R Tutorial: Refresher on xts and the plot() function Arnaud Amsellem The R Trader
Key Takeaways
Revises R xts and plot() function usage
Original Description
Want to learn more? Take the full course at https://learn.datacamp.com/courses/visualizing-time-series-data-in-r at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work.
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Welcome to Visualizing Time Series Data in R! My name is Arnaud Amsellem, and I’ll be your instructor for this course.
There is a fundamental difference between general plot and a times series plot. In a time series plot each value is associated to a time stamp where in a general plot there is no time index, there is no ordering in the data. In R there is a special class of objects to handle time series, the xts object. xts stands for eXtensible Time Series and this is a class of data that contains an array of values comprising data often in a matrix form and an index attribute to provide information about the data’s ordering. The index attribute must be a true time object: Date, POSIX Time, timeDate, chron and so on.
Once you have a time series the obvious question is how to visualize it? In R, the general plot function is plot() but for plotting time series plot.xts() is used instead. One useful trick to remember is that when the underlying object is a time series object then plot.xts() can be abbreviated and plot() can be used instead.
Let's look at an example. my_ts is a time series that you can plot using plot(). You can obviously draw a simple chart, but should you want to make it more readable or add specific information to tailor it, the plot() function offers many arguments. Probably too many to remember them all, but there are a few that need to be mastered in order to efficiently use R.
Once you have drawn my_ts the color of the line can be changed with the col argument. There is a small trick here. In order to change the line color without using plot() again, you can use the function lines using col = red to overplot the black line. We will see more about this function in the next chapter. The line thickness can also be adjuste
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