- Load the R package we will use.
- Quiz questions
-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 won’t knit until the ??? are replaced
-The quiz assumes that you have watched the videos, downloaded (to your examples folder) and worked through the exercises in exercises_slides-1-49.Rmd
- Pick one of your plots to save as your preview plot. Use the ggsave command at the end of the chunk of the plot that you want to preview.
Question: Modify slide 34
-Create a plot with 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 64
ggplot(faithful) +
geom_point(aes(x = eruptions,
y = waiting,
colour = waiting > 64))
Question: Modify intro-slide 35
-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')
Question: Modify intro-slide 36
-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))
Question: Modify geom-ex-1
-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 plus -set the point size to 1 -set the point transparency 0.4
ggplot(faithful) +
geom_point(aes(x = eruptions, y = waiting),
shape = 'plus', size = 1, alpha = 0.4)
Question: Modify geom-ex-2
-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 then or less than 3.2 minutes
ggplot(faithful) +
geom_histogram(aes(x = eruptions, fill = eruptions > 3.2))
Question: Modify stat-slide-40
-Create a plot with the mpg dataset
-add geom_bar() to create a bar chart of the variable **manufacturer
ggplot(mpg) +
geom_bar(aes(x = manufacturer))
Question: Modify stat-slide-41
-change code to count and to plot the variable manufacturer instead of class
mpg_counted <- mpg %>%
count(manufacturer, name = 'count')
ggplot(mpg_counted) +
geom_bar(aes(x = manufacturer, y = count), stat = 'identity')
Question: Modify stat-slide-43
-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))))
Question: modify answer to stat-ex-2
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 blueviolet -make the shape of the dot cross -make the dot size 9
ggplot(mpg) +
geom_jitter(aes(x = class, y = hwy), width = 0.2) +
stat_summary(aes(x = class, y = hwy), geom = "point",
fun = "median", color = "blueviolet",
shape = "cross", size = 9)
