From a84bcb149cc499e74b02eff0134c8744bbf92aba Mon Sep 17 00:00:00 2001
From: Joris Van den Bossche <jorisvandenbossche@gmail.com>
Date: Wed, 15 Aug 2018 15:47:01 +0200
Subject: [PATCH] DOC: edit docstring example to prevent segfault (#21824)

---
 pandas/core/frame.py | 10 ++++++----
 1 file changed, 6 insertions(+), 4 deletions(-)

diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index b35bc8325d560..78ad9728800d6 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -6896,21 +6896,21 @@ def count(self, axis=0, level=None, numeric_only=False):
         Constructing DataFrame from a dictionary:
 
         >>> df = pd.DataFrame({"Person":
-        ...                    ["John", "Myla", None, "John", "Myla"],
+        ...                    ["John", "Myla", "Lewis", "John", "Myla"],
         ...                    "Age": [24., np.nan, 21., 33, 26],
         ...                    "Single": [False, True, True, True, False]})
         >>> df
            Person   Age  Single
         0    John  24.0   False
         1    Myla   NaN    True
-        2    None  21.0    True
+        2   Lewis  21.0    True
         3    John  33.0    True
         4    Myla  26.0   False
 
         Notice the uncounted NA values:
 
         >>> df.count()
-        Person    4
+        Person    5
         Age       4
         Single    5
         dtype: int64
@@ -6920,7 +6920,7 @@ def count(self, axis=0, level=None, numeric_only=False):
         >>> df.count(axis='columns')
         0    3
         1    2
-        2    2
+        2    3
         3    3
         4    3
         dtype: int64
@@ -6931,7 +6931,9 @@ def count(self, axis=0, level=None, numeric_only=False):
                 Age
         Person
         John      2
+        Lewis     1
         Myla      1
+
         """
         axis = self._get_axis_number(axis)
         if level is not None: