This course is part of the Data Visualization & Dashboarding with R Specialization

Collin Paschall

Offered By

Data Visualization & Dashboarding with R SpecializationJohns Hopkins University

About this Course

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Data visualization is a critical skill for anyone that routinely using quantitative data in his or her work - which is to say that data visualization is a tool that almost every worker needs today. One of the critical tools for data visualization today is the R statistical programming language. Especially in conjunction with the tidyverse software packages, R has become an extremely powerful and flexible platform for making figures, tables, and reproducible reports. However, R can be intimidating for first time users, and there are so many resources online that it can be difficult to sort through without guidance.
This course is the second in a specialization in Data Visualization offered by Johns Hopkins. It is intended for learners who have either have some experience with R and data wrangling in the tidyverse or have taken the previous course in the specialization. The focus in this course learning to use ggplot2 to make a variety of visualizations and to polish those visualizations using tools within ggplot as well as vector graphics editing software. The course will not go into detail about how the data management works behind the scenes.

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Course 2 of 5 in the

Data Visualization & Dashboarding with R Specialization

Flexible deadlines

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Intermediate Level

Approx. 12 hours to complete

English

Subtitles: English

Instructor

Collin Paschall

Senior Lecturer

Johns Hopkins University Center for Advanced Governmental Studies

843 Learners

5 Courses

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 2 of 5 in the

Data Visualization & Dashboarding with R Specialization

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 12 hours to complete

English

Subtitles: English

Offered by

Johns Hopkins University

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.

Syllabus - What you will learn from this course

Week

Week 1

4 hours to complete

Introduction to the Grammar of Graphics

In this module, we will get started using ggplot2. You should begin by watching the introductory videos in each lesson. Then, carefully review the readings and reference materials provided. Once you have done that, I recommend watching the videos again to check your understanding. You will take a few quizzes as you progress through the material to make sure you are keeping up.

4 hours to complete

4 videos (Total 26 min), 10 readings, 3 quizzes

4 videos

Welcome to the Course2m

Getting Started with ggplot Part 17m

Getting Started with ggplot Part 28m

Distributions6m

10 readings

Note on Previewing Figures in R Studio5m

Wickham et al, Chapters 1 and 230m

ggplot Cheat Sheet15m

ggplot2 Overview and Reference15m

R Graphics Cookbook - Scatter Plots30m

Sample Data5m

R Graphics Cookbook - Histograms20m

R Graphics Cookbook - Box Plots10m

R Graphics Cookbook - Making a Density Plot10m

R Graphics Cookbook - Making a Violin Plot10m

2 practice exercises

ggplot2 Introduction and Scatter Plots10m

Univariate Figures Quiz5m

Week

Week 2

3 hours to complete

More Visualizations with ggplot

In this module, we will continue working with ggplot, learning additional types of visualization techniques. You should begin by watching the introductory videos in each lesson. Then, carefully review the readings and reference materials provided. Once you have done that, I recommend watching the videos again to check your understanding. You will take a few quizzes as you progress through the material to make sure you are keeping up.

3 hours to complete

7 videos (Total 39 min), 4 readings, 3 quizzes

7 videos

Bar Plots Part 16m

Bar Plots Part 25m

Bar Plots Part 34m

Line Plots Part 15m

Line Plots Part 24m

Learning New Figures Part 17m

Learning New Figures Part 24m

4 readings

Bar plots in the R Graph Gallery10m

Cookbook for R - Bar and line graphs15m

R Graphics Cookbook - Line Graphs30m

R Graph Gallery10m

2 practice exercises

Bar plots5m

Line plots quiz10m

Week

Week 3

5 hours to complete

ggplot Graphical Elements

In this module, we will cover how to refine plots created in ggplot2. You should begin by watching the introductory videos in each lesson. Then, carefully review the readings and reference materials provided. Once you have done that, I recommend watching the videos again to check your understanding. You will take a few quizzes as you progress through the material to make sure you are keeping up. Then, at the end of the module, you will submit an assignment for peer review that covers all of the material in this course.

5 hours to complete

6 videos (Total 38 min), 8 readings, 4 quizzes

6 videos

Annotations Part 14m

Annotations Part 26m

Colors, Legends, and Themes Part 18m

Colors, Legends, and Themes Part 25m

Inkscape Part 13m

Inkscape Part 28m

8 readings

Wickham et al, Chapter 820m

Wickham et al, Chapter 1030m

Wickham et al, Chapter 1615m

ggplot2 Themes Documentation15m

ggthemes Gallery10m

Download Page for Inkscape10m

Inkscape Tutorial Parts 1-330m

Inkscape Manual Quick Start Section10m

3 practice exercises

Annotations Quiz5m

Modifying Graphical Elements and Themes Quiz5m

Vector Graphics5m

About the Data Visualization & Dashboarding with R Specialization

This Specialization is intended for learners seeking to develop the ability to visualize data using R. Through five courses, you will use R to create static and interactive data visualizations and publish them on the web, which will you prepare you to provide insight to many types of audiences.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.
Will I earn university credit for completing the Course?
This Course doesn't carry university credit, but some universities may choose to accept Course Certificates for credit. Check with your institution to learn more. Online Degrees and Mastertrack™ Certificates on Coursera provide the opportunity to earn university credit.

More questions? Visit the Learner Help Center.

Data Visualization in R with ggplot2