Exploratory analysis II

Modified slides from “excersises_slides-50-72.rmd” for Quiz 7

Load Libraries

library(pacman) #load package manager
p_load(tidyverse,  maps, sf,
       patchwork)
theme_set(theme_minimal())
library(patchwork)

Question 1 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 2 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 3 Spend Time

• Download the file spend_time.csv from moodle
• 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 2011
• 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: 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)

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) 

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

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 4 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)

*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