Title:	Create Interactive Graphs with 'Echarts JavaScript' Version 5
Date:	2023-06-08
Version:	0.4.5
Description:	Easily create interactive charts by leveraging the 'Echarts Javascript' library which includes 36 chart types, themes, 'Shiny' proxies and animations.
License:	Apache License (≥ 2.0)
Encoding:	UTF-8
Imports:	htmlwidgets, dplyr (≥ 0.7.0), purrr, countrycode, broom, shiny, scales, corrplot, htmltools, jsonlite, rstudioapi
Suggests:	tidyr, testthat, knitr, rmarkdown, covr, data.tree, leaflet, tibble
Depends:	R (≥ 4.1.0)
RoxygenNote:	7.2.3
URL:	https://echarts4r.john-coene.com/, https://github.com/JohnCoene/echarts4r
BugReports:	https://github.com/JohnCoene/echarts4r/issues/
NeedsCompilation:	no
Packaged:	2023-06-16 14:02:03 UTC; david
Author:	John Coene [aut, cph], David Munoz Tord [cre, ctb], Wei Su [ctb], Helgasoft [ctb], Xianying Tan [ctb], Robin Cura [ctb], Mathida Chuk [ctb], Robert Koetsier [ctb], Jelle Geertsma [ctb]
Maintainer:	David Munoz Tord <david.munoztord@mailbox.org>
Repository:	CRAN
Date/Publication:	2023-06-16 23:30:02 UTC

Angle axis

Description

Customise angle axis.

Usage

e_angle_axis(e, serie, show = TRUE, ...)

e_angle_axis_(e, serie = NULL, show = TRUE, ...)

Arguments

See Also

Additional arguments

Examples

df <- data.frame(x = 1:100, y = seq(1, 200, by = 2))

df |>
  e_charts(x) |>
  e_polar(FALSE) |>
  e_angle_axis(FALSE) |>
  e_radius_axis(FALSE) |>
  e_line(y, coord.system = "polar", smooth = TRUE) |>
  e_legend(show = FALSE)

df <- data.frame(x = LETTERS[1:5], y = runif(5))

df |>
  e_charts(x) |>
  e_polar() |>
  e_angle_axis(x) |>
  e_radius_axis() |>
  e_line(y, coord.system = "polar", smooth = TRUE)

Confidence bands

Description

Add confidence bands

Usage

e_band(
  e,
  min,
  max,
  stack = "confidence-band",
  symbol = c("none", "none"),
  areaStyle = list(list(color = "rgba(0,0,0,0)"), list()),
  legend = list(FALSE, FALSE),
  ...
)

e_band_(
  e,
  min,
  max,
  stack = "confidence-band",
  symbol = c("none", "none"),
  areaStyle = list(list(color = "rgba(0,0,0,0)"), list()),
  legend = list(FALSE, FALSE),
  ...
)

Arguments

Examples

df <- data.frame(
  x = 1:10,
  y = runif(10, 5, 10)
) |>
  dplyr::mutate(
    lwr = y - runif(10, 1, 3),
    upr = y + runif(10, 2, 4)
  )

df |>
  e_charts(x) |>
  e_line(y) |>
  e_band(lwr, upr)

Area bands

Description

Add area bands

Usage

e_band2(e, lower, upper, ...)

e_band2_(
  e,
  lower,
  upper,
  name = NULL,
  legend = TRUE,
  y_index = 0,
  x_index = 0,
  coord_system = "cartesian2d",
  itemStyle = list(borderWidth = 0.5),
  ...
)

Arguments

Examples

data(EuStockMarkets)
as.data.frame(EuStockMarkets) |>
  dplyr::slice_head(n = 200) |>
  dplyr::mutate(day = 1:dplyr::n()) |>
  e_charts(day) |>
  e_line(CAC, symbol = "none") |>
  e_band2(DAX, FTSE, color = "lemonchiffon") |>
  e_band2(DAX, SMI, color = "lightblue", itemStyle = list(borderWidth = 0)) |>
  e_y_axis(scale = TRUE) |>
  e_datazoom(start = 50)

Callbacks

Description

Binds events to chart interactions.

