Load the R packages we will use.

library(tidyverse)
library(echarts4r)
library(ggforce) 
library(hrbrthemes)
library(tidyquant)
theme_set(theme_ipsum_rc())

Quiz questions

Replace all the instances of ‘SEE QUIZ’. These are inputs from your moodle quiz.

Replace all the instances of ‘???’. These are answers on your moodle quiz.

Run all the 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 (to your examples folder) and worked through the exercises in exercises_slides-73-108.Rmd.

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_tim

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 an 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

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

Create a plot with the spend_time data

assign year to the x-axis

assign avg_hours to the y-axis

assign activity to color

ADD points with geom_point

ADD geom_mark_ellipse

filter on activity == “leisure/sports” description is “Americans spend the most time on leisure/sport”

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 Facebook, ticker: FB, using tq_get

from 2019-08-01 to 2020-07-28

assign output to df

df<- tq_get ("FB",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

color the ellipse red

ADD labs

set the title to Facebook

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 == "2019-12-31",
    description = "The first recorded U.S. case of the new virus is reported"
  ), fill  = "yellow",) +
  geom_mark_ellipse(aes(
   filter  = date == "2020-05-25",
    description = "U.S. has 126,140 total deaths, 2.59 million confirmed cases, and 30 million tests completed."
  ), color = "red", ) +
  labs(
    title = "Facebook",
    x = NULL,
    y = "Closing price per share",
    caption = "Source: https://en.wikipedia.org/wiki/Timeline_of_the_COVID-19_pandemic_in_the_United_States"
  )

Data Visualization

Question: e_charts-1

Question: echarts-2

Question - modify slide 82

Question: tidyquant