Plotting multiple time-series in ggplot

Question

I have a time-series dataset consisting of 10 variables.

I would like to create a time-series plot, where each 10 variable is plotted in different colors, over time, on the same graph. The values should be on the Y axis and the dates on the X axis.

Click Here for dataset csv

This is the (probably wrong) code I have been using:

c.o<-read.csv(file="co.csv",head=TRUE) ggplot(c.o, aes(Year, a, b, c, d, e,f))+geom_line() 

and here's what the output from the code looks like:

Can anyone point me in the right direction? I wasn't able to find anything in previous threads.

PROBLEM SOLVED, SEE BELOW.

One additional thing I would like to know:

Is it possible to add an extra line to the plot which represents the average of all variables across time, and have some smoothing below and above that line to represent individual variations?

Answer 1

If your data is called df something like this:

library(ggplot2) library(reshape2) meltdf <- melt(df,id="Year") ggplot(meltdf,aes(x=Year,y=value,colour=variable,group=variable)) + geom_line() 

So basically in my code when I use aes() im telling it the x-axis is Year, the y-axis is value and then the colour/grouping is by the variable.

The melt() function was to get your data in the format ggplot2 would like. One big column for year, etc.. which you then effectively split when you tell it to plot by separate lines for your variable.