Transform and visualize data in R using the packages tidyr, dplyr and ggplot2: An EDI VTC Tutorial.

Key Info
Description - a brief synopsis, abstract or summary of what the learning resource is about: 

The two tutorials, presented by Susanne Grossman-Clarke, demonstrate how to tidy data in R with the package “tidyr” and transform data using the package “dplyr”. The goal of those data transformations is to support data visualization with the package “ggplot2” for data analysis and scientific publications of which examples were shown.

Authoring Person(s) Name: 
Susanne Grossman-Clarke
Authoring Organization(s) Name: 
Environmental Data Initiative (EDI)
License - link to legal statement specifying the copyright status of the learning resource: 
Creative Commons 0 - CC0 "No Rights Reserved" (Public Domain)
Access Cost: 
No fee
Primary language(s) in which the learning resource was originally published or made available: 
English
More info about
Keywords - short phrases describing what the learning resource is about: 
Data handling
Data visualization tools
Expert guidance - Core Trustworthy Data Repositories Requirements
Transformation tools for data
Published / Broadcast: 
Tuesday, October 17, 2017
Publisher - organization credited with publishing or broadcasting the learning resource: 
Environmental Data Initiative (EDI)
Media Type - designation of the form in which the content of the learning resource is represented, e.g., moving image: 
Presentation - representation of the particular way in which an author shows, describes or explains one or more concepts, e.g., a set of Powerpoint slides.
Contact Person(s): 
Susanne Grossman-Clarke
Educational Info
Purpose - primary educational reason for which the learning resource was created: 
Instruction - detailed information about aspects or processes related to data management.
Learning Resource Type - category of the learning resource from the point of view of a professional educator: 
Demonstration / Simulation - imitation or modeling of a real-world process.
Target Audience - intended audience for which the learning resource was created: 
Graduate student
Undergraduate student
Data professional
Librarian
Citizen scientist
Intended time to complete - approximate amount of time the average student will take to complete the learning resource: 
More than 1 hour (but less than 1 day)
Framework - A community-based organization plan or set of steps for education or training: 
FAIR Data Principles