John Little 2021-06-17

Due to COVID-19, This repo supports preparation for remote zoom-based teaching. I’m flipping the workshop.

This letter will be sent in advance to workshop registrants.

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

This is a two-part workshop. In Part 1 you’ll learn the fundamentals of R, everything you need to know to quickly get started. 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.

See https://rfun.library.duke.edu/portfolio/r_flipped/

• Part 1a - QuickStart [Basic] Introduction to R: (Part 1a of 2)

• Part 1b - [Basic] Data wrangling with dplyr: (Part 1b of 2)

  • i - background: RStudio: download and run locally, or cloud versions
  • ii - background: RStudio IDE
  • iii - background: ggplot for visualization (briefly). See QuickStart
  • iv - background: R Packages and the Tidyverse
  • v - background: assignment and pipes
  • A - detailed explanation: Get data & code
  • B - detailed explanation: R Markdown for flexible reports and literate coding
  • C - Basic (part 1): Data wrangling with dplyr (see Part 1b, above)
  • D - detailed explanation: Exploratory Data Analysis (EDA) with skimr
  • E - detailed explanation: Project reproducibility

• Subsetting and wrangling Data (Interactive)
• Download the intro2r-code repository. Then, complete practice exercises: exercise_00.Rmd and exercise_01.Rmd

• Part 2 [Basic] Visualization with ggplot2 (Part 2 of 2)

  • G - background / in brief: interactive viz with plotly
  • H - detailed explanation: left_join. merging data
  • I - detailed explanation: Tidy and pivot data
  • J - brief explanation: Models and linear regression

• Interactive: visualization exercises on Bar Charts, Histograms, Boxplots, Scatterplots, Overplotting, etc.
• Angela Zoss’s ggplot exercies
• 01_exercises from Mastering the Tidyverse
• Interactive: Join Data