Usage

e_on(e, query, handler, event = "click")

e_off(e, query, handler, event = "click")

Arguments

See Also

official documentation

Examples

cars |>
  e_charts(speed) |>
  e_scatter(dist) |>
  e_on(
    list(seriesName = "dist"),
    "function(){alert('Serie clicked')}"
  )

Connect charts

Description

Connect charts together.

Usage

e_connect(e, ids)

e_group(e, group)

e_connect_group(e, group)

e_disconnect_group(e, group = NULL)

e_arrange(..., rows = NULL, cols = NULL, width = "xs", title = NULL)

Arguments

Value

e_arrange: in an interactive session, returns a htmltools::browsable, in rmarkdown returns a container (htmltools::div).

Functions

• e_connect: connects charts by ids, cannot be disconnected.

• e_group: assigns a group to chart.

• e_connect_group: connects chart with another group.

• e_disconnect_group: diconnects chart from group.

• e_arrange: arrange charts.

Note

e_arrange may not work properly in the RStudio viewer.

Examples

# linked datazoom
e1 <- cars |>
  e_charts(
    speed,
    height = 200
  ) |>
  e_scatter(dist) |>
  e_datazoom(show = FALSE) |>
  e_group("grp") # assign group

e2 <- cars |>
  e_charts(
    dist,
    height = 200
  ) |>
  e_scatter(speed) |>
  e_datazoom() |>
  e_group("grp") |> # assign group
  e_connect_group("grp") # connect

if (interactive()) {
  e_arrange(e1, e2, title = "Linked datazoom")
}

Animation

Description

Customise animations.

Usage

e_animation(
  e,
  show = TRUE,
  threshold = NULL,
  duration = NULL,
  easing = NULL,
  delay = NULL,
  duration.update = NULL,
  easing.update = NULL,
  delay.update = NULL
)

Arguments

See Also

Additional arguments

Examples

mtcars |>
  e_charts(mpg) |>
  e_area(drat) |>
  e_animation(duration = 10000)

Append Proxy

Description

Append data dynamically.

Usage

e_append1_p(proxy, series_index = NULL, data, x, y, name = NULL)

e_append1_p_(proxy, series_index = NULL, data, x, y, name = NULL)

e_append2_p(
  proxy,
  series_index = NULL,
  data,
  x,
  y,
  z,
  scale = NULL,
  symbol_size = 1
)

e_append2_p_(
  proxy,
  series_index = NULL,
  data,
  x,
  y,
  z,
  scale = NULL,
  symbol_size = 1
)

Arguments

Details

Currently not all types of series supported incremental rendering when using appendData. Only these types of series support it: e_scatter and e_line of pure echarts, and e_scatter_3d, and e_line_3d of echarts-gl.

Examples

## Not run: 
library(shiny)

ui <- fluidPage(
  actionButton("add", "Add Data to y"),
  echarts4rOutput("plot"),
  h4("Brush"),
  verbatimTextOutput("selected"),
  h4("Legend select change"),
  verbatimTextOutput("legend")
)

server <- function(input, output, session) {
  data <- data.frame(x = rnorm(10, 5, 3), y = rnorm(10, 50, 12), z = rnorm(10, 5, 20))

  react <- eventReactive(input$add, {
    set.seed(sample(1:1000, 1))
    data.frame(x = rnorm(10, 5, 2), y = rnorm(10, 50, 10), z = rnorm(10, 5, 20))
  })

  output$plot <- renderEcharts4r({
    data |>
      e_charts(x) |>
      e_scatter(y, z, scale = NULL) |>
      e_scatter(z) |>
      e_brush()
  })

  observeEvent(input$add, {
    echarts4rProxy("plot") |>
      e_append2_p(0, react(), x, y, z)
  })

  output$selected <- renderPrint({
    input$plot_brush
  })

  output$legend <- renderPrint({
    input$plot_legend_change
  })
}

shinyApp(ui, server)

## End(Not run)

Area

Description

Add area serie. Note that this is NOT an unique series type. Rather, this function is a shorthand for using 'e_bar()' with 'areaStyle = list()' enabled.

