# Histogram and density plot

## Problem

You want to make a histogram or density plot.

## Solution

Some sample data: these two vectors contain 200 data points each:

```
set.seed(1234)
rating <- rnorm(200)
head(rating)
#> [1] -1.2070657 0.2774292 1.0844412 -2.3456977 0.4291247 0.5060559
rating2 <- rnorm(200, mean=.8)
head(rating2)
#> [1] 1.2852268 1.4967688 0.9855139 1.5007335 1.1116810 1.5604624
```

When plotting multiple groups of data, some graphing routines require a data frame with one column for the grouping variable and one for the measure variable.

```
# Make a column to indicate which group each value is in
cond <- factor( rep(c("A","B"), each=200) )
data <- data.frame(cond, rating = c(rating,rating2))
head(data)
#> cond rating
#> 1 A -1.2070657
#> 2 A 0.2774292
#> 3 A 1.0844412
#> 4 A -2.3456977
#> 5 A 0.4291247
#> 6 A 0.5060559
```

```
# Histogram
hist(rating)
# Use 8 bins (this is only approximate - it places boundaries on nice round numbers)
# Make it light blue #CCCCFF
# Instead of showing count, make area sum to 1, (freq=FALSE)
hist(rating, breaks=8, col="#CCCCFF", freq=FALSE)
# Put breaks at every 0.6
boundaries <- seq(-3, 3.6, by=.6)
boundaries
#> [1] -3.0 -2.4 -1.8 -1.2 -0.6 0.0 0.6 1.2 1.8 2.4 3.0 3.6
hist(rating, breaks=boundaries)
# Kernel density plot
plot(density(rating))
```

Multiple groups with kernel density plots.

This code is from: http://onertipaday.blogspot.com/2007/09/plotting-two-or-more-overlapping.html

```
plot.multi.dens <- function(s)
{
junk.x = NULL
junk.y = NULL
for(i in 1:length(s)) {
junk.x = c(junk.x, density(s[[i]])$x)
junk.y = c(junk.y, density(s[[i]])$y)
}
xr <- range(junk.x)
yr <- range(junk.y)
plot(density(s[[1]]), xlim = xr, ylim = yr, main = "")
for(i in 1:length(s)) {
lines(density(s[[i]]), xlim = xr, ylim = yr, col = i)
}
}
# the input of the following function MUST be a numeric list
plot.multi.dens( list(rating, rating2))
```

The `sm`

package also includes a way of doing multiple density plots. The data must be in a data frame.

```
library(sm)
sm.density.compare(data$rating, data$cond)
# Add a legend (the color numbers start from 2 and go up)
legend("topright", levels(data$cond), fill=2+(0:nlevels(data$cond)))
```