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Helper for creating an histogram

Usage

bb_histogram(
  bb,
  data,
  mapping = NULL,
  stacked = FALSE,
  fill = FALSE,
  bins = 30,
  binwidth = NULL,
  ...
)

Arguments

bb

A billboard htmlwidget object.

data

A data.frame or a vector, the first column will be used to calculate density if x is NULL.

mapping

Mapping of variables on the chart, see bbaes.

stacked

Logical, create a stacked histogram.

fill

Logical, create a stacked percentage histogram.

bins

Number of bins. Overridden by binwidth. Defaults to 30.

binwidth

The width of the bins. See geom_histogram

...

Not used.

Value

A billboard htmlwidget object.

See also

Examples


data("diamonds", package = "ggplot2")

# one variable
billboarder() %>% 
  bb_histogram(data = diamonds, x = "price")
# with mapping billboarder() %>% bb_histogram(diamonds, bbaes(price))
# equivalent to billboarder() %>% bb_histogram(data = diamonds$price)
# prettier with 'binwidth' # (but you need to know your data) billboarder() %>% bb_histogram(data = diamonds, x = "price", binwidth = 500) %>% bb_colors_manual()
# with a grouping variable billboarder() %>% bb_histogram(data = diamonds, x = "price", group = "cut", binwidth = 500)
# and with mapping billboarder() %>% bb_histogram(diamonds, bbaes(price, group = cut), binwidth = 500)
# stacked histogram billboarder() %>% bb_histogram(diamonds, bbaes(price, group = cut), stacked = TRUE, binwidth = 500)
# another example dat <- data.frame( sample = c(rnorm(n = 500, mean = 1), rnorm(n = 500, mean = 2)), group = rep(c("A", "B"), each = 500) ) billboarder() %>% bb_histogram(data = dat, x = "sample", binwidth = 0.25)
samples_mean <- tapply(dat$sample, dat$group, mean) billboarder() %>% bb_histogram(data = dat, x = "sample", group = "group", binwidth = 0.25) %>% bb_x_grid( lines = list( list(value = unname(samples_mean['A']), text = "mean of sample A"), list(value = unname(samples_mean['B']), text = "mean of sample B") ) )