From f8c0b61f93b27e4d3d22156dcdad0edfb77698b5 Mon Sep 17 00:00:00 2001
From: iofall <50991099+iofall@users.noreply.github.com>
Date: Wed, 29 Sep 2021 16:52:16 +0530
Subject: [PATCH] Lesson 12 fix grammar and completeness

---
 .../12-visualization-relationships/README.md                | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/3-Data-Visualization/12-visualization-relationships/README.md b/3-Data-Visualization/12-visualization-relationships/README.md
index 99be92b..0f4d2d1 100644
--- a/3-Data-Visualization/12-visualization-relationships/README.md
+++ b/3-Data-Visualization/12-visualization-relationships/README.md
@@ -6,13 +6,13 @@
 
 Continuing with the nature focus of our research, let's discover interesting visualizations to show the relationships between various types of honey, according to a dataset derived from the [United States Department of Agriculture](https://www.nass.usda.gov/About_NASS/index.php). 
 
-This dataset of about 600 items displays honey production in many U.S. states. So, for example, you can look at the number of colonies, yield per colony, total production, stocks, price per pound, and value of the honey produced in a given state from 1998-2012, with one row per year for each state. 
+This dataset of about 600 items, displays honey production in many U.S. states. So, for example, you can look at the number of colonies, yield per colony, total production, stocks, price per pound, and value of the honey produced in a given state from 1998-2012, with one row per year for each state. 
 
 It will be interesting to visualize the relationship between a given state's production per year and, for example, the price of honey in that state. Alternately, you could visualize the relationship between states' honey yield per colony. This year span covers the devastating 'CCD' or 'Colony Collapse Disorder' first seen in 2006 (http://npic.orst.edu/envir/ccd.html), so it is a poignant dataset to study. 🐝
 
 ## [Pre-lecture quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/22)
 
-In this lesson, you can use Seaborn, which you use before, as a good library to visualize relationships between variables. Particularly interesting is the use of Seaborn's `relplot` function that allows scatter plots and line plots to quickly visualize '[statistical relationships](https://seaborn.pydata.org/tutorial/relational.html?highlight=relationships)', which allow the data scientist to better understand how variables relate to each other.
+In this lesson, you can use Seaborn, which you have used before, as a good library to visualize relationships between variables. Particularly interesting is the use of Seaborn's `relplot` function that allows scatter plots and line plots to quickly visualize '[statistical relationships](https://seaborn.pydata.org/tutorial/relational.html?highlight=relationships)', which allow the data scientist to better understand how variables relate to each other.
 
 ## Scatterplots
 
@@ -156,7 +156,7 @@ ax.figure.legend();
 ```
 ![superimposed plots](images/dual-line.png)
 
-While nothing jumps out to the eye around the year 2003, it does allow us to end this lesson on a little happier note: while there are overall a declining number of colonies, their numbers might seem to be stabilizing and their yield per colony is actually increasing, even with fewer bees. 
+While nothing jumps out to the eye around the year 2003, it does allow us to end this lesson on a little happier note: while there are overall a declining number of colonies, their numbers might seem to be stabilizing. 
 
 Go, bees, go!