# Plot two graphs in same plot in R

## Plot two graphs in same plot in R

### Question

I would like to plot y1 and y2 in the same plot.

```
x <- seq(-2, 2, 0.05)
y1 <- pnorm(x)
y2 <- pnorm(x, 1, 1)
plot(x, y1, type = "l", col = "red")
plot(x, y2, type = "l", col = "green")
```

But when I do it like this, they are not plotted in the same plot together.

In Matlab one can do `hold on`

, but does anyone know how to do this in R?

### Accepted Answer

`lines()`

or `points()`

will add to the existing graph, but will not create a new window. So you'd need to do

```
plot(x,y1,type="l",col="red")
lines(x,y2,col="green")
```

Read more... Read less...

You can also use `par`

and plot on the same graph but different axis. Something as follows:

```
plot( x, y1, type="l", col="red" )
par(new=TRUE)
plot( x, y2, type="l", col="green" )
```

If you read in detail about `par`

in `R`

, you will be able to generate really interesting graphs. Another book to look at is Paul Murrel's R Graphics.

When constructing multilayer plots one should consider `ggplot`

package. The idea is to create a graphical object with basic aesthetics and enhance it incrementally.

`ggplot`

style requires data to be packed in `data.frame`

.

```
# Data generation
x <- seq(-2, 2, 0.05)
y1 <- pnorm(x)
y2 <- pnorm(x,1,1)
df <- data.frame(x,y1,y2)
```

Basic solution:

```
require(ggplot2)
ggplot(df, aes(x)) + # basic graphical object
geom_line(aes(y=y1), colour="red") + # first layer
geom_line(aes(y=y2), colour="green") # second layer
```

Here `+ operator`

is used to add extra layers to basic object.

With `ggplot`

you have access to graphical object on every stage of plotting. Say, usual step-by-step setup can look like this:

```
g <- ggplot(df, aes(x))
g <- g + geom_line(aes(y=y1), colour="red")
g <- g + geom_line(aes(y=y2), colour="green")
g
```

`g`

produces the plot, and you can see it at every stage (well, after creation of at least one layer). Further enchantments of the plot are also made with created object. For example, we can add labels for axises:

```
g <- g + ylab("Y") + xlab("X")
g
```

Final `g`

looks like:

**UPDATE (2013-11-08):**

As pointed out in comments, `ggplot`

's philosophy suggests using data in long format.
You can refer to this answer in order to see the corresponding code.

I think that the answer you are looking for is:

```
plot(first thing to plot)
plot(second thing to plot,add=TRUE)
```

Use the `matplot`

function:

```
matplot(x, cbind(y1,y2),type="l",col=c("red","green"),lty=c(1,1))
```

use this if `y1`

and `y2`

are evaluated at the same `x`

points. It scales the Y-axis to fit whichever is bigger (`y1`

or `y2`

), unlike some of the other answers here that will clip `y2`

if it gets bigger than `y1`

(ggplot solutions mostly are okay with this).

Alternatively, and if the two lines don't have the same x-coordinates, set the axis limits on the first plot and add:

```
x1 <- seq(-2, 2, 0.05)
x2 <- seq(-3, 3, 0.05)
y1 <- pnorm(x1)
y2 <- pnorm(x2,1,1)
plot(x1,y1,ylim=range(c(y1,y2)),xlim=range(c(x1,x2)), type="l",col="red")
lines(x2,y2,col="green")
```

Am astonished this Q is 4 years old and nobody has mentioned `matplot`

or `x/ylim`

...

**tl;dr:** You want to use `curve`

(with `add=TRUE`

) or `lines`

.

I disagree with `par(new=TRUE)`

because that will double-print tick-marks and axis labels. Eg

*The output of plot(sin); par(new=T); plot( function(x) x**2 ).*

Look how messed up the vertical axis labels are! Since the ranges are different you would need to set `ylim=c(lowest point between the two functions, highest point between the two functions)`

, which is less easy than what I'm about to show you---and *way* less easy if you want to add not just two curves, but many.

What always confused me about plotting is the difference between `curve`

and `lines`

. *(If you can't remember that these are the names of the two important plotting commands, just sing it.)*

### Here's the big difference between `curve`

and `lines`

.

`curve`

will plot a function, like `curve(sin)`

. `lines`

plots points with x and y values, like: `lines( x=0:10, y=sin(0:10) )`

.

And here's a minor difference: `curve`

needs to be called with `add=TRUE`

for what you're trying to do, while `lines`

already assumes you're adding to an existing plot.

*Here's the result of calling plot(0:2); curve(sin).*

Behind the scenes, check out `methods(plot)`

. And check `body( plot.function )[[5]]`

. When you call `plot(sin)`

R figures out that `sin`

is a function (not y values) and uses the `plot.function`

method, which ends up calling `curve`

. So `curve`

is the tool meant to handle functions.