Highlighting events in a time series
You have also learned that it is possible to use the function abline()
to add straight lines through an existing plot. Specifically, you can draw a horizontal line to identify a particular date by setting h
to a specific Y value, and a vertical line to identify a particular level by setting v
to a specific X value:
> abline(h = NULL, v = NULL, ...)
Recall that the index of an xts
object are date objects, so the X values of a plot will also contain dates. In this exercise, you will use indexing as well as as.Date("YYYY-MM-DD")
and mean()
to visually compare the average of the Citigroup stock market prices to its price on January 4, 2016, after it was affected by turbulence in the Chinese stock market.
You are provided with the same dataset data
as before. Let's give it a try.
Note: this code requires xts
version 0.9-7
to work. You can use remotes::install_version()
to install particular versions of packages.
This exercise is part of the course
Visualizing Time Series Data in R
Exercise instructions
- Plot the third series in
data
with the title "Citigroup" - Create
vert_line
, the index of the data point in the "citigroup" data that falls on January 4th, 2016 - Add a red vertical line at this date using
abline()
,.index()
, andvert_line
- Create
hori_line
, the object equal to the average value of the "citigroup" price - Add a blue horizontal line at this average value using
abline()
andhori_line
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Plot the "citigroup" time series
# Create vert_line to identify January 4th, 2016 in citigroup
vert_line <- which(index(___) == as.Date(___))
# Add a red vertical line using vert_line
abline(___ = .index(___)[___], col = "red")
# Create hori_line to identify average price of citigroup
hori_line <- ___(___)
# Add a blue horizontal line using hori_line
abline(___ = ___, col = "blue")