Visualize Data in R and Share Insights with Others
Instructor: Colin Paschall
Collin Paschall is a Senior Lecturer and Program Coordinator with the Center for Advanced Governmental Studies at Johns Hopkins University. He received his Ph.D. in Political Science from the University of Illinois at Urbana-Champaign and his J.D. from The George Washington University Law School. At Johns Hopkins, his teaching focuses on American government, research design, and data analysis. His research interests include legislative behavior in the U.S. Congress and the relationship between public opinion and the policymaking process. His work has appeared in Political Research Quarterly, Social Science Quarterly, and The Public Contract Law Journal. Dr. Paschall was an APSA Congressional Fellow in 2018-2019 in the office Congress member Karen Bass, working on issues related to criminal justice reform.
A repository dedicated to coursework, projects, and exercises completed during the Data Visualization & Dashboarding with R Specialization from John Hopkins University on Coursera.
There are a total of five courses in this Specialization.
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.
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.
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 third in the Specialization "Data Visualization and Dashboarding in R." Learners come into this course with a foundation using R to make many basic kinds of visualization, primarily with the ggplot2 package. Accordingly, this course focuses on expanding the learners' inventory of data visualization options. Drawing on additional packages to supplement ggplot2, learners will made more variants of traditional figures, as well as venture into spatial data. The course ends make interactive and animated figures.
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.
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 fourth in the Specialization "Data Visualization and Dashboarding in R." Learners will come to this course with a strong background in making visualization in R using ggplot2. To build on those skills, this course covers creating interactive visualization using Shiny, as well as combining different kinds of figures made in R into interactive dashboards.
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 is the final course in the Specialization "Data Visualization and Dashboarding in R." Learners in this course will enter with a well-developed set of skills making a wide variety of visualizations in R. The focus on this course will applying those skills to a unique project, drawing on publicly available data to tell a compelling story using the data visualization toolkit assembled in the previous courses.
This project is licensed under the MIT License.