# histboxp

##### Use plotly to Draw Stratified Spike Histogram and Box Plot Statistics

Uses `plotly`

to draw horizontal spike histograms stratified by
`group`

, plus the mean (solid dot) and vertical bars for these
quantiles: 0.05 (red, short), 0.25 (blue, medium), 0.50 (black, long),
0.75 (blue, medium), and 0.95 (red, short). The robust dispersion measure
Gini's mean difference and the SD may optionally be added. These are
shown as horizontal lines starting at the minimum value of `x`

having a length equal to the mean difference or SD. Even when Gini's
and SD are computed, they are not drawn unless the user clicks on their
legend entry.

Spike histograms have the advantage of effectively showing the raw data for both small and huge datasets, and unlike box plots allow multi-modality to be easily seen.

`histboxpM`

plots multiple histograms stacked vertically, for
variables in a data frame having a common `group`

variable (if any)
and combined using `plotly::subplot`

.

`dhistboxp`

is like `histboxp`

but no `plotly`

graphics
are actually drawn. Instead, a data frame suitable for use with
`plotlyM`

is returned. For `dhistboxp`

an additional level of
stratification `strata`

is implemented. `group`

causes a
different result here to produce back-to-back histograms (in the case of
two groups) for each level of `strata`

.

- Keywords
- hplot

##### Usage

```
histboxp(p = plotly::plot_ly(height=height), x, group = NULL,
xlab=NULL, gmd=TRUE, sd=FALSE, bins = 100, wmax=190, mult=7,
connect=TRUE, showlegend=TRUE)
```dhistboxp(x, group = NULL, strata=NULL, xlab=NULL,
gmd=FALSE, sd=FALSE, bins = 100, nmin=5, ff1=1, ff2=1)

histboxpM(p=plotly::plot_ly(height=height), x, group=NULL,
gmd=TRUE, sd=FALSE, nrows=NULL, ncols=NULL, ...)

##### Arguments

- p
`plotly`

graphics object if already begun- x
a numeric vector, or for

`histboxpM`

a numeric vector or a data frame of numeric vectors, hopefully with`label`

and`units`

attributes- group
a discrete grouping variable. If omitted, defaults to a vector of ones

- strata
a discrete numeric stratification variable. Values are also used to space out different spike histograms. Defaults to a vector of ones.

- xlab
x-axis label, defaults to labelled version include units of measurement if any

- gmd
set to

`FALSE`

to not compute Gini's mean difference- sd
set to

`TRUE`

to compute the SD- nrows
number of rows for layout of multiple plots

- ncols
number of columns for layout of multiple plots. At most one of

`nrows,ncols`

should be specified.- bins
number of equal-width bins to use for spike histogram. If the number of distinct values of

`x`

is less than`bins`

, the actual values of`x`

are used.- nmin
minimum number of non-missing observations for a group-stratum combination before the spike histogram and quantiles are drawn

- ff1,ff2
fudge factors for position and bar length for spike histograms

- wmax,mult
tweaks for margin to allocate

- connect
set to

`FALSE`

to suppress lines connecting quantiles- showlegend
used if producing multiple plots to be combined with

`subplot`

; set to`FALSE`

for all but one plot- …
other arguments for

`histboxpM`

that are passed to`histboxp`

##### Value

a `plotly`

object. For `dhistboxp`

a data frame as
expected by `plotlyM`

##### See Also

##### Examples

```
# NOT RUN {
dist <- c(rep(1, 500), rep(2, 250), rep(3, 600))
Distribution <- factor(dist, 1 : 3, c('Unimodal', 'Bimodal', 'Trimodal'))
x <- c(rnorm(500, 6, 1),
rnorm(200, 3, .7), rnorm(50, 7, .4),
rnorm(200, 2, .7), rnorm(300, 5.5, .4), rnorm(100, 8, .4))
histboxp(x=x, group=Distribution, sd=TRUE)
X <- data.frame(x, x2=runif(length(x)))
histboxpM(x=X, group=Distribution, ncols=2) # separate plots
# }
```

*Documentation reproduced from package Hmisc, version 4.3-1, License: GPL (>= 2)*