My Blog: Exploratory analysis II

Load the R package(s) we will use.

library(tidyverse)
library(patchwork)

Quiz questions

Replace all of the ???
Run all 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, and worked through the exercises in exercises_slides-1-49.Rmd

Plot preview

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 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")

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

Start with spend_time

Extract observations for 2015
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: 2015
- Set x and y to NULL so they won’t be labeled
Assign the output to p1
Display p1

p1  <- spend_time %>% filter(year == "2015")  %>%
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: 2015", 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

ggsave(filename = "preview.png",
       path = here::here("_posts", "2022-03-12-exploratory-analysis-ii"))

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 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 Survery, 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 yera 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
Disply 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_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