Here is an even simpler solution using base graphics and alpha-blending (which does not work on all graphics devices):

```
set.seed(42)
p1 <- hist(rnorm(500,4)) # centered at 4
p2 <- hist(rnorm(500,6)) # centered at 6
plot( p1, col=rgb(0,0,1,1/4), xlim=c(0,10)) # first histogram
plot( p2, col=rgb(1,0,0,1/4), xlim=c(0,10), add=T) # second
```

The key is that the colours are semi-transparent.

**Edit, more than two years later**: As this just got an upvote, I figure I may as well add a visual of what the code produces as alpha-blending is so darn useful:

There are a number of ways to do what you want. To add to what @inalis and @Navi already said, you can use the `bbox_to_anchor`

keyword argument to place the legend partially outside the axes and/or decrease the font size.

Before you consider decreasing the font size (which can make things awfully hard to read), try playing around with placing the legend in different places:

So, let's start with a generic example:

```
import matplotlib.pyplot as plt
import numpy as np
x = np.arange(10)
fig = plt.figure()
ax = plt.subplot(111)
for i in xrange(5):
ax.plot(x, i * x, label='$y = %ix$' % i)
ax.legend()
plt.show()
```

If we do the same thing, but use the `bbox_to_anchor`

keyword argument we can shift the legend slightly outside the axes boundaries:

```
import matplotlib.pyplot as plt
import numpy as np
x = np.arange(10)
fig = plt.figure()
ax = plt.subplot(111)
for i in xrange(5):
ax.plot(x, i * x, label='$y = %ix$' % i)
ax.legend(bbox_to_anchor=(1.1, 1.05))
plt.show()
```

Similarly, make the legend more horizontal and/or put it at the top of the figure (I'm also turning on rounded corners and a simple drop shadow):

```
import matplotlib.pyplot as plt
import numpy as np
x = np.arange(10)
fig = plt.figure()
ax = plt.subplot(111)
for i in xrange(5):
line, = ax.plot(x, i * x, label='$y = %ix$'%i)
ax.legend(loc='upper center', bbox_to_anchor=(0.5, 1.05),
ncol=3, fancybox=True, shadow=True)
plt.show()
```

Alternatively, shrink the current plot's width, and put the legend entirely outside the axis of the figure (note: if you use `tight_layout()`

, then leave out `ax.set_position()`

:

```
import matplotlib.pyplot as plt
import numpy as np
x = np.arange(10)
fig = plt.figure()
ax = plt.subplot(111)
for i in xrange(5):
ax.plot(x, i * x, label='$y = %ix$'%i)
# Shrink current axis by 20%
box = ax.get_position()
ax.set_position([box.x0, box.y0, box.width * 0.8, box.height])
# Put a legend to the right of the current axis
ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))
plt.show()
```

And in a similar manner, shrink the plot vertically, and put a horizontal legend at the bottom:

```
import matplotlib.pyplot as plt
import numpy as np
x = np.arange(10)
fig = plt.figure()
ax = plt.subplot(111)
for i in xrange(5):
line, = ax.plot(x, i * x, label='$y = %ix$'%i)
# Shrink current axis's height by 10% on the bottom
box = ax.get_position()
ax.set_position([box.x0, box.y0 + box.height * 0.1,
box.width, box.height * 0.9])
# Put a legend below current axis
ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.05),
fancybox=True, shadow=True, ncol=5)
plt.show()
```

Have a look at the matplotlib legend guide. You might also take a look at `plt.figlegend()`

.

## Best Solution

If I understood correctly, both hists should go into the same subplot. So it should be

You can also pass the pandas plot method an axis object, so if you want both kde's in another plot do:

To get everything into a single plot you need two different y-scales since kde is density and histogram is frequency. For that you use the

`axes.twinx()`

command.