1- Load the R package we will use
- 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 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
#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)
#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 other activities"))
#Question: tidyquant
Modify the tidyquant example in the video
Retrieve stock price for Google, ticker: GOOG, using tq_get
• from 2019-08-01 to 2020-07-28
• assign output to df
df <- tq_get("GOOG", 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 Google
* 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 == "2020-01-30", description = "The first case of person-to-person transmission was confirmed in Chicago"), fill = "yellow",) +
geom_mark_ellipse(aes(filter = date == "2020-03-26", description = "U.S has highest number of coronavirus patients in the world"), colour = "red",) +
labs(
title = "Google",
x = NULL,
Y= "Closing price per share",
caption = "Source: https://en.wikipepedia.org/wiki/Timeline_of_the_COVID-19_pandemic_in_the_United_States")
