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
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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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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 Sep 26, 2021
An accessible introduction to the world of R and Ggplot. The Specialization is recommended for researchers of all areas.
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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