Load the R packages we will use.

library(tidyverse)
library(patchwork)

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-50-61.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 51

Create a plot with the mpg dataset
add points with geom_point
assign the variable displ to the x-axis
assign the variable hwy to the y-axis
add facet_wrap to split the data into panels based on the manufacturer

ggplot(data = mpg) +
  geom_point(aes(x = displ, y = hwy))+
  facet_wrap(facets = vars(manufacturer))

Question: Modify facet-ex-2

Create a plot with mpg dataset
add bars with geom_bar
- assign the variable manufacturer to the y-axis
add facet_grid to split the data into panels based on the class
- let scales vary across columns
- let space taken up by panels vary by columns

ggplot(mpg) +
  geom_bar(aes(y = manufacturer)) +
  facet_grid(vars(class), scales = "free_y", space = "free_y")

Questions: spend_time

To help you complete this question use:

the patchwork slides and
the vignette: https://patchwork.data-imaginist.com/articles/patchwork.html Download the file spend_time.csv from Moodle into directory for this post.
read_csv(“https://estanny.com/static/week8/spend_time.csv”)
spend_time contains 10 years of data on how many hours Americans spend each day on 5 activties.
read it into spend_time

spend_time <- read_csv("https://estanny.com/static/week8/spend_time.csv")

Start with spend_time

extract observations for 2011
THEN create a plot with that data
ADD a barchart with with geom_col
assign activity to the x-axis
assign avg_hours to the y-axis
assign activity to fill
ADD scale_y_continuous with breaks every hour from 0 to 6 hours
ADD labs to
set subtitle to Avg hours per day: 2011
set x and y to NULL so they won’t be labeled
assign the output to p1
display p1

p1 <- spend_time %>% filter(year == "2011") %>% 
ggplot() + 
  geom_col(aes(x = activity, y = avg_hours, fill = activity)) +
  scale_y_continuous(breaks = seq(0, 6, by = 1)) +
  labs(subtitle = "Avg hours per day: 2011", x = NULL, y = NULL)

Start with spend_time

THEN create a plot with it
ADD a barchart with with geom_col
assign year to the x-axis
assign avg_hours to the y-axis
assign activity` to fill
ADD labs to
set subtitle to “Avg hours per day: 2010-2019”
set x and y to NULL so they won’t be labeled
assign the output to p2
display p2

p2 <- spend_time %>% 
  ggplot() + 
  geom_col(aes(x = year, y = avg_hours, fill = activity)) +
  labs(subtitle = "Avg hours per day: 2010-2019", x = NULL, y = NULL)

Use patchwork to display p1 on top of p2 - assign the output to p_all - display p_all

p_all <-  p1 / p2

Start with p_all - AND set legend.position to ‘none’ to get rid of the legend - assign the output to p_all_no_legend - display p_all_no_legend

p_all_no_legend <- p_all & theme(legend.position = 'none')

Start with p_all_no_legend - see how annotate the composition here: https://patchwork.data-imaginist.com/reference/plot_annotation.html - ADD plot_annotation set - title to “How much time Americans spent on selected activities” - caption to “Source: American Time of Use Survey, https://data.bls.gov/cgi-bin/surveymost?tu”

p_all_no_legend +
  plot_annotation(title = "How much time Americans spent on selected activities", caption = "Source: American Time of Use Survey, https://data.bls.gov/cgi-bin/surveymost?tu")

Use spend_time from last question patchwork slides

Start with spend_time - extract observations for food prep - THEN create a plot with that data - ADD points with geom_point - assign year to the x-axis - assign avg_hours to the y-axis ADD line with geom_smooth - assign year to the x-axis - assign avg_hours to the y-axis ADD breaks on for every year on x axis with with scale_x_continuous ADD labs to - set subtitle to Avg hours per day: food prep - set x and y to NULL so x and y axes won’t be labeled - assign the output to p4 - display p4

p4  <- 
spend_time %>% filter(activity == "food prep")  %>% 
ggplot() + 
  geom_point(aes(x = year, y = avg_hours)) +
  geom_smooth(aes(x = year, y = avg_hours)) +
  scale_x_continuous(breaks = seq(2010, 2019, by = 1)) +
  labs(subtitle = "Avg hours per day: food prep", x = NULL, y = NULL)

Start with p4 - ADD coord_cartesian to change range on y axis to 0 to 6 - assign the output to p5 - display p5

p5 <-  p4 + coord_cartesian(ylim = c(0, 6))

Start with spend_time

create a plot with that data
ADD points with geom_point
assign year to the x-axis
assign avg_hours to the y-axis
assign activity to color
assign activity to group
ADD line with geom_smooth
assign year to the x-axis
assign avg_hours to the y-axis
assign activity to color
assign activity to group
ADD breaks on for every year on x axis with with scale_x_continuous
ADD coord_cartesian to change range on y axis to 0 to 6
ADD labs to
- set x and y to NULL so they won’t be labeled
assign the output to p6
display p6

p6   <- 
 spend_time  %>% 
ggplot() + 
  geom_point(aes(x = year, y = avg_hours, color = activity, group = activity)) +
  geom_smooth(aes(x = year, y = avg_hours, color = activity, group = activity)) +
  scale_x_continuous(breaks = seq(2010, 2019, by = 1)) +
  coord_cartesian(ylim = c(0, 6)) + 
  labs(x = NULL, y = NULL)

Use patchwork to display p4 and p5 on top of p6

(p4 | p5) / p6

Save file and plot.

ggsave(filename = "preview.png", 
       path = here::here("_posts", "2022-03-08-exploratory-analysis-ii"))

Exploratory Analysis II

Question: Modify slide 51

Question: Modify facet-ex-2

Questions: spend_time