Usage

e_area(
  e,
  serie,
  bind,
  name = NULL,
  legend = TRUE,
  y_index = 0,
  x_index = 0,
  coord_system = "cartesian2d",
  ...
)

e_area_(
  e,
  serie,
  bind = NULL,
  name = NULL,
  legend = TRUE,
  y_index = 0,
  x_index = 0,
  coord_system = "cartesian2d",
  ...
)

Arguments

See Also

Additional arguments

Examples

CO2 |>
  group_by(Plant) |>
  e_charts(conc) |>
  e_area(uptake) |>
  e_tooltip(trigger = "axis")

# timeline
iris |>
  group_by(Species) |>
  e_charts(Sepal.Length, timeline = TRUE) |>
  e_area(Sepal.Width) |>
  e_tooltip(trigger = "axis")

Aria

Description

W3C defined the Accessible Rich Internet Applications Suite (WAI-ARIA) to make Web content and Web applications more accessible to the disabled. From ECharts 4.0, echarts4r supports ARIA by generating description for charts automatically.

Usage

e_aria(e, enabled = TRUE, ...)

Arguments

Details

There should be an aria-label attribute on the chart DOM, which can help the disabled understand the content of charts with the help of certain devices.

See Also

official documentation

Axis

Description

Customise axis.

Usage

e_axis(
  e,
  serie,
  axis = c("x", "y", "z"),
  index = 0,
  formatter = NULL,
  margin = 0,
  ...
)

e_axis_(
  e,
  serie = NULL,
  axis = c("x", "y", "z"),
  index = 0,
  formatter = NULL,
  margin = 0,
  ...
)

e_x_axis_(e, serie = NULL, index = 0, formatter = NULL, margin = 0, ...)

e_y_axis_(e, serie = NULL, index = 0, formatter = NULL, margin = 0, ...)

e_z_axis_(e, serie = NULL, index = 0, margin = 0, ...)

e_x_axis(e, serie, index = 0, formatter = NULL, margin = 0, ...)

e_y_axis(e, serie, index = 0, formatter = NULL, margin = 0, ...)

e_z_axis(e, serie, index = 0, margin = 0, ...)

e_rm_axis(e, axis = c("x", "y", "z"))

e_axis_formatter(
  style = c("decimal", "percent", "currency"),
  digits = 0,
  locale = NULL,
  currency = "USD"
)

Arguments

Details

The e_axis_formatter may not work in RStudio, open the plot in your browser. It will display just fine in Rmarkdown and Shiny.

Functions

• e_axis to customise axis

• e_rm_axis to remove axis

See Also

Additional x arguments, Additional y arguments

Examples

# range axis based on serie
cars |>
  e_charts(speed) |>
  e_line(dist) |>
  e_x_axis(speed) |>
  e_y_axis(dist)

# use formatter
cars |>
  dplyr::mutate(
    speed = speed / 25
  ) |>
  e_charts(speed) |>
  e_scatter(dist) |>
  e_y_axis(
    formatter = e_axis_formatter("currency")
  ) |>
  e_x_axis(
    formatter = e_axis_formatter("percent", digits = 0)
  )

# plot all labels & rotate
USArrests |>
  head(10) |>
  tibble::rownames_to_column(var = "State") |> 
  e_charts(State) |>
  e_area(Murder) |>
  e_x_axis(axisLabel = list(interval = 0, rotate = 45)) # rotate

Axis 3D

Description

Customise 3D axis.

Usage

e_axis_3d(e, axis = c("x", "y", "z"), index = 0, ...)

e_x_axis_3d(e, index = 0, ...)

e_y_axis_3d(e, index = 0, ...)

e_z_axis_3d(e, index = 0, ...)

Arguments

See Also

Additional x arguments, Additional y arguments, Additional z arguments

Examples

# phony data
v <- LETTERS[1:10]
matrix <- data.frame(
  x = sample(v, 300, replace = TRUE),
  y = sample(v, 300, replace = TRUE),
  z1 = rnorm(300, 10, 1),
  z2 = rnorm(300, 10, 1),
  stringsAsFactors = FALSE
) |>
  dplyr::group_by(x, y) |>
  dplyr::summarise(
    z1 = sum(z1),
    z2 = sum(z2)
  ) |>
  dplyr::ungroup()

trans <- list(opacity = 0.4) # transparency
emphasis <- list(itemStyle = list(color = "#313695"))

matrix |>
  e_charts(x) |>
  e_bar_3d(y, z1, stack = "stack", name = "Serie 1", itemStyle = trans, emphasis = emphasis) |>
  e_bar_3d(y, z2, stack = "stack", name = "Serie 2", itemStyle = trans, emphasis = emphasis) |>
  e_x_axis_3d(axisLine = list(lineStyle = list(color = "blue")))

Axis Labels

Description

Convenience function to add axis labels.

