R for Data Science

Mondays from Feb 25 - Apr 22, 2019

12:30 - 4:30 pm

Instructors: Dan Gatti, Selcan Aydin, Stanley Yang, Sue McClatchy

Helpers: Duy Pham

General Information

Where: Breezeway Bioinformatics Training Room, Bldg 1, Unit 5, Room 1540, 600 Main Street, Bar Harbor, Maine. Get directions with OpenStreetMap or Google Maps.

When: Mondays from Feb 25 - Apr 22, 2019. Add to your Google Calendar.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below). They are also required to abide by Code of Conduct.

Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:

Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.

Contact: Please email susan.mcclatchy@jax.org for more information.


Surveys

Please be sure to complete these surveys before and after the workshop.


Schedule

Monday, Feb 25

12:30 Welcome and introductions
12:45 Introduction to Data Exploration
12:55 Data Visualisation
14:30 Coffee
14:45 Data Visualisation (continued)
16:25 Wrap-up
16:30 End

Monday, Mar 11

12:30 Workflow: basics
12:45 Data Transformation
14:30 Coffee
14:45 Data Transformation (continued)
16:25 Wrap-up
16:30 End

Monday, Mar 18

12:30 Workflow: scripts
13:00 Exploratory Data Analysis
14:30 Coffee
14:45 Exploratory Data Analysis (continued)
15:45 Workflow: projects
16:25 Wrap-up
16:30 End

Monday, Mar 25

12:30 Introduction to Data Wrangling
12:45 Tibbles
13:30 Data Import
14:30 Coffee
14:45 Tidy Data
16:25 Wrap-up
16:30 End

Monday, Apr 1

12:30 Relational Data
13:45 Strings
14:30 Coffee
14:45 Strings (continued)
16:25 Wrap-up
16:30 End

Monday, Apr 8

12:30 Factors
13:15 Dates and Times
14:30 Coffee
14:45 Introduction to Programming
15:00 Pipes
15:15 Functions
16:25 Wrap-up
16:30 End

Monday, Apr 15

Holiday Patriots Day

Monday, Apr 22

12:30 Vectors
13:50 Iteration
14:30 Coffee
14:45 Introduction to Modelling
15:00 Model Basics
16:00 Model Building
16:25 Wrap-up
16:30 End

We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.


Syllabus

Data Science in R

  • Working with vectors, data frames, and tibbles
  • Importing, exploring, and tidying data
  • Creating and using scripts and projects
  • Working with different R data types
  • Modelling
  • Reference...

Setup

To participate in a workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.

We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.

R

R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.

Windows

Video Tutorial

Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE. Note that if you have separate user and admin accounts, you should run the installers as administrator (right-click on .exe file and select "Run as administrator" instead of double-clicking). Otherwise problems may occur later, for example when installing R packages.

macOS

Video Tutorial

Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.

Linux

You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo dnf install R). Also, please install the RStudio IDE.