From fd60ad0f672eb1ad1354db0c0dd14c67e644919e Mon Sep 17 00:00:00 2001
From: Eric Brassell <31701272+ebrassell@users.noreply.github.com>
Date: Fri, 22 Nov 2019 21:44:45 -0500
Subject: [PATCH 1/3] Correct misuse of high-cardinality

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

diff --git a/doc/source/user_guide/scale.rst b/doc/source/user_guide/scale.rst
index 7b590a3a1fcc8..a1d414708a271 100644
--- a/doc/source/user_guide/scale.rst
+++ b/doc/source/user_guide/scale.rst
@@ -93,7 +93,7 @@ Use efficient datatypes
 -----------------------
 
 The default pandas data types are not the most memory efficient. This is
-especially true for high-cardinality text data (columns with relatively few
+especially true for low-cardinality text data (columns with relatively few
 unique values). By using more efficient data types you can store larger datasets
 in memory.
 

From a50fa3e72630fd459ecf8cd063ece48a17fe7f9d Mon Sep 17 00:00:00 2001
From: Eric Brassell <31701272+ebrassell@users.noreply.github.com>
Date: Sat, 23 Nov 2019 06:24:14 -0500
Subject: [PATCH 2/3] Incorporate feedback on phrasing.

---
 doc/source/user_guide/scale.rst | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/doc/source/user_guide/scale.rst b/doc/source/user_guide/scale.rst
index a1d414708a271..c030af4bdc913 100644
--- a/doc/source/user_guide/scale.rst
+++ b/doc/source/user_guide/scale.rst
@@ -93,9 +93,9 @@ Use efficient datatypes
 -----------------------
 
 The default pandas data types are not the most memory efficient. This is
-especially true for low-cardinality text data (columns with relatively few
-unique values). By using more efficient data types you can store larger datasets
-in memory.
+especially true for text data columns with relatively few unique values (commonly 
+referred to as "low-cardinality" data). By using more efficient data types you
+can store larger datasets in memory.
 
 .. ipython:: python
 

From 2ed159032638b2c3c9a6460d9aa9db1d5a499db3 Mon Sep 17 00:00:00 2001
From: Eric Brassell <31701272+ebrassell@users.noreply.github.com>
Date: Sat, 23 Nov 2019 16:55:57 -0500
Subject: [PATCH 3/3] Remove trailing whitespace.

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

diff --git a/doc/source/user_guide/scale.rst b/doc/source/user_guide/scale.rst
index c030af4bdc913..cff782678a4b3 100644
--- a/doc/source/user_guide/scale.rst
+++ b/doc/source/user_guide/scale.rst
@@ -93,7 +93,7 @@ Use efficient datatypes
 -----------------------
 
 The default pandas data types are not the most memory efficient. This is
-especially true for text data columns with relatively few unique values (commonly 
+especially true for text data columns with relatively few unique values (commonly
 referred to as "low-cardinality" data). By using more efficient data types you
 can store larger datasets in memory.