Plotting Multiple Series in R — Part 4 in a Series

Frequently, you want to simultaneously plot multiple series on the same plot. Let’s try plotting daily observations along with a 30 day moving average.

To start, I have observations for YHOO stock from 12 April 1996 through 2 July 2009.

First, the data needs cleaning — I turn the column names into lower case for convenience with the tolower function and turn the text dates formatted as yyyy-mm-dd into dates instead of factors via the as.Date constructor for Date classes:

> yahoo <- read.csv(file='~/stuff/blog/YHOO stock prices [19960412, 20090702].csv', header=T, sep=',')
> str(yahoo)
'data.frame':	3329 obs. of  7 variables:
 $ Date     : Factor w/ 3329 levels "1996-04-12","1996-04-15",..: 3329 3328 3327 3326 3325 3324 3323 3322 3321 3320 ...
 $ Open     : num  15.2 15.5 15.8 15.9 15.6 ...
 $ High     : num  15.3 15.7 15.9 16 15.8 ...
 $ Low      : num  14.9 15.3 15.3 15.6 15.5 ...
 $ Close    : num  15 15.4 15.7 15.9 15.7 ...
 $ Volume   : int  16919900 12716100 16033900 12312100 26449100 19827800 30979700 15866300 26488700 20323100 ...
 $ Adj.Close: num  15 15.4 15.7 15.9 15.7 ...
>
> colnames(yahoo) <- tolower( colnames(yahoo) )
> yahoo$date <- as.Date( as.character( yahoo$date ) )
>
> # order yahoo into the same way we want to display it
> yahoo <- yahoo[ order(yahoo$date), ]

Now, let's take a first pass at plotting:

> plot(x=yahoo$date, y=yahoo$close,
+ 	main='YHOO stock close', xlab='date', ylab='close ($)')

YHOO close prices, all time

That isn't very pretty, not least of which because we're displaying too much data to be useful. Let's cut it down to just data from January 1 2008 and on:

> yahoo2 <- yahoo[ yahoo$date >= as.Date('2008-01-01'), ]
> plot(x=yahoo2$date, y=yahoo2$close,
+ 	main='YHOO stock close', xlab='date', ylab='close ($)')

YHOO close prices, 2008 on

It's worth pointing out that R's plotting code will attempt to set the upper and lower y bounds to something reasonable based on that data you present it with. However, sometimes, particularly to get a sense of scale, you really want to see the full range. You can accomplish this by explicitly setting the y axis limits with ylim. I also make the data more presentable.

> plot(x=yahoo2$date, y=yahoo2$close, ylim=c(0,1.1*max(yahoo2$close)),
+ 	col='black', type='l',
+ 	main='YHOO stock close', xlab='date', ylab='close ($)')

YHOO close data

Also, I wish to plot the moving average, so I create the function ma30 to calculate it. I also add ma30 as a column, using the whole data range so that the moving average is correct at the beginning of our subset:

> ma30 <- function( x, na.rm=F ){
+ 		val <- rep( 0, length( x ) )
+ 		for( j in 1:length( x ) ){
+ 			val[ j ] <- sum( x[ max( j - 29, 1 ):j ], na.rm=na.rm) / length( max( j-29,1):j )
+ 		}
+ 		val
+ 	}
>
> yahoo$close30 <- ma30(yahoo$close)
> yahoo2 <- yahoo[ yahoo$date >= as.Date('2008-01-01'), ]

And finally, I replot the data, adding the moving average as a second series and making it slightly bolder (lwd=2) to emphasize the moving average over the daily observations:

> plot(x=yahoo2$date, y=yahoo2$close, ylim=c(0,1.1*max(yahoo2$close)),
+ 	col='black', type='l',
+ 	main='YHOO stock close', xlab='date', ylab='close ($)')
> points(x=yahoo2$date, y=yahoo2$close30, col='red', type='l', lwd=2)

YHOO close data plus 30 day moving average