- 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 you have watched the videos had 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 the faithful dataset
-Add points with geom_point
-Assign the variable eruptions to the x-axis
-Assign the variable waiting to the y-axis
-color the points according to whether waiting is smaller or greater than 76
ggplot(faithful) +
geom_point(aes(x = eruptions, y = waiting,
colour = waiting > 76))
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 color Purple to all the points
ggplot(faithful) +
geom_point(aes(x = eruptions, y = waiting),
colour = "purple")
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 than 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 purple
-Make the shape of the dot plus
-Make the dot size 3
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 = "plus", size = 3 )
ggsave(filename = "preview.png",
path = here::here("_posts", "2021-03-29-exploratory-analysis"))