Exploratory Analysis

Data visualisation part 1. Code for Quiz 7

Load the R package we will use
```
library(tidyverse)
```

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.

Questions: Modify Silde 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 58

ggplot(faithful) + 
   geom_point(aes(x = eruptions, y = waiting, 
                  colour = waiting > 58))

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 ‘darkorange’ to all points

ggplot(faithful) + 
   geom_point(aes(x = eruptions, y = waiting),
              colour = "darkorange")

Question: modify intro-slide 36

Create a plot with the ‘faithful’ dataset
use ‘geom_histogram()’ to plot the distribution of the ‘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
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 ‘cross’
set the point size to ‘4’
set the point transparency ‘0.3’

ggplot(faithful) + 
   geom_point(aes(x = eruptions, y = waiting), 
   shape = "cross", size = 4, alpha =0.3)

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 here
Use stat_summary() to add a dot at the median of each group
color the dot ’orange
make the shape of the dot ‘square’
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 = "orange", 
  shape = "square", size = 9 )

ggsave(filename = "preview.png", 
       path = here::here("_posts", "2021-03-29-exploratory-analysis"))