Getting Started with Data Visualization in R

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Getting Started with Data Visualization in R

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

Instructor: Collin Paschall

34,993 already enrolled

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3 modules

Gain insight into a topic and learn the fundamentals.

306 reviews

Beginner level

No prior experience required

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

94%

Most learners liked this course

3 modules

Gain insight into a topic and learn the fundamentals.

306 reviews

Beginner level

No prior experience required

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

94%

Most learners liked this course

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

9 assignments¹

AI Graded see disclaimer

Taught in English

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

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 3 modules in this course

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.

To fill that need, this course is intended for learners who have little or no experience with R but who are looking for an introduction to this tool. By the end of this course, students will be able to import data into R, manipulate that data using tools from the popular tidyverse package, and make simple reports using R Markdown. The course is designed for students with good basic computing skills, but limited if any experience with programming.

In this module, we will get set up with R to process data for visualizations. 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.

What's included

8 videos7 readings4 assignments1 peer review

8 videos Total 40 minutes

Introduction to the Course 3 minutes
Introduction to R and Software Installation 6 minutes
Basic R, Part 1 4 minutes
Basic R Part 2 6 minutes
Functions in R 3 minutes
Dataframes 8 minutes
Basics of Importing Data into R 6 minutes
Base R Visualizations 5 minutes

7 readings Total 107 minutes

How to Watch the Videos 2 minutes
The RStudio Cheat Sheet 20 minutes
Base R Cheat Sheet 20 minutes
R for Data Science, Chapter 4 20 minutes
A Note on File Paths 10 minutes
CCES Data 5 minutes
Cookbook for R: Basic Plots 30 minutes

4 assignments Total 35 minutes

Install R and Setup Quiz 10 minutes
Base R and Functions Quiz 10 minutes
Dataframes and Importing Data in R 10 minutes
Base R Visualization Quiz 5 minutes

1 peer review Total 30 minutes

Base R Peer Review Practice 30 minutes

In this module, we will use functions from the tidyverse to manipulate data. 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.

What's included

5 videos7 readings2 assignments1 peer review

5 videos Total 27 minutes

Introduction to the tidyverse 6 minutes
Data import and structure in the tidyverse 5 minutes
Filtering, selecting, recoding, renaming, and piping 6 minutes
Recoding, Renaming, and Calculating Columns 6 minutes
Grouping and summarizing data 4 minutes

7 readings Total 160 minutes

R for Data Science, Introduction and Part II: Wrangle 40 minutes
Data Import Cheat Sheet 10 minutes
tibble, readr, and tidyr Documentation 30 minutes
R for Data Science, Chapter 5 30 minutes
Data Wrangling Cheat Sheet 10 minutes
Getting Started with dplyr 20 minutes
Learning to Read R Documentation 20 minutes

2 assignments Total 30 minutes

Tidyverse Introduction Quiz 15 minutes
Manipulating Variables and Creating Summaries Quiz 15 minutes

1 peer review Total 30 minutes

tidyverse Practice Peer Review 30 minutes

In this module, we learn to make reproducible reports using R Markdown. 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.

What's included

3 videos8 readings3 assignments1 peer review

3 videos Total 15 minutes

Creating reports with R Markdown 6 minutes
R Markdown syntax and tables 5 minutes
qplots and closing thoughts 4 minutes

8 readings Total 90 minutes

Note on Installing LaTex 10 minutes
Note on Previewing Figures in R Markdown 10 minutes
R for Data Science, Chapter 27 10 minutes
R Markdown Cheat Sheet 10 minutes
R Markdown Reference Guide 10 minutes
R Markdown: The Definitive Guide 10 minutes
qplot() Documentation 20 minutes
A Note About Peer Review Assignments 10 minutes

3 assignments Total 20 minutes

R Markdown Intro Quiz 10 minutes
R Markdown Syntax Quiz 5 minutes
Incorporating Tables and Figures Quiz 5 minutes

1 peer review Total 120 minutes

Your R Markdown Report 120 minutes

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Instructor

Instructor ratings

(130 ratings)

Collin Paschall

Johns Hopkins University

5 Courses 44,438 learners

Offered by

Johns Hopkins University

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Reviewed on Jan 29, 2021

very informative and easy xplanation course. Very helpful in analyasis

Reviewed on Apr 11, 2021

I found this course interesting. It help me improve on the skills as a look to advance skills in R.I liked the recode function. I had not yet used it

Reviewed on Jun 7, 2024

Course materials and guides were streamlined and clear. I really enjoyed doing all the activities and assessments!

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