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README.Rmd
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---
title: "Intro to R, 2018 Fall"
author: "John Little"
date: "`r Sys.Date()`"
output: github_document
---
<!-- Edit the README.Rmd. Readme.md is auto genererated -->
[](https://mybinder.org/v2/gh/libjohn/intro2r-2018fall.git/master?urlpath=rstudio)
README
======
- Code
- https://is.gd/2018r1
- https://is.gd/2018r2
- Repo -- Intro2R repo
- https://is.gd/intro2r_2018fall
This repository contains supporting datasets and files for our [*Intro to R*](https://rfun.library.duke.edu/intro2r/) workshop by the [Data & Visualization Services Department](http://library.duke.edu/data), Duke University Libraries. You can find more information about our future and past [workshops](http://library.duke.edu/data/news)
- our *guide* can be found at our [Rfun site](https://rfun.library.duke.edu/intro2r/)
- More on R [(then, scroll down to "R Learning Resources".) Includes video captures](https://library.duke.edu/data/guides)
Outline
-------
1. Download the zipped repository 
1. Unzip/expand the zipped repo as a folder **in your Documents Directory**
1. Launch RStudio
1. File > New Project...
1. Existing Directory: Browse to your unzipped copy in the documents directory
1. Literate Coding: brief explanation
1. New Code Chunk: *Ctrl+Alt+I*
2. R Markdown: brief explanation
1. [`library(tidyverse)`](https://tidyverse.org)
2. Load & View Tibble (data frame)
3. Data Structure & Data Types (brief)
4. [`dplyr`](http://dplyr.tidyverse.org/) -- part of tidyverse
1. `filter` rows
2. `arrange` rows by variables
3. `select` columns
4. `mutate` derive cells / new variables
5. `count` column totals
6. `summarize` grouping reports
5. **Now You Try It.** Hands on exercises.
1. [exercise\_01.Rmd](exercise_01.Rmd)
2. [exercise\_02.Rmd](exercise_02.Rmd)
3. [answers.Rmd](answers.Rmd)
5. Basic Exploratory Data Analysis
1. Read in new datasets
1. `library(skimr)`
5. More `dplyr` -- join two datasets
1. `left_join` to merge data
7. More Visualize with `ggvis` (syntactically simpler than ggplot2, but...)
1. Basic visualization (Scatter Plot, Box Plot, Histogram, Bar Chart)
1. Take the ggplot2 workshop, or see the [materials](https://github.com/data-and-visualization/ggplot2-S18)
1. Resource: https://rfun.library.duke.edu/intro2r/visualization.html
9. Our Training Materials
1. R we having fun yet‽ <https://rfun.library.duke.edu>. Training materials for R.
- [2018 Workshops](http://rfun.library.duke.edu/2017/11/30/tidyverse-workshops-coming-in-january/): Intro to 2 / Visualization / Shiny / Mapping / Git / R Markdown
2. Full DVS [workshop series](https://library.duke.edu/data/news/past-workshops)
10. Questions: [Walk-in schedule](https://library.duke.edu/data/about/schedule) and by appointment [Data Science Consulting](https://library.duke.edu/data/about)
License
-------
Shareable via Creative Commons: [CC-BY-NC](https://creativecommons.org/licenses/by-nc/4.0/)<br> {height=30px}