# histboxp

0th

Percentile

##### 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.

Keywords
hplot
##### Usage
histboxp(p = plotly::plot_ly(height=height), x, group = NULL, xlab=NULL, gmd=TRUE, sd=FALSE, bins = 100)
##### Arguments
p
plotly graphics object if already begun
x
a numeric vector
group
a discrete grouping variable. If omitted, 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
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.
##### Value

plotly object

histSpike, plot.describe, scat1d

• histboxp
##### 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)
# ## End(Not run)

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

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