diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index e741fa7b37f33..8ba9926c054ba 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -7505,8 +7505,8 @@ def nlargest(
 
             - ``first`` : prioritize the first occurrence(s)
             - ``last`` : prioritize the last occurrence(s)
-            - ``all`` : do not drop any duplicates, even it means
-              selecting more than `n` items.
+            - ``all`` : keep all the ties of the smallest item even if it means
+              selecting more than ``n`` items.
 
         Returns
         -------
@@ -7568,7 +7568,9 @@ def nlargest(
         Italy     59000000  1937894      IT
         Brunei      434000    12128      BN
 
-        When using ``keep='all'``, all duplicate items are maintained:
+        When using ``keep='all'``, the number of element kept can go beyond ``n``
+        if there are duplicate values for the smallest element, all the
+        ties are kept:
 
         >>> df.nlargest(3, 'population', keep='all')
                   population      GDP alpha-2
@@ -7578,6 +7580,16 @@ def nlargest(
         Maldives      434000     4520      MV
         Brunei        434000    12128      BN
 
+        However, ``nlargest`` does not keep ``n`` distinct largest elements:
+
+        >>> df.nlargest(5, 'population', keep='all')
+                  population      GDP alpha-2
+        France      65000000  2583560      FR
+        Italy       59000000  1937894      IT
+        Malta         434000    12011      MT
+        Maldives      434000     4520      MV
+        Brunei        434000    12128      BN
+
         To order by the largest values in column "population" and then "GDP",
         we can specify multiple columns like in the next example.
 
@@ -7614,8 +7626,8 @@ def nsmallest(
 
             - ``first`` : take the first occurrence.
             - ``last`` : take the last occurrence.
-            - ``all`` : do not drop any duplicates, even it means
-              selecting more than `n` items.
+            - ``all`` : keep all the ties of the largest item even if it means
+              selecting more than ``n`` items.
 
         Returns
         -------
@@ -7669,7 +7681,9 @@ def nsmallest(
         Tuvalu         11300   38      TV
         Nauru         337000  182      NR
 
-        When using ``keep='all'``, all duplicate items are maintained:
+        When using ``keep='all'``, the number of element kept can go beyond ``n``
+        if there are duplicate values for the largest element, all the
+        ties are kept.
 
         >>> df.nsmallest(3, 'population', keep='all')
                   population    GDP alpha-2
@@ -7678,6 +7692,16 @@ def nsmallest(
         Iceland       337000  17036      IS
         Nauru         337000    182      NR
 
+        However, ``nsmallest`` does not keep ``n`` distinct
+        smallest elements:
+
+        >>> df.nsmallest(4, 'population', keep='all')
+                  population    GDP alpha-2
+        Tuvalu         11300     38      TV
+        Anguilla       11300    311      AI
+        Iceland       337000  17036      IS
+        Nauru         337000    182      NR
+
         To order by the smallest values in column "population" and then "GDP", we can
         specify multiple columns like in the next example.