- 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 videos, downloaded (to your examples folder) and worked through the exercises in “exercises_slides-73-108.Rmd”. Knitted file is here.
#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 through the years.
spend_time <- read_csv("https://estanny.com/static/week8/spend_time.csv")
-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
#echarts-2
Create a line cgart for the activities that Americans 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 (seperated 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 onject 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)
#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"))
#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 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 == "2020-01-08", description = "CDC issues first public alert avout COVID-19"), fill = "yellow") +
geom_mark_ellipse(aes(filter = date == "2020-03-16", description = "Our World in Data reports 3,170 deaths, 164,620 confirmed cases, and 1.07 million tests completed in the U.S."), 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")