Usage

e_axis_labels(e, x = "", y = "")

Arguments

Examples

cars |>
  e_charts(speed) |>
  e_scatter(dist) |>
  e_axis_labels(
    x = "speed",
    y = "distance"
  )

Axis pointer

Description

Customise axis pointer.

Usage

e_axis_pointer(e, ...)

Arguments

See Also

Additional arguments

Stagger Axis Labels

Description

Stagger axis labels.

Usage

e_axis_stagger(e)

Arguments

Examples

df <- data.frame(
  x = c("a very long label", "Another long label"),
  y = 1:2
)

df |>
  e_charts(x, width = 150) |>
  e_bar(y) |>
  e_axis_stagger()

Bar and Line chart

Description

Add bar serie.

Usage

e_bar(
  e,
  serie,
  bind,
  name = NULL,
  legend = TRUE,
  y_index = 0,
  x_index = 0,
  coord_system = "cartesian2d",
  ...
)

e_bar_(
  e,
  serie,
  bind = NULL,
  name = NULL,
  legend = TRUE,
  y_index = 0,
  x_index = 0,
  coord_system = "cartesian2d",
  ...
)

Arguments

Note

The bar serie expects the data on the x axis to be categorical in R this means a factor or character. If the data on the x axis is numeric everything should work well in most cases but strange behaviour may be observed.

See Also

Additional arguments

Examples

library(dplyr)

mtcars |>
  tibble::rownames_to_column("model") |> 
  mutate(total = mpg + qsec) |>
  arrange(desc(total)) |>
  e_charts(model) |>
  e_bar(mpg, stack = "grp") |>
  e_bar(qsec, stack = "grp")

Bar 3D

Description

Add 3D bars

Usage

e_bar_3d(
  e,
  y,
  z,
  bind,
  coord_system = "cartesian3D",
  name = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

e_bar_3d_(
  e,
  y,
  z,
  bind = NULL,
  coord_system = "cartesian3D",
  name = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

Arguments

See Also

Additional arguments

Examples

## Not run: 
# volcano
volcano |>
  as.table() |>
  as.data.frame() |>
  dplyr::mutate(
    Var1 = as.integer(Var1),
    Var2 = as.integer(Var2)
  ) |>
  e_charts(Var1) |>
  e_bar_3d(Var2, Freq) |>
  e_visual_map(Freq)

url <- paste0(
  "https://echarts.apache.org/examples/",
  "data-gl/asset/data/population.json"
)
data <- jsonlite::fromJSON(url)
data <- as.data.frame(data)
names(data) <- c("lon", "lat", "value")

# globe
data |>
  e_charts(lon) |>
  e_globe() |>
  e_bar_3d(lat, value, coord_system = "globe") |>
  e_visual_map()

# get3d
data |>
  e_charts(lon) |>
  e_geo_3d() |>
  e_bar_3d(lat, value, coord_system = "geo3D") |>
  e_visual_map()

# stacked
v <- LETTERS[1:10]
matrix <- data.frame(
  x = sample(v, 300, replace = TRUE),
  y = sample(v, 300, replace = TRUE),
  z1 = rnorm(300, 10, 1),
  z2 = rnorm(300, 10, 1),
  stringsAsFactors = FALSE
) |>
  dplyr::group_by(x, y) |>
  dplyr::summarise(
    z1 = sum(z1),
    z2 = sum(z2)
  ) |>
  dplyr::ungroup()

trans <- list(opacity = 0.4) # transparency
emphasis <- list(itemStyle = list(color = "#313695"))

matrix |>
  e_charts(x) |>
  e_bar_3d(y, z1, stack = "stack", name = "Serie 1", itemStyle = trans, emphasis = emphasis) |>
  e_bar_3d(y, z2, stack = "stack", name = "Serie 2", itemStyle = trans, emphasis = emphasis) |>
  e_legend()

# timeline
matrix |>
  group_by(x) |>
  e_charts(y, timeline = TRUE) |>
  e_bar_3d(z1, z2) |>
  e_visual_map(z2)

## End(Not run)

Boxplot

Description

Draw boxplot.

