Data visualization, part 1. Code for quiz 7.
Replace all the ???s. These are answers on your moodle quiz.
Run all the individual code chunks to make sure the answers in this file correspond with your quiz answers.
After you check all your code chunks run then you can knit it. It wont knit until the ??? are replaced.
the quiz assumes you have watched the videos and worked through the exercises in excersises_slides-1-49.Rmd
ggsave
command at the end of the chunk of the plot you want to preview.Create a plot with the faithful
dataset
Add points with geom_point
Assign the variable eruptions
to the x-axis
Assign the variable waiting
to the y-axis
Colour the points according to whether waiting
is smaller or greater than 77
ggplot(faithful) +
geom_point(aes(x = eruptions , y = waiting,
colour = waiting > 77))
create a plot with the faithful
dataset
add points with geom_point
assign the variable eruptions
to the x-axis
assign the variable waiting
to the y-axis
assign the colour blueviolet to all the points
ggplot(faithful) +
geom_point(aes(x = eruptions, y = waiting),
colour = "blueviolet")
create a plot with the faithful dataset
use geom_histogram()
to plot the distribution of waiting
time
assign the variable waiting
to the x-axis
ggplot(faithful) +
geom_histogram(aes(x = waiting))
see how shapes and sizes of points can be specified here: https://ggplot2.tidyverse.org/articles/ggplot2-specs.html#sec:shape-spec
create a plot with the faithful
dataset
add points with geom_point
assign the variable eruptions
to the x-axis
assign the variable waiting
to the y-axis
set the shape of the points to asterisk
set the point size to 8
set the point transparency to 0.7
ggplot(faithful) +
geom_point(aes(x = eruptions, y = waiting),
shape = "asterisk", size = 8, alpha = 0.7)
create a plot with the faithful
dataset
use geom_histogram()
to plot the distribution of the eruptions
(time)
fill in the histogram based on whether eruptions
are greater than or less than 3.2 minutes
ggplot(faithful) +
geom_histogram(aes(x = eruptions, fill = eruptions > 3.2))
create a plot with the mpg
dataset
add geom_bar()
to create a bar chart of the variable manufacturer
change code to plot bar chart of each manufacturer as a percent of total
change class to manufacturer
ggplot(mpg) +
geom_bar(aes(x = manufacturer, y = after_stat(100 * count / sum(count))))
for reference see: https://ggplot2.tidyverse.org/reference/stat_summary.html?q=stat%20_%20summary#examples
use stat_summary()
to add a dot at the median of each group
color the dot purple
make the shape of the dot asterisk
make the dot size 7
ggplot(mpg) +
geom_jitter(aes(x = class, y = hwy), width = 0.2) +
stat_summary(aes(x = class, y = hwy), geom = "point",
fun = "median", color = "purple",
shape = "asterisk", size = 7 )