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Go to Help! for some troubleshooting options, cheatsheets, and other learning resources.

R Camp

This series of workshops teaches the basics of importing data, using new packages, cleaning and summarizing data with tidy tools, and using ggplot2 to create charts, maps and other data visualizations.

Day 1

  1. Become a Jedi scrap scavenger
  2. Project launch
    • Create a new project and R script
    • Install R packages
    • Create variables, lists, data frames
  3. Read data into R
    • Arrange, select and filter data
  4. Plot the data!

Packages: readr, dplyr
Planets visited: Jakku

  1. The ggplot sandwich
  2. Data cleaning
  3. Data transformations
    • Add new columns and convert units
    • Summarize data
  4. Group the data
    • Answers for each monitoring site or group

Packages: dplyr,
Planets visited: Jakku

  1. Working with Dates
  2. Join 2 data tables
  3. Calculate new column values
  4. Save data
  5. More plots!

Packages: ggplot2, lubridate
Planets visited: Endor

  1. Conditions: ifelse() do this
  2. Summarize by group
  3. Even more plots
    • Scatter plots + box plots
    • Add titles, colors, and labels
    • Reference lines
  4. Save plots
  5. Explore Your data
    • Tidy your data
    • Plot your data

Packages: ggplot2, readxl Planets visited: Ahch-To

R Workshops

Each of these workshops dives into more detail on a common data anlaysis task.

Messy data
Databases
Maps and shapefiles

  1. Collapse data spread across many columns
  2. Read an entire folder of files and combine into 1 table
  3. Order plots from highest to lowest
  4. Parse dates into seasons, months, quarters, or day of the year

Packages: tidyr, readxl, lubridate, forcats

  1. Connect to Oracle databases
    • DELTA / TEMPO
  2. Explore datbase tables
  3. Read data from different schemas
  4. Join tables

Packages: RODBC, dplyr

  1. Read and save shapefiles
  2. Convert coordinate projections (ex. Lat/Long to UTM)
  3. Load reference maps
    • States, counties, ZIP Codes
  4. Build interactive maps

Packages: leaflet, sf, tidycensus, tigris


Web data
Talking to SAS & MATLAB
Tableau reading

  1. Read CSVs from the web
  2. Connect to FTP sites
  3. Other web APIs
  4. Scrape text from webpages

Packages: dplyr

  1. Read & write data from other stats programs
    • SAS, SPSS, & Stata
    • MATLAB
    • Systat / SigmaPlot
    • Minitab

Packages: haven, foreign

  1. Read and save shapefiles
  2. Convert projections
    • Lat/Long to UTM
  3. Load reference maps
    • States, counties, ZIP Codes
  4. Build interactive maps

Packages: readr