9/19/2022

Chapter 6 - Tidy data

• Importing data with the path - see TidyData-path.R
• List-columns
  • Variables in data frames that have type list are called list-columns
  • Working with list-columns requires your careful attention
• Example with gender-neutral names
  • Starting with one name - e.g. "A Boy Named Sue"
  • A more thorough analysis with all baby names
• Naming conventions with objects
  • A name cannot start with a number
  • A name cannot contain punctuation, other than . or _
  • Case (R or r) matters in names - e.g., NCHS, nchs, Nchs, nChs, etc. are all different to R
  • Consider using tidyverse style guide, but recognize that deviations are inevitable when using code from lots of different people
  • The styler package can be used to reformat your code with the tidyverse style guide
• Data Intake - i.e., getting data into R
  • Native format for R is .rda or .RData
    • saveRDS() writes files in this format
    • readRDS() reads .rda or .RData files into R
  • Data-table friendly formats
    • CSV - comma separated values
    • Software-package specific format - e.g., Octave, Stata, SPSS, Minitab, SAS, Epi, etc.
    • Relational databases - see Chapter 15 for SQL
    • Excel
    • Web related - e.g., HTML, XML, JSON, Google Sheets, API
  • R packages for reading data
    • readxl - for Excel files
    • googlesheets4 - for Google Sheets
    • haven - for software packages
    • dplyr and DBI - for relational databases
    • readr and rvest - for web scraping - see TidyData-Read-from-web.R
  • APIs - application programming interface
    • twitteR
    • aRxiv
    • Rfacebook
    • instaR
    • FlickrAPI
    • tumblR
    • Rlinkedin
    • RSocrata
• Data cleaning
  • Transforming data in a variable to a useable form
• Recoding
  • translate integers (or other abbreviations) to more informative codes

Activity 8

• Replicate the analysis in Example 6.4.4 on nuclear reactors in Japan.

Please complete your reading of Chapter 6 for class on Wednesday.