1- Load the R package we will use
- 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))
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")
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. Or read it in directly:
read_csv("https://estanny.com/static/week8/spend_time.csv")
# A tibble: 50 × 3
activity year avg_hours
<chr> <dbl> <dbl>
1 leisure/sports 2019 5.19
2 leisure/sports 2018 5.27
3 leisure/sports 2017 5.24
4 leisure/sports 2016 5.13
5 leisure/sports 2015 5.21
6 leisure/sports 2014 5.3
7 leisure/sports 2013 5.26
8 leisure/sports 2012 5.37
9 leisure/sports 2011 5.21
10 leisure/sports 2010 5.18
# … with 40 more rows• 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 2015
• THEN create a plot with that data
• ADD a barchart with with geom_col
assign activity to the x-axi s
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: 2015
set x and y to NULL so they won’t be labeled
• assign the output to p1
• display p1
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
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 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")
Patchwork 2
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)
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)) +
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