Usage

e_boxplot(e, serie, name = NULL, outliers = TRUE, ...)

e_boxplot_(e, serie, name = NULL, outliers = TRUE, ...)

Arguments

See Also

Additional arguments

Examples

df <- data.frame(
  x = c(1:10, 25),
  y = c(1:10, -6)
)

df |>
  e_charts() |>
  e_boxplot(y, outliers = TRUE) |>
  e_boxplot(x, outliers = TRUE)

Brush

Description

Add a brush.

Usage

e_brush(e, x_index = NULL, y_index = NULL, brush_link = "all", ...)

Arguments

brush_link

$

• c(3, 4, 5), for interacting series with seriesIndex as 3, 4, or 5.

• all, for interacting all series.

• none for disabling.

See Also

Additional arguments

Examples

quakes |>
  e_charts(long) |>
  e_geo(
    boundingCoords = list(
      c(190, -10),
      c(180, -40)
    )
  ) |>
  e_scatter(lat, mag, stations, coord.system = "geo", name = "mag") |>
  e_data(quakes, depth) |>
  e_scatter(mag, mag, stations, name = "mag & depth") |>
  e_grid(right = 40, top = 100, width = "30%") |>
  e_y_axis(type = "value", name = "depth", min = 3.5) |>
  e_brush() |>
  e_theme("dark")

Button

Description

Add a button to your visualisation.

Usage

e_button(e, id, ..., position = "top", tag = htmltools::tags$button)

Arguments

Examples

iris |>
  group_by(Species) |>
  e_charts(Sepal.Length) |>
  e_line(Sepal.Width) |>
  e_line(Petal.Length) |>
  e_highlight(series_name = "setosa", btn = "myBtn") |>
  e_button("myBtn", "highlight stuff")

Calendar

Description

Calendar

Usage

e_calendar(e, range, ...)

Arguments

See Also

Additional arguments

Examples

dates <- seq.Date(as.Date("2017-01-01"), as.Date("2019-12-31"), by = "day")
values <- rnorm(length(dates), 20, 6)
year <- data.frame(date = dates, values = values)

year |>
   e_charts(date) |>
   e_calendar(range = "2017") |>
   e_visual_map(max = 30) |>
   e_heatmap(values, coord_system = "calendar")

# month
year |>
   e_charts(date) |>
   e_calendar(range = "2017-01") |>
   e_visual_map(max = 30) |>
   e_heatmap(values, coord_system = "calendar")

# range
year |>
   e_charts(date) |>
   e_calendar(range = c("2018-01", "2018-07")) |>
   e_visual_map(max = 30) |>
   e_heatmap(values, coord_system = "calendar")

Candlestick

Description

Add a candlestick chart.

Usage

e_candle(e, opening, closing, low, high, bind, name = NULL, legend = TRUE, ...)

e_candle_(
  e,
  opening,
  closing,
  low,
  high,
  bind = NULL,
  name = NULL,
  legend = TRUE,
  ...
)

Arguments

See Also

Additional arguments

Examples

date <- c(
  "2017-01-01",
  "2017-01-02",
  "2017-01-03",
  "2017-01-04",
  "2017-03-05",
  "2017-01-06",
  "2017-01-07"
)

stock <- data.frame(
  date = date,
  opening = c(200.60, 200.22, 198.43, 199.05, 203.54, 203.40, 208.34),
  closing = c(200.72, 198.85, 199.05, 203.73, 204.08, 208.11, 211.88),
  low = c(197.82, 198.07, 197.90, 198.10, 202.00, 201.50, 207.60),
  high = c(203.32, 200.67, 200.00, 203.95, 204.90, 208.44, 213.17)
)

stock |>
  e_charts(date) |>
  e_candle(opening, closing, low, high) |>
  e_y_axis(min = 190, max = 220)

Capture event

Description

Add an event capture.

