- Load the R packages we will use.
- Quiz Questions
- Replace all the ???s. These are the 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 then you can knit it. It won’t knit until the ???s 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 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 the 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. Or read it in directly: 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 activities
- read it into spend_time
spend_time <- read_csv("spend_time.csv")
- Start with spend_time
- extract observations for 2018
- THEN create a plot with that data
- ADD a barchart 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 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)
p2
- 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
- see how to 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 Survery, 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 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: housework", 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 scale_x_conintuous
- 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
