- Load the R package we will use.
- Quiz questions
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 the mpg dataset
add bars with 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")
Question: 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.
spend_time contains 10 years of data on how many hours Americans spend each day on 5 activities
read it into spend_time
spend_time contains 10 years of data on how many hours Americans spend each day on 5 activities
read it into spend_time
spend_time <- read_csv(here::here("_posts", "2021-03-29-exploratory-analysis-ii", "spend_time.csv"))
Start with spend_time
extract observations for 2018
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: 2018
set x and y to NULL so they won’t be labeled
assign the output to p1
display p1
p1 <- spend_time %>% filter(year == "2018") %>%
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: 2018", x = NULL, y = NULL)
p1
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
p_all
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')
p_all_no_legend
Start with p_all_no_legend
ee 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")
Question: Patchwork 2
use spend_time from last question patchwork slides
Start with spend_time
extract observations for housework
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: housework
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 == "housework") %>%
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: leisure/sports", x = NULL, y = NULL)
p4
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))
p5
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)
p6
Use patchwork to display p4 and p5 on top of p6
( p4 | p5 ) / p6
ggsave(filename = "preview.png",
path = here::here("_posts", "2021-03-29-exploratory-analysis-ii"))