echarts4r

ECharts 4: powerful interactive visualisations in R.

Get Started Gallery Changelog Shiny demo

Installation

Version 0.1.1 sees great performance and security improvements, upgrading is highly recommended.

You can install echarts4r with devtools or remotes from Github, Bitbucket or Coding. The latter is specifically for China, as the package is large download from Mainland can be long from outside the firewall.

# install.packages("devtools")
devtools::install_github("JohnCoene/echarts4r") # github

# install.packages("remotes")
remotes::install_bitbucket("JohnCoene/echarts4r") # bitbucket

# install.packages("remotes")
remotes::install_git("https://git.coding.net/JohnCoene/echarts4r.git") # coding.net

Features

Some of the features:

• 33 chart types
• Animations
• Brush & sliders
• WebGL support
• Plugins included
• Shiny proxies
• themes

Group new

echarts4r now understands dplyr::group_by in order to better work with tidy data concept; the package now works much better with *long* datasets. See get started guide or the various examples in the functions' documentation or the gallery

# one serie per group
 iris %>% 
   group_by(Species) %>% 
   e_charts(Sepal.Length) %>% 
   e_line(Sepal.Width)

Examples

Some of what you can do with echarts4r, see the guide for more.

library(echarts4r)

# with negative
USArrests %>% 
  dplyr::mutate(
    State = row.names(.),
    Rape = -Rape
  ) %>% 
  e_charts(State) %>% 
  e_area(Murder) %>%
  e_bar(Rape, name = "Sick basterd", x.index = 1) %>% # second y axis 
  e_mark_line("Sick basterd", data = list(type = "average")) %>% 
  e_mark_point("Murder", data = list(type = "max")) %>% 
  e_tooltip(trigger = "axis")

# 3D bars
url <- paste0("https://ecomfe.github.io/echarts-examples/",
              "public/data-gl/asset/data/population.json")
data <- jsonlite::fromJSON(url)
data <- as.data.frame(data)
names(data) <- c("lon", "lat", "value")

data %>% 
  e_charts(lon) %>% 
  e_geo_3d() %>% 
  e_bar_3d(lat, value, coord.system = "geo3D") %>% 
  e_visual_map()