Exploratory Analysis

Data visualization, part 1. Code for Quiz 7.

1. Load the R package we will use.

library(tidyverse)

2. 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 data set

*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 64

ggplot(faithful) + 
   geom_point(aes(x = eruptions, y = waiting, 
                  color = waiting > 64)) 

Question : modify intro-slide 35

*create a plot with the faithful database

*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 the points

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

Question : modify intro-slide 36

*Create a plt 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

*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 triangle set the point size to 7 set the point transparency 0.5

ggplot(faithful) + 
   geom_point(aes(x = eruptions, y = waiting), 
   shape = "triangle", size = 7, alpha =0.5) 

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 examples.

Use stat_summary() to add a dot median at the median of each group

color the dot dodgerblue

make the shape of the dot plus

make the dot size 2

ggplot(mpg) + 
  geom_jitter(aes(x = class, y = hwy), width = 0.2) +
  stat_summary(aes(x = class, y = hwy), geom = "point", 
  fun = "median", color = "dodgerblue", 
  shape = "plus", size = 2 )

ggsave(filename = "preview.png", 
       path = here::here("_posts", "2021-03-26-exploratory-analysis"))