Plot Group-wise Histograms

Usage

groupwise_histogram(
  data,
  group,
  trait,
  background.hist = TRUE,
  background.hist.alpha = 0.25,
  background.density = TRUE,
  background.density.alpha = 0.1,
  hist = TRUE,
  hist.border = TRUE,
  hist.position = c("identity", "stack"),
  hist.alpha = 0.8,
  bw.adjust = 0.5,
  density = TRUE,
  density.alpha = 0.1,
  normal.curve = TRUE,
  normal.curve.linetype = "solid",
  highlight.mean = TRUE,
  show.counts = TRUE,
  count.text.size = 3,
  subset = c("facet", "list", "none"),
  ncol = NULL,
  nrow = NULL
)

Arguments

data: The data as a data frame object. The data frame should possess columns specifying the group and trait.
group: Name of column specifying the group as a character string.
trait: Name of column specifying the trait as a character string.
background.hist: logical. If TRUE, the background data histogram is plotted. Default is TRUE.
background.hist.alpha: Alpha transparency for the background data histogram.
background.density: logical. If TRUE, the background data kernel density is plotted. Default is TRUE.
background.density.alpha: Alpha transparency for the background data kernel density.
hist: logical. If TRUE, the group-wise histogram is plotted. Default is TRUE.
hist.border: logical. If TRUE, histogram border is also plotted. Default is TRUE.
hist.position: Histogram position adjustment. Either "identity" or "stack".
hist.alpha: Alpha transparency for the group-wise histogram.
bw.adjust: Multiplicative bin width adjustment. Default is 0.5 which means use half of the default bandwidth.
density: logical. If TRUE, the group-wise kernel density is plotted. Default is TRUE.
density.alpha: Alpha transparency for the group-wise kernel density
normal.curve: logical. If TRUE, a normal curve is plotted. Default is TRUE.
normal.curve.linetype: Linetype for the normal curve. See aes_linetype_size_shape.
highlight.mean: logical. If TRUE, the mean value is highlighted as a vertical line. Default is TRUE.
show.counts: logical. If TRUE, group wise counts are plotted as a text annotation. Default is TRUE.
count.text.size: The size of the count text annotation.
subset: The method for subsetting the plots according to the argument "group". Either "facet" for getting an plot using faceting in ggplot2 or "list" for getting a list of plots.
ncol: Number of columns when subset = "facet".
nrow: Number of rows when subset = "facet".

Value

The group-wise histogram as a ggplot2 plot grob or as a list of ggplot2 plot grobs.

Examples

library(agridat)
library(ggplot2)
library(patchwork)

soydata <- australia.soybean
# soydata[soydata$loc == "Nambour", ]$lodging <- NA

clrs <- c("#B2182B", "#2166AC", "#009E53", "#E69F00")
clrs_dark <- colorspace::darken(clrs, amount = 0.2)

# Group-wise histogram ----
outg_hist <-
  groupwise_histogram(data = soydata, group = "loc", trait = "lodging",
                      background.hist = FALSE,
                      background.density = FALSE,
                      hist.alpha = 0.5,
                      density = FALSE,
                      subset = "none")
outg_hist


outg_hist +
  scale_fill_manual(values = clrs) +
  scale_colour_manual(values = clrs_dark)
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.


# Group-wise histogram - stacked ----
outg_hist_stack <-
  groupwise_histogram(data = soydata, group = "loc", trait = "lodging",
                      background.hist = FALSE,
                      background.density = FALSE,
                      hist.position = "stack",
                      density = FALSE,
                      normal.curve = FALSE,
                      subset = "none")
outg_hist_stack


outg_hist_stack +
  scale_fill_manual(values = clrs) +
  scale_colour_manual(values = clrs_dark)
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.


# Group-wise histogram with facet ----
outg_hist_facet <-
  groupwise_histogram(data = soydata, group = "loc", trait = "lodging",
                      background.hist = TRUE,
                      background.density = FALSE,
                      hist.alpha = 0.5,
                      density = FALSE,
                      subset = "facet")
outg_hist_facet


outg_hist_facet +
  scale_fill_manual(values = clrs) +
  scale_colour_manual(values = clrs_dark)
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.


