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