diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 68ea6795d47dd..6092368e2b944 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -9038,16 +9038,6 @@ def combine(
         0  0 -5.0
         1  0  4.0
 
-        However, if the same element in both dataframes is None, that None
-        is preserved
-
-        >>> df1 = pd.DataFrame({"A": [0, 0], "B": [None, 4]})
-        >>> df2 = pd.DataFrame({"A": [1, 1], "B": [None, 3]})
-        >>> df1.combine(df2, take_smaller, fill_value=-5)
-            A    B
-        0  0 -5.0
-        1  0  3.0
-
         Example that demonstrates the use of `overwrite` and behavior when
         the axis differ between the dataframes.
 
@@ -13820,8 +13810,8 @@ def quantile(
         0.1  1    1
         0.5  3  100
 
-        Specifying `numeric_only=False` will also compute the quantile of
-        datetime and timedelta data.
+        Specifying `numeric_only=False` will compute the quantiles for all
+        columns.
 
         >>> df = pd.DataFrame(
         ...     {
diff --git a/pandas/core/series.py b/pandas/core/series.py
index fe71a3ab91933..f2fc338c99c55 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -3112,8 +3112,8 @@ def combine(
 
         Combine the Series and `other` using `func` to perform elementwise
         selection for combined Series.
-        `fill_value` is assumed when value is missing at some index
-        from one of the two objects being combined.
+        `fill_value` is assumed when value is not present at some index
+        from one of the two Series being combined.
 
         Parameters
         ----------