exploratory analysis 2

A short description of the post.

1. Load the R packages.

library(tidyverse)
library(patchwork)

2. Quiz Questions

• Replace all ?’s

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 data set -add bars with geom_bar -add facet-grid

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

Question 3

• Download the file spend_time.csv
• Read it into R

spend_time <- read_csv("spend_time.csv")

• Start with spend_time
• create a plot
• add geom_col, scale_y_continuous, and labs

p1 <- spend_time %>% filter(year == "2017") %>%
  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: 2017", x = NULL, y = NULL)
p1

• 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

• 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/surveym?tu")

Question: 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")

p4

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

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","2021-04-06-exploratory-analysis-2"))