Data Visualization

Code for Quiz 9.

  1. Load the R packages we will use.
library(tidyverse)
library(echarts4r)
library(ggforce) 
library(hrbrthemes)
library(tidyquant)
theme_set(theme_ipsum())
  1. Quiz questions

Question: e_charts-1

Create a bar chart that shows the average hours Americans spend on five activities by year. Use the timeline argument to create an animation that will animate through the years. - 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")

e_charts-1

Start with spend_time - THEN group_by year - THEN create an e_chart that assigns activity to the x-axis and will show activity by year (the variable that you grouped the data on) - THEN use e_timeline_opts to set autoPlay to TRUE - THEN use e_bar to represent the variable avg_hours with a bar chart - THEN use e_title to set the main title to ‘Average hours Americans spend per day on each activity’ - THEN remove the legend with e_legend

spend_time  %>% 
  group_by(year)  %>% 
  e_charts(x = activity , timeline = TRUE) %>% 
  e_timeline_opts(autoPlay = TRUE)  %>% 
  e_bar(serie = avg_hours)  %>% 
  e_title(text ='Average hours Americans spend per day on each activity')  %>% 
  e_legend(show = FALSE )

Question: echarts-2

Create a line chart for the activities that American spend time on. Start with spend_time - THEN use mutate to convert year from a number to a string (year-month-day) using mutate - first convert year to a string “201X-12-31” using the function paste - paste will paste each year to 12 and 31 (separated by -) - THEN use mutate to convert year from a character object to a date object using the ymd function from the lubridate package (part of the tidyverse, but not automatically loaded). ymd converts dates stored as characters to date objects. - THEN group_by the variable activity (to get a line for each activity) - THEN initiate an e_charts object with year on the x-axis - THEN use e_line to add a line to the variable avg_hours - THEN add a tooltip with e_tooltip - THEN use e_title to set the main title to ‘Average hours Americans spend per day on each activity’ - THEN use e_legend(top = 40) to move the legend down (from the top)

spend_time  %>%
  mutate(year = paste(year, "12","31", sep = "-"))  %>% 
  mutate (year = lubridate::ymd(year))  %>% 
  group_by(activity)  %>%
  e_charts(x  = year)  %>% 
  e_line(serie = avg_hours)  %>% 
  e_tooltip()  %>% 
  e_title(text = 'Average hours Americans spend per day on each activity')  %>% 
  e_legend(top = 40)

Question - modify slide 82

ggplot(spend_time, aes(x = year, y = avg_hours, color = activity)) +
  geom_point() +
  geom_mark_ellipse(aes(filter = activity == "leisure/sports", 
  description= "Americans spend on average more time each day on leisure/sports than the other activities"))

Question: tidyquant

Modify the tidyquant example in the video

Retrieve stock price for Microsoft, ticker: MSFT, using tq_get - from 2019-08-01 to 2020-07-28 - assign output to df

df  <- tq_get("MSFT", get = "stock.prices", 
          from = "2019-08-01", to = "2020-07-28" )

Create a plot with the df data - assign date to the x-axis - assign close to the y-axis - ADD a line with with geom_line - ADD geom_mark_ellipse - filter on a date to mark. Pick a date after looking at the line plot. Include the date in your Rmd code chunk. - include a description of something that happened on that date from the pandemic timeline. Include the description in your Rmd code chunk - fill the ellipse yellow - ADD geom_mark_ellipse - filter on the date that had the minimum close price. Include the date in your Rmd code chunk. - include a description of something that happened on that date from the pandemic timeline. Include the description in your Rmd code chunk - color the ellipse red - ADD labs - set the title to Microsoft - set x to NULL - set y to “Closing price per share” - set caption to “Source: https://en.wikipedia.org/wiki/Timeline_of_the_COVID-19_pandemic_in_the_United_States”

ggplot(df, aes(x = date, y = close)) +
  geom_line() +
  geom_mark_ellipse(aes(
    filter = date == "2020-02-19",
    description = "two more confirmed cases in California"
  ), fill  = "yellow",) +
  geom_mark_ellipse(aes(
   filter  = date == "2020-03-23",
    description = "WHO describes pandemic as 'accelerating'"
  ), color = "red", ) +
  labs(
    title = "Microsoft",
    x = NULL,
    y = "Closing price per share",
    caption = "Source: https://en.wikipedia.org/wiki/Timeline_of_the_COVID-19_pandemic_in_the_United_States"
  )