From 5c2de525e26844a7a9b41e769fe49eb29a3efcfa Mon Sep 17 00:00:00 2001
From: Vidushi Gupta <55969597+Vidushi-Gupta@users.noreply.github.com>
Date: Tue, 8 Feb 2022 13:29:40 +0530
Subject: [PATCH] Adding R linked lessons for topics in README

---
 3-Data-Visualization/README.md | 15 ++++++++-------
 1 file changed, 8 insertions(+), 7 deletions(-)

diff --git a/3-Data-Visualization/README.md b/3-Data-Visualization/README.md
index 38d63b1c..fa46a85a 100644
--- a/3-Data-Visualization/README.md
+++ b/3-Data-Visualization/README.md
@@ -7,17 +7,18 @@
 Visualizing data is one of the most important tasks of a data scientist. Images are worth 1000 words, and a visualization can help you identify all kinds of interesting parts of your data such as spikes, outliers, groupings, tendencies, and more, that can help you understand the story your data is trying to tell.
 
 In these five lessons, you will explore data sourced from nature and create interesting and beautiful visualizations using various techniques.
-### Topics
 
-1. [Visualizing quantities](09-visualization-quantities/README.md)
-1. [Visualizing distribution](10-visualization-distributions/README.md)
-1. [Visualizing proportions](11-visualization-proportions/README.md)
-1. [Visualizing relationships](12-visualization-relationships/README.md)
-1. [Making Meaningful Visualizations](13-meaningful-visualizations/README.md)
+| Topic Number | Topic | Linked Lesson | Author |
+| :-----------: | :--: | :-----------: | :----: |
+| 1. | Visualizing quantities | <ul> <li> [Python](09-visualization-quantities/README.md)</li>  <li>[R]() </li> </ul>|<ul> <li> [Jen Looper](https://twitter.com/jenlooper)</li><li> [Vidushi Gupta]()</li> <li>[Jasleen Sondhi]()</li></ul> |
+| 2. | Visualizing distribution | <ul> <li> [Python](10-visualization-distributions/README.md)</li>  <li>[R]() </li> </ul>|<ul> <li> [Jen Looper](https://twitter.com/jenlooper)</li><li> [Vidushi Gupta]()</li> <li>[Jasleen Sondhi]()</li></ul> |
+| 3. | Visualizing proportions | <ul> <li> [Python](11-visualization-proportions/README.md)</li>  <li>[R]() </li> </ul>|<ul> <li> [Jen Looper](https://twitter.com/jenlooper)</li><li> [Vidushi Gupta]()</li> <li>[Jasleen Sondhi]()</li></ul> |
+| 4. | Visualizing relationships | <ul> <li> [Python](12-visualization-relationships/README.md)</li>  <li>[R]() </li> </ul>|<ul> <li> [Jen Looper](https://twitter.com/jenlooper)</li><li> [Vidushi Gupta]()</li> <li>[Jasleen Sondhi]()</li></ul> |
+| 5. | Making Meaningful Visualizations | <ul> <li> [Python](13-meaningful-visualizations/README.md)</li>  <li>[R]() </li> </ul>|<ul> <li> [Jen Looper](https://twitter.com/jenlooper)</li><li> [Vidushi Gupta]()</li> <li>[Jasleen Sondhi]()</li></ul> |
 
 ### Credits
 
-These visualization lessons were written with 🌸 by [Jen Looper](https://twitter.com/jenlooper)
+These visualization lessons were written with 🌸 by [Jen Looper](https://twitter.com/jenlooper), [Jasleen Sondhi]() and [Vidushi Gupta]().
 
 🍯 Data for US Honey Production is sourced from Jessica Li's project on [Kaggle](https://www.kaggle.com/jessicali9530/honey-production). The [data](https://usda.library.cornell.edu/concern/publications/rn301137d) is derived from the [United States Department of Agriculture](https://www.nass.usda.gov/About_NASS/index.php).