quickStart with R

R and the Tidyverse are a data-first coding language that enables reproducible analytics workflows. In this two-part workshop, you’ll learn the fundamentals of R, everything you need to know to quickly get started.

In Part 1 you’ll learn how to access and install RStudio, how to wrangle data for analysis, gain a brief introduction to visualization, practice Exploratory Data Analysis (EDA), and how to generate reports. In Part 2 you’ll learn about visualization using ggplot2, how to make interactive charts for use in dashboards, how to reshape and merge data, and be introduced to models.

Part 1 has no prerequisites and no prior experience is necessary. By the end of part 1 you will import data, edit and save scripts, subset data, use projects to organize your work, and develop self-help techniques.

Additonal videos…  
Import data / get code Projects / Reproducibility
Exploratory Data Analysis (EDA) Assignment <- / Pipes %>%
Join / Merge (left_join) Packages / Tidyverse
Pivot data (pivot_longer) RStudio IDE
R Markdown Download
Or see the complete “Rfun flipped” YouTube playlist  

Part 2 requires the familiarity of part 1. By the end of part 2 you will have a familiarity with the grammar of graphics, be introduced to interactivity techniques, be able to invoke data joins and pivots, and gain an introduction to linear regression.

This next video starts at timestamp 19:42 and covers how to handle linear regression models.

Register

Register: Part 1. Jan. 28, 2021

Register: Part 2. Feb. 4, 2021  

      Repeat…
Register: Part 1. Mar. 16, 2021

Code Repositories

Resources

Image Credit Data Visualization: Bang Wong. Peter Durand

Rfun is a DVS learning series

The 'R We Having Fun Yet?' learning series is part of the broader Data & Visualization Services workshop series. DVS offers workshops on [R], Python, GIS and mapping, Research Data Management, and Visualization.

Rfun Blog

The blog features semester summaries of our workshop series and extra bits of information which may assist you in your practical data science journeys.