Importing and recoding data

Lecture 10

Author

Affiliation

Dr. Mine Çetinkaya-Rundel

Duke University
STA 199 - Fall 2025

Warm-up

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Announcements

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• Start thinking about your project teams:

  • Teams of 3-4 people from your lab section
  • Fill out the project team form (link on Friday’s weekly recap email) or let your TA know of your team preferences by the end of lab on Monday
  • After that, we’ll assign teams for you

From last time

Finish up: ae-08-durham-climate-factors

• Go to your ae project in RStudio.

• Open ae-08-durham-climate-factors.qmd and pick up at “Pivot”.

Reading data into R

Reading rectangular data

• Using readr:
  • Most commonly: read_csv()
  • Maybe also: read_tsv(), read_delim(), etc.

. . .

• Using readxl: read_excel()

. . .

• Using googlesheets4: read_sheet() – We haven’t covered this in the videos, but might be useful for your projects

Application exercise

Reading Excel files

• Read an Excel file, with all its Excel-ness

• Split it into subsets based on features of the data

• Write out subsets as CSV files

Age gap in Hollywood relationships

Identify and articulate one feature of the data based on this visualization.

ae-08-age-gaps-import

• Go to your ae project in RStudio.

• If you haven’t yet done so, make sure all of your changes up to this point are committed and pushed, i.e., there’s nothing left in your Git pane.

• If you haven’t yet done so, click Pull to get today’s application exercise file: ae-08-age-gaps-import.qmd.

• Work through the application exercise in class, and render, commit, and push your edits.