# hist.data.frame

##### Histograms for Variables in a Data Frame

This functions tries to compute the maximum number of histograms that will fit on one page, then it draws a matrix of histograms. If there are more qualifying variables than will fit on a page, the function waits for a mouse click before drawing the next page.

- Keywords
- hplot, distribution, dplot

##### Usage

```
# S3 method for data.frame
hist(x, n.unique = 3, nclass = "compute",
na.big = FALSE, rugs = FALSE, freq=TRUE, mtitl = FALSE, ...)
```

##### Arguments

- x
a data frame

- n.unique
minimum number of unique values a variable must have before a histogram is drawn

- nclass
number of bins. Default is max(2,trunc(min(n/10,25*log(n,10))/2)), where n is the number of non-missing values for a variable.

- na.big
set to

`TRUE`

to draw the number of missing values on the top of the histogram in addition to in a subtitle. In the subtitle, n is the number of non-missing values and m is the number of missing values- rugs
set to

`TRUE`

to add rug plots at the top of each histogram- freq
see

`hist`

. Default is to show frequencies.- mtitl
set to a character string to set aside extra outside top margin and to use the string for an overall title

- …
arguments passed to

`scat1d`

##### Value

the number of pages drawn

##### See Also

##### Examples

```
# NOT RUN {
d <- data.frame(a=runif(200), b=rnorm(200),
w=factor(sample(c('green','red','blue'), 200, TRUE)))
hist.data.frame(d) # in R, just say hist(d)
# }
```

*Documentation reproduced from package Hmisc, version 4.0-3, License: GPL (>= 2)*