R-for-data-analysis-2023

Materials for the IRE & NICAR mini-bootcamp on using R for data analysis, Oct 30 - Nov 2, 2023.

Day 1

Goals: See some examples of what R can do, get familiar with RStudio, learn how to set up a project and run code, learn how the tidyverse packages work.

Story Examples:

• Texas winter storm excess deaths story, analysis
• Mapping Sinclair TV stations story, analysis

Resources:

• Introduction to R and RStudio (best to download this and open it in a browser)

Reference Scripts:

• My First Notebook!
• Intro to the Tidyverse

Day 2

Goals: Wrangle that data! We’ll import a csv and an excel file, and walk through the fundamentals: sorting, filtering, grouping, summarizing.

Resources:

• R Functions tipsheet
• Dplyr cheat sheet

Reference Scripts:

• Importing
• Sorting, filtering, and summarizing
• Grouping with salaries

Day 3

Goals: Joining. Learn how to work with multiple tables. Reinforce main analysis functions from Day 2.

Resources:

• Slides about different kinds of joins

Reference Scripts:

• Joining tables
• Using grepl

Day 4

Goals: Make tidy data! We often get data that is messy, dirty, misshapen, missing values, etc. We’ll cover best practices and helpful functions for cleaning data.

Resources:

• Tidyr cheat sheet
• Stringr cheat sheet
• Lubridate cheat sheet

Reference Scripts:

• Cleaning dirty data
• Graphing data in R