From 703d547ccc4d33cc5553609bd0971637a0d5561c Mon Sep 17 00:00:00 2001
From: GYHHAHA <1801214626@qq.com>
Date: Sat, 25 Apr 2020 11:01:00 +0800
Subject: [PATCH 1/3] fix doc for crosstab with Categorical data input

---
 doc/source/user_guide/reshaping.rst | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/doc/source/user_guide/reshaping.rst b/doc/source/user_guide/reshaping.rst
index 7e890962d8da1..a987ee258d76d 100644
--- a/doc/source/user_guide/reshaping.rst
+++ b/doc/source/user_guide/reshaping.rst
@@ -472,14 +472,15 @@ If ``crosstab`` receives only two Series, it will provide a frequency table.
     pd.crosstab(df['A'], df['B'])
 
 Any input passed containing ``Categorical`` data will have **all** of its
-categories included in the cross-tabulation, even if the actual data does
-not contain any instances of a particular category.
+categories included in the cross-tabulation while setting ``dropna=False``, 
+even if the actual data does not contain any instances of a particular category.
 
 .. ipython:: python
 
     foo = pd.Categorical(['a', 'b'], categories=['a', 'b', 'c'])
     bar = pd.Categorical(['d', 'e'], categories=['d', 'e', 'f'])
     pd.crosstab(foo, bar)
+    pd.crosstab(foo, bar, dropna=False)
 
 Normalization
 ~~~~~~~~~~~~~

From 4d8611e815cf74ed527b8f5e384416811a1e3d8a Mon Sep 17 00:00:00 2001
From: GYHHAHA <1801214626@qq.com>
Date: Sun, 26 Apr 2020 10:52:28 +0800
Subject: [PATCH 2/3] fix doc for crosstab with Categorical data input

---
 doc/source/user_guide/reshaping.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/doc/source/user_guide/reshaping.rst b/doc/source/user_guide/reshaping.rst
index a987ee258d76d..28e3f3bd0aeca 100644
--- a/doc/source/user_guide/reshaping.rst
+++ b/doc/source/user_guide/reshaping.rst
@@ -472,7 +472,7 @@ If ``crosstab`` receives only two Series, it will provide a frequency table.
     pd.crosstab(df['A'], df['B'])
 
 Any input passed containing ``Categorical`` data will have **all** of its
-categories included in the cross-tabulation while setting ``dropna=False``, 
+categories included in the cross-tabulation while setting ``dropna=False``,
 even if the actual data does not contain any instances of a particular category.
 
 .. ipython:: python

From c905e18ce329b2cc89b8629643029707271e37f6 Mon Sep 17 00:00:00 2001
From: GYHHAHA <1801214626@qq.com>
Date: Mon, 27 Apr 2020 08:41:36 +0800
Subject: [PATCH 3/3] put dropna=False in a separate ipython block

---
 doc/source/user_guide/reshaping.rst | 13 ++++++++++---
 1 file changed, 10 insertions(+), 3 deletions(-)

diff --git a/doc/source/user_guide/reshaping.rst b/doc/source/user_guide/reshaping.rst
index 28e3f3bd0aeca..c476e33b8ddde 100644
--- a/doc/source/user_guide/reshaping.rst
+++ b/doc/source/user_guide/reshaping.rst
@@ -471,15 +471,22 @@ If ``crosstab`` receives only two Series, it will provide a frequency table.
 
     pd.crosstab(df['A'], df['B'])
 
-Any input passed containing ``Categorical`` data will have **all** of its
-categories included in the cross-tabulation while setting ``dropna=False``,
-even if the actual data does not contain any instances of a particular category.
+``crosstab`` can also be implemented
+to ``Categorical`` data.
 
 .. ipython:: python
 
     foo = pd.Categorical(['a', 'b'], categories=['a', 'b', 'c'])
     bar = pd.Categorical(['d', 'e'], categories=['d', 'e', 'f'])
     pd.crosstab(foo, bar)
+
+If you want to include **all** of data categories even if the actual data does
+not contain any instances of a particular category, you should set ``dropna=False``.
+
+For example:
+
+.. ipython:: python
+
     pd.crosstab(foo, bar, dropna=False)
 
 Normalization