A short description of the post.
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
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)
_ 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 SEE QUIZ, ticker: SEE QUIZ, 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
ggplot(df, aes(x = date, y = close)) +
geom_line() +
geom_mark_ellipse(aes(
filter = date == "2020-01-08",
description = "The CDC issused its first public alert about the coronavirus "
), fill= "yellow") +
geom_mark_ellipse(aes(
filter = date == "2020-03-23",
description = "WHO describes pandemic as 'accelerating'"
), color = "red", ) +
labs(
title = "Google",
x = NULL,
y = "Closing price per share",
caption = "Source: https://en.wikipedia.org/wiki/Timeline_of_the_COVID-19_pandemic_in_the_United_States"
)