dplyr: joins and pivots

Lecture 9

Dr. Elijah Meyer

NC State University
ST 295 - Spring 2025

2025-02-06

Checklist

– Have you cloned the today’s AE repo?

– Are you keeping up with prepare material?

– Homework-2 is live! Due Feb 10th at 11:59

  -- Late window Feb 11th at 11:59

– Quiz-4 released today at noon!

Warm up

What would left_join(x,y) produce?

full_join()?

x <- tibble(
  value = c(1, 2, 3),
  xcol = c("x1", "x2", "x3")
  )
y <- tibble(
  value = c(1, 2, 4),
  ycol = c("y1", "y2", "y4")
  )

Warm up

Read the following code as a sentence

penguins |>
  filter(species == "Adelie",
         island == "Torgersen",
         !is.na(body_mass_g)) |>
  mutate(size = if_else(body_mass_g > 4000,"large","small")) |>
  select(body_mass_g, size)

AE

– if_else() vs case_when()

– joining by > 1 variable

– pivots

Joins Summary

– There are many ways to join data

– Let the join criteria choose the function for you

– Data sets are joined by a “key”

– The key(s) default to common names across data sets unless specified

– Can join on variables with different names by using the = sign by = c("variable1" = "variable2")

Forms of Data

Data Format (Wide vs Long)

– Wide data contains values that do not repeat in the first column

– Long data contains values that do repeat in the first column

Data Format (Wide vs Long)

– Which have we typically used to create plots in this class?

Tidy Data

There are three interrelated rules that make a dataset tidy:

Each variable is a column; each column is a variable.
Each observation is row; each row is an observation.
Each value is a cell; each cell is a single value.

Motivation

– Sometimes, data are not in this format…

pivots

– pivot_longer

– pivot_wider

pivot_wider

– Making tables for quick comparison / display purposes

– names_from

– values_from