ggplot2 wind time series with arrows/vectors

Question

From meteorological data (hourly values of temperature, wind and humidity) I managed to plot time series of wind speed and direction. Now I would like to add wind vectors on the time series plot. Here you can see the output I would like (arrows drawn over the actual plot).

I am using ggplot2, been looking through stackoverflow, ggplot2 package docs (will continue) but no solution found. Any idea or indication where to look would be a starting point.

Thanks in advance

EDIT QUESTION As suggested in a comment by @slowlearner I add here code and data to make a reproducible example. It looks like geom_segment could do the trick. I managed to calculate yend in geom_segment but can't figure out how to find xend as x axis is a time axis. I've got wind speed and direction data so I can calculate x,y wind components for geom_segment but x needs to be converted to time format.

Here is the code used for the plot (temperature) and data

for (i in 1:2 ) {

rams=subset(data,data$stat_id %in% i)
tore=subset(torre,torre$stat_id %in% i)

# Gràfica en ggplot

# Gráfica de evolución temporal de las estaciones de la zona

gtitol=places$nom[places$stat_id == i]

myplot=ggplot(data=rams,aes(x=datetime, y=tempc, colour="RAMS")) +
  geom_line()  +  ylab("Temperatura (ºC)") + xlab(" ") + 
  ggtitle(gtitol) + theme(legend.title=element_blank()) + theme(legend.position="bottom") +
  scale_y_continuous(limits = c(0,40)) +
  geom_line(data=tore,aes(x=datetime,y=temp,colour = "Torre")) 
#scale_y_continuous(breaks = round(seq(min(data$tempc), max(data$tempc), by = 2),0))


ggsave(myplot,filename=paste("RAMS-",i,".png",sep=""),width=7.78,height=5.79)

}

Following geom_segment docs I tried

p=ggplot(tore, aes(x =datetime, y = 5))
p + geom_segment(aes(xend = datetime, yend = 5 + v), arrow = arrow(length = unit(0.1,"cm")))

Getting this kind of figure. You can see x coordinate is datetime, how should I convert wind component to get xend? By now xend equals datetime but I would like something like "datetime + xwindcomp"

Thanks for your help

Answer 1

Just as a preamble, please make sure you include all code and relevant data in future questions. If you look at your question above, you will see that some objects such as torre are not defined. That means we can't copy and paste into our R setups. Also the data to which you linked could not be used with the code in the question as it was a limited subset. My advice: (a) create fake data that looks like the data you are using (b) keep your code to the absolute minimum (c) test and double-check code and data in a new R session before you post.

As far as I can tell you want something like the below. Of course you will have to adapt it for your own purposes, but it should give you some ideas on how to tackle your problem. Notice most of the cosmetic properties such as line colours, thicknesses, legends and titles have been omitted from the plot: they are not important for the purposes of this question. EDIT Another approach might be to use the same data frame for the wind data and then use a faceting variable to show the speed in a different but linked plot.

require(ggplot2)
require(scales)
require(gridExtra)
require(lubridate)
set.seed(1234)

# create fake data for temperature
mydf <- data.frame(datetime = ISOdatetime(2013,08,04,0,0,0) +
                   seq(0:50)*10*60,
                   temp = runif(51, 15, 25))

# take a subset of temperature data,
# basically sampling every 60 minutes
wind <- mydf[minute(mydf$datetime) == 0, ]
# then create fake wind velocity data
wind$velocity <- runif(nrow(wind), -5, 20)
# define an end point for geom_segment
wind$x.end <- wind$datetime + minutes(60)

ggplot(data = mydf, aes(x = datetime, y = temp, group = 1)) +
    geom_line() +
    geom_segment(data = wind,
                 size = 3,
                 aes(x = datetime,
                     xend = x.end,
                     y = 10,
                     yend = velocity),
                 arrow = arrow(length = unit(0.5, "cm"))) +
    theme()

This generates the following plot: