First, make sure you install and load the esquisse package using install.packages and library:

install.packages("esquisse")
install.packages("ggplot2")

library(esquisse)
library(ggplot2)
library(jhur)

1.1

Try creating a plot using the Orange data that automatically comes with R using the esquisse package.

Drag and drop the age variable to be plotted on the x-axis.
Drag and drop the circumference variable to be plotted on the y-axis.
What happens when you drag tree to the facet region of the esquisse GUI?
What happens if you move this to color?
Copy and paste the code from both options into the chunk below:

# esquisser(Orange)
ggplot(Orange) +
  aes(x = age, y = circumference) +
  geom_point(shape = "circle", size = 1.5, colour = "#112446") +
  theme_minimal() +
  facet_wrap(vars(Tree))

ggplot(Orange) +
  aes(x = age, y = circumference, colour = Tree) +
  geom_point(shape = "circle", size = 1.5) +
  scale_color_hue(direction = 1) +
  theme_minimal()

1.2

Click where it says “point” (may say “auto” depending on how you did the last question) on the far left side and change the plot to a different type of plot. Copy and paste the code into the chunk below. Close Esquisse and run the chunk below to generate a ggplot.

ggplot(Orange) +
  aes(x = age, y = circumference, colour = Tree) +
  geom_line(size = 0.5) +
  scale_color_hue(direction = 1) +
  theme_minimal()

## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.

Practice on Your Own!

P.1

Launch Esquisse on any selection of the following datasets we have worked with before and explore!

yts <- read_yts()
tb <- read_tb()
bike <- read_bike()

## Rows: 1631 Columns: 9
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (6): subType, name, block, type, project, route
## dbl (3): numLanes, length, dateInstalled
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

circ <- read_circulator()

## Rows: 1146 Columns: 15
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr  (2): day, date
## dbl (13): orangeBoardings, orangeAlightings, orangeAverage, purpleBoardings,...
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

vacc <- read_csv("http://jhudatascience.org/intro_to_r/data/USA_covid19_vaccinations.csv")

## Rows: 64 Columns: 125
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr   (1): State/Territory/Federal Entity
## dbl (121): Total Doses Delivered, Doses Delivered per 100K, 18+ Doses Delive...
## lgl   (3): People with 2 Doses by State of Residence, People 18+ with 1+ Dos...
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

# esquisser(vacc)

Esquisse Data Visualization Lab - Key

1.1

1.2

Practice on Your Own!

P.1