: Axis = 0) -> Series:
+        """
+        Return Modulo of series and other, element-wise (binary operator `mod`).
+
+        Equivalent to ``series % other``, but with support to substitute a
+        fill_value for missing data in either one of the inputs.
+
+        Parameters
+        ----------
+        other : Series or scalar value
+            Series with which to compute modulo.
+        level : int or name
+            Broadcast across a level, matching Index values on the
+            passed MultiIndex level.
+        fill_value : None or float value, default None (NaN)
+            Fill existing missing (NaN) values, and any new element needed for
+            successful Series alignment, with this value before computation.
+            If data in both corresponding Series locations is missing
+            the result of filling (at that location) will be missing.
+        axis : {0 or 'index'}
+            Unused. Parameter needed for compatibility with DataFrame.
+
+        Returns
+        -------
+        Series
+            The result of the operation.
+
+        See Also
+        --------
+        Series.rmod : Reverse of the Modulo operator, see
+            `Python documentation
+            <https://docs.python.org/3/reference/datamodel.html#emulating-numeric-types>`_
+            for more details.
+
+        Examples
+        --------
+        >>> a = pd.Series([1, 1, 1, np.nan], index=["a", "b", "c", "d"])
+        >>> a
+        a    1.0
+        b    1.0
+        c    1.0
+        d    NaN
+        dtype: float64
+        >>> b = pd.Series([1, np.nan, 1, np.nan], index=["a", "b", "d", "e"])
+        >>> b
+        a    1.0
+        b    NaN
+        d    1.0
+        e    NaN
+        dtype: float64
+        >>> a.mod(b, fill_value=0)
+        a    0.0
+        b    NaN
+        c    NaN
+        d    0.0
+        e    NaN
+        dtype: float64
+        """
         return self._flex_method(
             other, operator.mod, level=level, fill_value=fill_value, axis=axis
         )