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Overview


Interactive Visualization with R for Social Scientists

Next course runs from [[date]]

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Overview


Interactive Visualization with R for Social Scientists

Next course runs from [[date]]

Course overview

If you’re a social scientist looking to communicate your research in a new and engaging way, this course could be the right choice for you. 

This course introduces you to techniques and tools for presenting data in visually attractive and interactive ways using the R programming language. 

Data visualization is a powerful tool for any social scientist looking to disseminate and communicate their research findings. Data in a table or spreadsheet is valuable, but as human beings, we often find it challenging to see patterns or summarize tabular data. Visualizations allow you to do exactly that – create a visual representation of the data, giving you a chance to see and interpret complex data efficiently at a glance.
 

Course objectives

By the end of the course you will:

  • Be familiar with the workflows for producing visualizations

  • Be able to produce a range of visualizations from data

  • Understand the need for interactive visualizations and reports, and the associated workflows

  • Produce a range of visualizations relevant to the available data

  • Create a report that tells a story from data using appropriate interactive visualizations

 

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Interactive Visualization with R for Social Scientists

Effort
This course is approximately 35 hours of learning including activities.
Prerequisites
This course assumes a basic familiarity and comfort with the R language and RStudio, it's assumed that you know what the following things mean (and how to do them):
  • Install and load an R package
  • Assign a variable
  • Import a .csv file into R
  • Extract specific columns from a "data frame"
In addition, this course depends heavily on the pipe operator (%>%). Though the instructor will cover the basics of using %>% in code, it's well worthwhile reading http://r4ds.had.co.nz/pipes.html in preparation for the course.
Instructors
Martin John Hadley and Professor Richard Traunmüller
In association with
Royal Statistical Society
Language
English
 
299.00
Start date:
Enroll
299.00
Start date:
Enroll

Course Instructors


Course Instructors


Course Instructors

 
 

How it works


How it works


How it works

The course is organized into a set of four interactive learning modules, and you should work through the modules sequentially.
 
The interactive learning modules contain a number of topic pages. Each topic page has a video to walk you through the concept and interactive text to reinforce what was covered in the video, quick questions and knowledge checks.
 
There are three additional types of activity in your course to facilitate deeper learning. These are presented in the relevant topic pages.

  1. Match: These activities require you to have a go at a task offline, then select the correct solution
  2. Guided: These are multi-part match activities so you do a part of the task then submit your solution, which unlocks feedback on your attempt and the next part of the task
  3. Structured: This is a more complex offline task. To see the Tutor’s solution you need to share your attempt at the task and your reasoning. You also get to see other participants' attempts and are encouraged to engage in discussion. The Tutor will then share further feedback

The vast majority of topics in the course are fundamentally practical. You are strongly encouraged to recreate and run the code as you work through them, and complete knowledge checks and activities.

You have 3 months' access to this course. During the first 4 weeks of your course you will receive learning support from Martin, your instructor.  We recommend working through as many modules as possible in these initial 4 weeks so that you can make the most Martin’s expertise. He’ll be on hand to answer any questions, or help you if you get stuck.

After the learning support period, you’ll still have access to the course materials but you won’t receive assistance from the instructor. SAGE Campus will help you with any IT or platform issues you might have throughout the course.


 

Syllabus


Syllabus


Syllabus 

Module 1 - Toolkit

Module 1 gives an overview of interactive visualization, and explains how to set up the various toolkits you’ll be using throughout the course

Module 2 - Getting ready

In this module, you’ll cover the following:

  • Typical workflow for interactive visualizations and reports - Overview of the workflow for putting together an interactive visualization and report
  • Planning a story - What needs to be considered when planning visualizations and reports
  • Getting data ready - Coverage of defined tidyverse packages to get data ready for visualization, along with a simple exercise
  • A simple example of a workflow - Preparing data using tidyverse and producing a simple bar chart with plotly

Module 3 - Interactive charts and maps

In this module, you’ll cover the following:

  • Producing charts with plotly - More in-depth look at using htmlwidget plotly to make a chart
  • Producing charts with highcharter - Making a chart with highcharter and comparison to plotly
  • Making an interactive map with leaflet and plotly - Creating a map with interactive markers
  • Producing a network chart - Creating a network chart using tibbles and visNetwork

Module 4 - Shiny basics and R markdown

In this module, you’ll cover the following:

  • Charts in shiny - Outputting htmlwidget charts in shiny
  • Controls and UI - Adding and configuring controls
  • Reactivity and publishing - Controlling when variables update, and publishing your app
  • Creating an RMarkdown document - Creating the right type of document for your report
  • Adding charts and code - Adding charts, code chunks and shiny apps
  • Publishing - Publishing Rmarkdown documents

Testimonials


Testimonials


what our learners say

In association with


In association with


developed in association WITH

This course was first delivered by the Royal Statistical Society at the International conference in 2017. This course is an online course, which is an expanded version of that course.
 

FAQs


FAQs


Frequently Asked Questions

Please see below answers to some of the most frequent questions we get about this course.

What do I need to know before taking this course?

This course assumes a basic familiarity and comfort with the R language and RStudio. It's assumed that you know what the following things mean (and how to do them):

  • Install and load an R package
  • Assign a variable
  • Import a .csv file into R
  • Extract specific columns from a "data frame"

In addition, this course depends heavily on the pipe operator (%>%). Though the instructor will cover the basics of using %>% in code, it's well worthwhile reading http://r4ds.had.co.nz/pipes.html in preparation for the course.

Through the course you will be introduced to a wide-range of different packages for creating interactive charts, plots and network diagrams. Each of these packages has a slightly different approach to handling data. During the course you will develop an understanding of these approaches like accessing specific columns from "data frames". The exercises will provide you with the opportunity to test your understanding of these approaches but you should expect to mix these up a bit before you've mastered them.

Finally, the Shiny component of the course does cover the more conceptually complicated concepts of transferring data between "client" and "server" in order that you can create useful interactive web applications and visualizations of your research data. The course is deliberately designed to equip you with all of the basics to build Shiny apps and the exercises will slowly improve your understanding of how to craft Shiny apps that fit your needs.

What software do I need for this course?

It’s a good idea to install R Studio prior to starting this course as this will be used throughout the course (this should take about 10 minutes to do). There are a number of R libraries that are required but these will be discussed and can be installed via R Studio.

Do I need to buy any of this software?

No, they are either open source or have community (free) versions.

What do I need to participate on this course?

A computer or laptop with the suggested software and a modern browser e.g. Internet Explorer 10+ or the latest versions of Chrome and Firefox.

Can I do this course on my mobile device?

While you can access the course on your mobile device, go through the content and answer questions, you will need a desktop or laptop computer to practice and complete the activities that require you to write and/or test code.

How long will I have access to the course for?

The course will be run over 4 weeks, during which you will have access to learning support provided by the course instructor. After the 4 weeks, you will still have access to the course materials for another 2 months, but you will not be able to receive learning support from the instructor, and if there is a course forum, you will not be able to ask any questions.

Do learners get a certificate?

All of our courses offer a certificate of completion signed by your instructor. You will be able to download this certificate, from the Learning Platform, when you complete the course.

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Interactive Visualization with R for Social Scientists
299.00
Start date:
Enroll