A very newbish question, but say I have data like this:
test_data <-
data.frame(
var0 = 100 + c(0, cumsum(runif(49, -20, 20))),
var1 = 150 + c(0, cumsum(runif(49, -10, 10))),
date = seq(as.Date("2002-01-01"), by="1 month", length.out=100)
)
How can I plot both time series var0
and var1
on the same graph, with date
on the x-axis, using ggplot2
? Bonus points if you make var0
and var1
different colours, and can include a legend!
I'm sure this is very simple, but I can't find any examples out there.
For a small number of variables, you can build the plot manually yourself:
ggplot(test_data, aes(date)) +
geom_line(aes(y = var0, colour = "var0")) +
geom_line(aes(y = var1, colour = "var1"))
The general approach is to convert the data to long format (using melt()
from package reshape
or reshape2
) or gather()
/pivot_longer()
from the tidyr
package:
library("reshape2")
library("ggplot2")
test_data_long <- melt(test_data, id="date") # convert to long format
ggplot(data=test_data_long,
aes(x=date, y=value, colour=variable)) +
geom_line()
https://i.stack.imgur.com/qkaZR.png
Also see this question on reshaping data from wide to long.
gather()
function of tidyr
package to melt the data: gather(test_data, variable, value, -date)
You need the data to be in "tall" format instead of "wide" for ggplot2. "wide" means having an observation per row with each variable as a different column (like you have now). You need to convert it to a "tall" format where you have a column that tells you the name of the variable and another column that tells you the value of the variable. The process of passing from wide to tall is usually called "melting". You can use tidyr::gather
to melt your data frame:
library(ggplot2)
library(tidyr)
test_data <-
data.frame(
var0 = 100 + c(0, cumsum(runif(49, -20, 20))),
var1 = 150 + c(0, cumsum(runif(49, -10, 10))),
date = seq(as.Date("2002-01-01"), by="1 month", length.out=100)
)
test_data %>%
gather(key,value, var0, var1) %>%
ggplot(aes(x=date, y=value, colour=key)) +
geom_line()
https://i.stack.imgur.com/7ji3z.png
Just to be clear the data
that ggplot
is consuming after piping it via gather
looks like this:
date key value
2002-01-01 var0 100.00000
2002-02-01 var0 115.16388
...
2007-11-01 var1 114.86302
2007-12-01 var1 119.30996
Using your data:
test_data <- data.frame(
var0 = 100 + c(0, cumsum(runif(49, -20, 20))),
var1 = 150 + c(0, cumsum(runif(49, -10, 10))),
Dates = seq.Date(as.Date("2002-01-01"), by="1 month", length.out=100))
I create a stacked version which is what ggplot()
would like to work with:
stacked <- with(test_data,
data.frame(value = c(var0, var1),
variable = factor(rep(c("Var0","Var1"),
each = NROW(test_data))),
Dates = rep(Dates, 2)))
In this case producing stacked
was quite easy as we only had to do a couple of manipulations, but reshape()
and the reshape
and reshape2
might be useful if you have a more complex real data set to manipulate.
Once the data are in this stacked form, it only requires a simple ggplot()
call to produce the plot you wanted with all the extras (one reason why higher-level plotting packages like lattice
and ggplot2
are so useful):
require(ggplot2)
p <- ggplot(stacked, aes(Dates, value, colour = variable))
p + geom_line()
I'll leave it to you to tidy up the axis labels, legend title etc.
HTH
rep()
, so we really are only getting 3 cols in stacked
. I'll edit the code to make the indent clearer.
melt()
is well taken, and I note that the reshape[2] package would be useful here. I'm not that familiar with reshape2 and for such a simple manipulation doing it by hand is more complex than a call to melt()
, it was less effort as I didn't need to read how to use melt()
. And rcs sneaked in with his answer whilst I was producing mine; when I started the reply there had been no answers. more than one way to skin a cat - as they say! ;-)
I am also new to R but trying to understand how ggplot works I think I get another way to do it. I just share probably not as a complete perfect solution but to add some different points of view.
I know ggplot is made to work with dataframes better but maybe it can be also sometimes useful to know that you can directly plot two vectors without using a dataframe.
Loading data. Original date vector length is 100 while var0 and var1 have length 50 so I only plot the available data (first 50 dates).
var0 <- 100 + c(0, cumsum(runif(49, -20, 20)))
var1 <- 150 + c(0, cumsum(runif(49, -10, 10)))
date <- seq(as.Date("2002-01-01"), by="1 month", length.out=50)
Plotting
ggplot() + geom_line(aes(x=date,y=var0),color='red') +
geom_line(aes(x=date,y=var1),color='blue') +
ylab('Values')+xlab('date')
https://i.stack.imgur.com/M1Dhv.png
However I was not able to add a correct legend using this format. Does anyone know how?
ggplot() + geom_line(aes(x=date,y=var0, group=1, colour = 'red')) + geom_line(aes(x=date,y=var1, group = 2, colour = 'blue')) + ylab('Values')+xlab('date')
Success story sharing
colour=
as the variable name.colour='var_names'
as specified by hadley works fine. but @DaveX - would be more specific if one wants to choose specific colors rather than automatically selected colours by the function.