Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/achubaty/datawranglr

course notes for "Data Wrangling and Presentation in R"
https://github.com/achubaty/datawranglr

Last synced: 12 days ago
JSON representation

course notes for "Data Wrangling and Presentation in R"

Awesome Lists containing this project

README 

        
# Data Wrangling and Visualization in R



BISC 888-1 Directed Readings at Simon Fraser University



## Course Description

When presenting research "a picture is worth a thousand words", but how do you make that picture as clear and compelling as possible?

The R programming language is predominately known for statistical analysis, but R is also capable of producing publication-quality figures for scientific papers, international newspapers (e.g., The New York Times), and websites.

In addition to its core functionality, sophisticated visualization in R is enhanced by supplemental packages, most notably the `ggplot2` library.

In this course we move beyond basic plotting and highlight some of the more powerful approaches for visualization in R.

Students will learn to rapidly explore their data with the `ggplot2` package and develop highly-customized figures with base graphics functions.

This course will also cover the use of the `plyr` and `reshape2` packages, which are useful tools to format, reshape, and "wrangle" data sets before plotting or analysis.

This course is applicable both to students who have never used R before and those who have used R, but have not accessed its higher-powered data-manipulation and graphing capabilities.

Throughout the course, the exercises and assignments will emphasize reproducible research documentation ("literate programming") in which documentation, code, and figures are combined in the easy-to-learn plain-text language Markdown.



We will meet for 2-hour blocks every 2 weeks. Students will receive 1 course credit, graded pass/fail. The final grade is determined by completion of assignments and attendance. Assignments will be given at the end of each meeting and will be due prior to the following meeting. Attendance is mandatory for a passing grade.



## Course Instructors

 - Bernard Roitberg (faculty supervisor): [email protected]

 - Franz Simon [email protected]

 - Sean Anderson: [email protected]

 - Alex Chubaty: [email protected]

 - Corey Phillis: [email protected]



## Class size

 - Based on enrollment (limited to 20 students)



## Course Highlights

- We will meet for 2-hour sessions bi-weekly for a total of 6 sessions

- Targeted for new and experienced R users

- Learn basic R commands and usage

- Produce high-quality graphics using R base graphics and `ggplot`

- Construct custom figures using `par`

- Learn to manipulate data quickly using `plyr` and `reshape`

- Begin using Markdown and R together to generate reproducible reports



## Course Overview

### Before we start

- Install R version 3.0.0 or higher from [CRAN](http://cran.stat.sfu.ca)

- Install R Studio from [rstudio.org](http://www.rstudio.com/ide/download/desktop)



### Topics covered

- Introduction to R

- Reproducible documents with Markdown

- R base graphics

- Data manipulation in R: `plyr` and `reshape`

- R grid graphics (`ggplot`)

- Multipanel plotting with base graphics (`layout`, `mfrow`, `split.screen`)

- Additional graphics customization (`par`, building plots with `lines`, `points`, etc.)



### Assignments

- Assignments are due at the start of class

- Assignments are designed to apply the skills learned and practice using R

- All assignments will be written in Markdown format