Skip to contents

Highcharter

Joshua Kunst

2022-11-23

Source: vignettes/highcharter.Rmd
highcharter.Rmd

Highcharts

let us start start with a simple example using hchart function.

library(highcharter)

# install.packages("palmerpenguins")
data(penguins, package = "palmerpenguins") 

hchart(
  penguins,
  "scatter",
  hcaes(x = flipper_length_mm, y = bill_length_mm, group = species)
)

Among its features {highcharter} can chart various objects depending of its class with the generic hchart function. In the next example x is numeric:

x <- c(rnorm(10000), rnorm(1000, 4, 0.5))

hchart(x, name = "data", color = "#17b8b6")

One of the nicest class which hchart can plot is the forecast class from the {forecast} package.

library(forecast)

airforecast <- forecast(auto.arima(AirPassengers), level = 95)

hchart(airforecast)

See more examples of hchart in vignette("hchart").

Highstock

With {highcharter} you can use the highstock library which include sophisticated navigation options like:

  • Small navigator series
  • Preset date ranges
  • Date picker
  • Scrolling and panning.

It is easy make candlesticks or ohlc charts using time series data. For example, using data from {quantmod} package:

library(quantmod)

x <- getSymbols("GOOG", auto.assign = FALSE)
y <- getSymbols("AMZN", auto.assign = FALSE)

highchart(type = "stock") |> 
  hc_add_series(x) |> 
  hc_add_series(y, type = "ohlc")

Highmaps

We can chart maps elements and choropleth using the highmaps and build interactive maps to display data linked to geographic objects.

data(GNI2014, package = "treemap")

hcmap(
  "custom/world-robinson-lowres",
  data = GNI2014,
  name = "Gross national income per capita",
  value = "GNI",
  borderWidth = 0,
  nullColor = "#d3d3d3",
  joinBy = c("iso-a3", "iso3")
) |>
  hc_colorAxis(
    stops = color_stops(colors = viridisLite::inferno(10, begin = 0.1)),
    type = "logarithmic"
  )

What now?

Since you know the basics now it could be interesting: