This a generic function, this means you can chart various R like numeric, histograms, character, factor, ts on the fly. The resulting chart is a highchart object so you can keep modifying with the implemented API.
This function works like qplot
: You pass the data, choose the type of chart and then define the aesthetics for each variable.
library(highcharter) library(dplyr) # remotes::install_github("allisonhorst/palmerpenguins") data(penguins, package = "palmerpenguins") data(diamonds, economics_long, package = "ggplot2") hchart(penguins, "scatter", hcaes(x = body_mass_g, y = flipper_length_mm , group = species))
## Rows: 5
## Columns: 3
## $ species <fct> Adelie, Adelie, Adelie, Chinstrap, Gentoo
## $ island <fct> Biscoe, Dream, Torgersen, Dream, Biscoe
## $ n <int> 44, 56, 52, 68, 124
Check automatically if the x column is date class:
x <- diamonds$price hchart(x)
x <- diamonds$cut hchart(x, type = "column")
library(igraph) N <- 40 net <- sample_gnp(N, p = 2 / N) wc <- cluster_walktrap(net) V(net)$label <- seq(N) V(net)$name <- paste("I'm #", seq(N)) V(net)$page_rank <- round(page.rank(net)$vector, 2) V(net)$betweenness <- round(betweenness(net), 2) V(net)$degree <- degree(net) V(net)$size <- V(net)$degree V(net)$comm <- membership(wc) V(net)$color <- colorize(membership(wc)) hchart(net, layout = layout_with_fr)
The highstock extension is used to chart xts
and xts ohlc
classes from the quantmod package.
y <- getSymbols("SPY", auto.assign = FALSE) hchart(y)
data(volcano) hchart(volcano) %>% # changing default color hc_colorAxis( stops = color_stops(colors = c("#000004FF", "#56106EFF", "#BB3754FF", "#F98C0AFF", "#FCFFA4FF")) )