% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/gghistogram.R
\name{gghistogram}
\alias{gghistogram}
\title{Histogram plot}
\usage{
gghistogram(
  data,
  x,
  y = "count",
  combine = FALSE,
  merge = FALSE,
  weight = NULL,
  color = "black",
  fill = NA,
  palette = NULL,
  size = NULL,
  linetype = "solid",
  alpha = 0.5,
  bins = NULL,
  binwidth = NULL,
  title = NULL,
  xlab = NULL,
  ylab = NULL,
  facet.by = NULL,
  panel.labs = NULL,
  short.panel.labs = TRUE,
  add = c("none", "mean", "median"),
  add.params = list(linetype = "dashed"),
  rug = FALSE,
  add_density = FALSE,
  label = NULL,
  font.label = list(size = 11, color = "black"),
  label.select = NULL,
  repel = FALSE,
  label.rectangle = FALSE,
  position = position_identity(),
  ggtheme = theme_pubr(),
  ...
)
}
\arguments{
\item{data}{a data frame}

\item{x}{variable to be drawn.}

\item{y}{one of "density" or "count".}

\item{combine}{logical value. Default is FALSE. Used only when y is a vector
containing multiple variables to plot. If TRUE, create a multi-panel plot by
combining the plot of y variables.}

\item{merge}{logical or character value. Default is FALSE. Used only when y is
a vector containing multiple variables to plot. If TRUE, merge multiple y
variables in the same plotting area. Allowed values include also "asis"
(TRUE) and "flip". If merge = "flip", then y variables are used as x tick
labels and the x variable is used as grouping variable.}

\item{weight}{a variable name available in the input data for creating a weighted histogram.}

\item{color, fill}{histogram line color and fill color.}

\item{palette}{the color palette to be used for coloring or filling by groups.
Allowed values include "grey" for grey color palettes; brewer palettes e.g.
"RdBu", "Blues", ...; or custom color palette e.g. c("blue", "red"); and
scientific journal palettes from ggsci R package, e.g.: "npg", "aaas",
"lancet", "jco", "ucscgb", "uchicago", "simpsons" and "rickandmorty".}

\item{size}{Numeric value (e.g.: size = 1). change the size of points and
outlines.}

\item{linetype}{line type. See \code{\link{show_line_types}}.}

\item{alpha}{numeric value specifying fill color transparency. Value should
be in [0, 1], where 0 is full transparency and 1 is no transparency.}

\item{bins}{Number of bins. Defaults to 30.}

\item{binwidth}{numeric value specifying bin width. use value between 0 and 1
when you have a strong dense dotplot. For example binwidth = 0.2.}

\item{title}{plot main title.}

\item{xlab}{character vector specifying x axis labels. Use xlab = FALSE to
hide xlab.}

\item{ylab}{character vector specifying y axis labels. Use ylab = FALSE to
hide ylab.}

\item{facet.by}{character vector, of length 1 or 2, specifying grouping
variables for faceting the plot into multiple panels. Should be in the data.}

\item{panel.labs}{a list of one or two character vectors to modify facet panel
labels. For example, panel.labs = list(sex = c("Male", "Female")) specifies
the labels for the "sex" variable. For two grouping variables, you can use
for example panel.labs = list(sex = c("Male", "Female"), rx = c("Obs",
"Lev", "Lev2") ).}

\item{short.panel.labs}{logical value. Default is TRUE. If TRUE, create short
labels for panels by omitting variable names; in other words panels will be
labelled only by variable grouping levels.}

\item{add}{allowed values are one of "mean" or "median" (for adding mean or
median line, respectively).}

\item{add.params}{parameters (color, size, linetype) for the argument 'add';
e.g.: add.params = list(color = "red").}

\item{rug}{logical value. If TRUE, add marginal rug.}

\item{add_density}{logical value. If TRUE, add density curves.}

\item{label}{the name of the column containing point labels. Can be also a
character vector with length = nrow(data).}

\item{font.label}{a list which can contain the combination of the following
elements: the size (e.g.: 14), the style (e.g.: "plain", "bold", "italic",
"bold.italic") and the color (e.g.: "red") of labels. For example font.label
= list(size = 14, face = "bold", color ="red"). To specify only the size and
the style, use font.label = list(size = 14, face = "plain").}

\item{label.select}{can be of two formats: \itemize{ \item a character vector
specifying some labels to show. \item a list containing one or the
combination of the following components: \itemize{ \item \code{top.up} and
\code{top.down}: to display the labels  of the top up/down points. For
example, \code{label.select = list(top.up = 10, top.down = 4)}. \item
\code{criteria}: to filter, for example, by x and y variabes values, use
this: \code{label.select = list(criteria = "`y` > 2 & `y` < 5 & `x` \%in\%
c('A', 'B')")}. } }}

\item{repel}{a logical value, whether to use ggrepel to avoid overplotting
text labels or not.}

\item{label.rectangle}{logical value. If TRUE, add rectangle underneath the
text, making it easier to read.}

\item{position}{Position adjustment, either as a string, or the result of a
call to a position adjustment function. Allowed values include "identity",
"stack", "dodge".}

\item{ggtheme}{function, ggplot2 theme name. Default value is theme_pubr().
Allowed values include ggplot2 official themes: theme_gray(), theme_bw(),
theme_minimal(), theme_classic(), theme_void(), ....}

\item{...}{other arguments to be passed to
\code{\link[ggplot2]{geom_histogram}} and \code{\link{ggpar}}.}
}
\description{
Create a histogram plot.
}
\details{
The plot can be easily customized using the function ggpar(). Read
  ?ggpar for changing: \itemize{ \item main title and axis labels: main,
  xlab, ylab \item axis limits: xlim, ylim (e.g.: ylim = c(0, 30)) \item axis
  scales: xscale, yscale (e.g.: yscale = "log2") \item color palettes:
  palette = "Dark2" or palette = c("gray", "blue", "red") \item legend title,
  labels and position: legend = "right" \item plot orientation : orientation
  = c("vertical", "horizontal", "reverse") }
}
\examples{
# Create some data format
set.seed(1234)
wdata = data.frame(
   sex = factor(rep(c("F", "M"), each=200)),
   weight = c(rnorm(200, 55), rnorm(200, 58)))

head(wdata, 4)

# Basic density plot
# Add mean line and marginal rug
gghistogram(wdata, x = "weight", fill = "lightgray",
   add = "mean", rug = TRUE)

# Change outline colors by groups ("sex")
# Use custom color palette
gghistogram(wdata, x = "weight",
   add = "mean", rug = TRUE,
   color = "sex", palette = c("#00AFBB", "#E7B800"))

# Change outline and fill colors by groups ("sex")
# Use custom color palette
gghistogram(wdata, x = "weight",
   add = "mean", rug = TRUE,
   color = "sex", fill = "sex",
   palette = c("#00AFBB", "#E7B800"))



# Combine histogram and density plots
gghistogram(wdata, x = "weight",
   add = "mean", rug = TRUE,
   fill = "sex", palette = c("#00AFBB", "#E7B800"),
   add_density = TRUE)

# Weighted histogram
gghistogram(iris, x = "Sepal.Length", weight = "Petal.Length")
}
\seealso{
\code{\link{ggdensity}} and \code{\link{ggpar}}
}