Data analysis and visualization in R for transportation
Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. The lessons below were designed for those interested in working with Transportation data in R for data analysis.
This is an introduction to R designed for participants with no programming experience. These lessons can be taught in an hour and a half tutorial. They start with some basic information about R syntax, the RStudio interface, and move through how to import CSV files, the structure of data.frame, how to deal with factors, how to add/remove rows and columns, and finish with how to calculate summary statistics for each level and a very brief introduction to plotting. Normal Data Carpentry tutorials are taught over a day. This material is signficantly shortened.
Content Contributors: Josie Kressner, Greg Macfarlane, Sarah Supp, John Blischak, Gavin Simpson, Tracy Teal, Greg Wilson, Diego Barneche, Stephen Turner, Francois Michonneau
Lesson Maintainers: Josie Kressner, Greg Macfarlane
Lesson status: Teaching
Lessons
- Lesson 00 Before we start
- Lesson 01 Introduction to R and dplyr
- Lesson 02 Data visualization with ggplot2
- Lesson 03 Using censusr [bonus if time allows]
Data
Two data files are required for this lesson: nhts_day.csv and nhts_per.csv. These only include the first 200 lines of the full National Household Travel Survey files.
Requirements
Data Carpentry’s teaching is hands-on, so participants are encouraged to use their own computers to insure the proper setup of tools for an efficient workflow. These lessons assume no prior knowledge of the skills or tools, but working through this lesson requires working copies of the software described below. To most effectively use these materials, please make sure to install everything before working through this lesson.
Please visit the ITM Tutorial homepage for software installations instructions for Windows, Mac, and Linux.