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.

Examples


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

# one variable
billboarder() %>% 
  bb_histogram(data = diamonds, x = "price")
#> Warning: `aes_string()` was deprecated in ggplot2 3.0.0.
#> ℹ Please use tidy evaluation idioms with `aes()`.
#> ℹ See also `vignette("ggplot2-in-packages")` for more information.
#> ℹ The deprecated feature was likely used in the billboarder package.
#>   Please report the issue at <https://github.com/dreamRs/billboarder/issues>.

  
  


# 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")
    )
  )