Usage

e_capture(e, event)

Arguments

Details

Many events can be captured, however not all are integrated, you can pass one that is not implemented with this function.

Examples

## Not run: 
# add datazoom
library(shiny)

ui <- fluidPage(
  echarts4rOutput("chart"),
  verbatimTextOutput("zoom")
)

server <- function(input, output) {
  output$chart <- renderEcharts4r({
    mtcars |>
      e_charts(mpg) |>
      e_scatter(qsec) |>
      e_datazoom() |>
      e_capture("datazoom")
  })

  output$zoom <- renderPrint({
    input$chart_datazoom
  })
}

if (interactive()) {
  shinyApp(ui, server)
}

## End(Not run)

Wordcloud

Description

Draw a wordcloud.

Usage

e_cloud(e, word, freq, color, rm_x = TRUE, rm_y = TRUE, ...)

e_cloud_(e, word, freq, color = NULL, rm_x = TRUE, rm_y = TRUE, ...)

Arguments

See Also

official documentation

Examples

words <- function(n = 5000) {
  a <- do.call(paste0, replicate(5, sample(LETTERS, n, TRUE), FALSE))
  paste0(a, sprintf("%04d", sample(9999, n, TRUE)), sample(LETTERS, n, TRUE))
}

tf <- data.frame(
  terms = words(100),
  freq = rnorm(100, 55, 10)
) |>
  dplyr::arrange(-freq)

tf |>
  e_color_range(freq, color) |>
  e_charts() |>
  e_cloud(terms, freq, color, shape = "circle", sizeRange = c(3, 15))

Color

Description

Customise chart and background colors.

Usage

e_color(e, color = NULL, background = NULL, append = TRUE)

## S3 method for class 'echarts4r'
e_color(e, color = NULL, background = NULL, append = TRUE)

## S3 method for class 'echarts4rProxy'
e_color(e, color = NULL, background = NULL, append = TRUE)

Arguments

See Also

e_theme, Official color documentation, Official background documentation

Examples

mtcars |>
  e_charts(drat) |>
  e_line(mpg) |>
  e_area(qsec) |>
  e_color(
    c("red", "blue"),
    "#d3d3d3"
  )

Color range

Description

Build manual color range

Usage

e_color_range(
  data,
  input,
  output,
  colors = c("#bf444c", "#d88273", "#f6efa6"),
  ...
)

e_color_range_(
  data,
  input,
  output,
  colors = c("#bf444c", "#d88273", "#f6efa6"),
  ...
)

Arguments

Examples

df <- data.frame(val = 1:10)

e_color_range(df, val, colors)

General options

Description

General options

Usage

e_common(font_family = NULL, theme = NULL)

Arguments

Correlation

Description

Correlation

Usage

e_correlations(e, order = NULL, visual_map = TRUE, ...)

Arguments

Examples

cor(mtcars) |>
  e_charts() |>
  e_correlations(
    order = "hclust",
    visual_map = FALSE
  ) |>
  e_visual_map(
    min = -1,
    max = 1
  )

Country names

Description

Convert country names to echarts format.

Usage

e_country_names(data, input, output, type = "iso2c", ...)

e_country_names_(data, input, output = NULL, type = "iso2c", ...)

Arguments

Details

Taiwan and Hong Kong cannot be plotted.

Examples

cns <- data.frame(country = c("US", "BE"))

# replace
e_country_names(cns, country)

# specify output
e_country_names(cns, country, country_name)

Data zoom

Description

Add data zoom.

Usage

e_datazoom(e, x_index = NULL, y_index = NULL, toolbox = TRUE, ...)

Arguments

See Also

Additional arguments

Examples

USArrests |>
  e_charts(UrbanPop) |>
  e_line(Assault) |>
  e_area(Murder, y_index = 1, x_index = 1) |>
  e_y_axis(gridIndex = 1) |>
  e_x_axis(gridIndex = 1) |>
  e_grid(height = "35%") |>
  e_grid(height = "35%", top = "50%") |>
  e_toolbox_feature("dataZoom", title = list(zoom = "zoom", back = "back")) |>
  e_datazoom(x_index = c(0, 1))

Dimensions

Description

Sets the dimensions of the chart _internally._ This will only affect the dimensions of the chart within its parent container. Use the 'height' and 'width' arguments of [e_charts] if you want to change the dimensions of said parent (recommended).