# Group-wise histogram as list ----
outg_hist_list <-
  groupwise_histogram(data = soydata, group = "loc", trait = "lodging",
                      background.hist = TRUE,
                      background.density = FALSE,
                      hist.alpha = 0.5,
                      density = FALSE,
                      subset = "list")

wrap_plots(outg_hist_list, nrow = 2, guides = "collect")


outg_hist_list <-
  lapply(seq_along(outg_hist_list), function(i) {
    outg_hist_list[[i]] +
      scale_fill_manual(values = clrs[i]) +
      scale_colour_manual(values = clrs_dark[i])
  })
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.

wrap_plots(outg_hist_list, nrow = 2, guides = "collect")


# Group-wise density ----
outg_density <-
  groupwise_histogram(data = soydata, group = "loc", trait = "lodging",
                      background.hist = FALSE,
                      background.density = TRUE,
                      hist = FALSE,
                      density = TRUE,
                      normal.curve = FALSE,
                      subset = "none")
outg_density


outg_density +
  scale_fill_manual(values = clrs) +
  scale_colour_manual(values = clrs_dark)
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.


# Group-wise density with facet ----
outg_density_facet <-
  groupwise_histogram(data = soydata, group = "loc", trait = "lodging",
                      background.hist = FALSE,
                      background.density = TRUE,
                      hist = FALSE,
                      density = TRUE,
                      normal.curve = FALSE,
                      subset = "facet")
outg_density_facet


outg_density_facet +
  scale_fill_manual(values = clrs) +
  scale_colour_manual(values = clrs_dark)
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.


# Group-wise density as list ----
outg_density_list <-
  groupwise_histogram(data = soydata, group = "loc", trait = "lodging",
                      background.hist = FALSE,
                      background.density = TRUE,
                      hist = FALSE,
                      density = TRUE,
                      normal.curve = FALSE,
                      subset = "list")

wrap_plots(outg_density_list, nrow = 2, guides = "collect")


outg_density_list <-
  lapply(seq_along(outg_density_list), function(i) {
    outg_density_list[[i]] +
      scale_fill_manual(values = clrs[i]) +
      scale_colour_manual(values = clrs_dark[i])
  })
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.

wrap_plots(outg_density_list, nrow = 2, guides = "collect")


# Group-wise density + histogram ----
outg_density_hist <-
  groupwise_histogram(data = soydata, group = "loc", trait = "lodging",
                      background.hist = FALSE,
                      background.density = FALSE,
                      hist = TRUE,
                      hist.alpha = 0.3,
                      density = TRUE,
                      normal.curve = FALSE,
                      subset = "none")
outg_density_hist


outg_density_hist +
  scale_fill_manual(values = clrs) +
  scale_colour_manual(values = clrs_dark)
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.


# Group-wise density + histogram with facet ----
outg_density_hist_facet <-
  groupwise_histogram(data = soydata, group = "loc", trait = "lodging",
                      background.hist = TRUE,
                      background.density = FALSE,
                      hist = TRUE,
                      hist.alpha = 0.3,
                      density = TRUE,
                      normal.curve = FALSE,
                      subset = "facet")
outg_density_hist_facet


outg_density_hist_facet +
  scale_fill_manual(values = clrs) +
  scale_colour_manual(values = clrs_dark)
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.


# Group-wise density + histogram as list ----
outg_density_hist_list <-
  groupwise_histogram(data = soydata, group = "loc", trait = "lodging",
                      background.hist = TRUE,
                      background.density = FALSE,
                      hist = TRUE,
                      hist.alpha = 0.3,
                      density = TRUE,
                      normal.curve = FALSE,
                      subset = "list")

wrap_plots(outg_density_hist_list, nrow = 2, guides = "collect")


outg_density_hist_list <-
  lapply(seq_along(outg_density_hist_list), function(i) {
    outg_density_hist_list[[i]] +
      scale_fill_manual(values = clrs[i]) +
      scale_colour_manual(values = clrs_dark[i])
  })
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.

wrap_plots(outg_density_hist_list, nrow = 2, guides = "collect")