Exploratory Analysis II

Data visualization, part 2. Code for quiz 8.

  1. Load the R package we will use

Question: Modify Slide 51

ggplot(data = mpg) + 
  geom_point(aes(x = displ, y = hwy)) + 
  facet_wrap(facets = vars(manufacturer))


Question: Modify facet-ex-2

ggplot(mpg) + 
  geom_bar(aes(y = manufacturer)) + 
  facet_grid(vars(class), scales = "free_y", space = "free_y")


Question: Spend_time

spend_time <- read_csv("spend_time.csv")

p1 <- spend_time %>% filter(year == 2019) %>% 
  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: 2019", x = NULL, y = NULL)

p1


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


p_all <- (p1/p2)

p_all


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: Patchwork 2

p4 <- spend_time %>% 
  filter(activity == "leisure/sports") %>% 
  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


p5 <- p4 + coord_cartesian(ylim = c(0,6))

p5


Start with spend_time

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

(p4/p5) / p6

ggsave(filename = "preview.png", path = here::here("_posts", "2022-03-25-exploratory-analysis-ii"))