Usage

e_dims(e, height = "auto", width = "auto")

Arguments

Dispatch Action

Description

Create your own proxies, essentially a wrapper around the action API.

Usage

e_dispatch_action_p(proxy, type, ...)

Arguments

Examples

## Not run: 

library(shiny)

ui <- fluidPage(
  fluidRow(
    column(8, echarts4rOutput("chart")),
    column(4, actionButton("zoom", "Zoom"))
  )
)

server <- function(input, output, session) {
  output$chart <- renderEcharts4r({
    cars |>
      e_charts(speed) |>
      e_scatter(dist) |>
      e_datazoom()
  })

  observe({
    req(input$zoom)

    echarts4rProxy("chart") |>
      e_dispatch_action_p("dataZoom", startValue = 1, endValue = 10)
  })
}

if (interactive()) {
  shinyApp(ui, server)
}

## End(Not run)

Draft

Description

Add a draft watermark to your graph.

Usage

e_draft(e, text = "DRAFT", size = "120px", opacity = 0.4, color = "#d3d3d3")

Arguments

Examples

cars |>
  e_charts(speed) |>
  e_scatter(dist) |>
  e_draft()

Draw

Description

Draw the chart.

Usage

e_draw_p(proxy)

Arguments

Details

Useful if you set draw to FALSE in e_charts.

Examples

## Not run: 
library(shiny)

ui <- fluidPage(
  echarts4rOutput("chart"),
  actionButton("draw", "draw")
)

server <- function(input, output) {
  output$chart <- renderEcharts4r({
    mtcars |>
      e_charts(mpg, draw = FALSE) |>
      e_scatter(qsec) |>
      e_datazoom()
  })

  observeEvent(input$draw, {
    echarts4rProxy("chart") |>
      e_draw_p()
  })
}

if (interactive()) {
  shinyApp(ui, server)
}

## End(Not run)

Error bar

Description

Add error bars.

Usage

e_error_bar(
  e,
  lower,
  upper,
  name = NULL,
  legend = FALSE,
  y_index = 0,
  x_index = 0,
  coord_system = "cartesian2d",
  ...
)

e_error_bar_(
  e,
  lower,
  upper,
  name = NULL,
  legend = FALSE,
  y_index = 0,
  x_index = 0,
  coord_system = "cartesian2d",
  itemStyle = list(borderWidth = 1.5),
  renderer = "renderErrorBar2",
  ...
)

Arguments

Examples

df <- data.frame(
  x = factor(c(1, 2)),
  y = c(1, 5),
  upper = c(1.1, 5.3),
  lower = c(0.8, 4.6)
)

df |>
  e_charts(x) |>
  e_bar(y) |>
  e_error_bar(lower, upper)

# timeline
df <- data.frame(
  x = factor(c(1, 1, 2, 2)),
  y = c(1, 5, 3, 4),
  step = factor(c(1, 2, 1, 2)),
  upper = c(1.1, 5.3, 3.3, 4.2),
  lower = c(0.8, 4.6, 2.4, 3.6)
)

df |>
  group_by(step) |>
  e_charts(x, timeline = TRUE) |>
  e_bar(y) |>
  e_error_bar(lower, upper)

Send

Description

Send new series to chart.

Usage

e_execute(proxy)

e_execute_p(proxy)

Arguments

Facet

Description

Create facets for multiple plots.

Usage

e_facet(
  e,
  rows = NULL,
  cols = NULL,
  legend_pos = "top",
  legend_space = 10,
  margin_trbl = c(t = 2, r = 2, b = 5, l = 2),
  h_panel_space = NULL,
  v_panel_space = NULL
)

Arguments

Details

Each serie, i.e.: e_bar will be plotted against a facet.

Examples

group_size <- 20
n_groups <- 13
df <- data.frame("day" = rep(1:group_size, times=n_groups), 
                 "temperature" = runif(group_size * n_groups, 10, 40),
                 "location" = rep(LETTERS[1:n_groups], each=group_size))

df |> 
  group_by(location) |> 
  e_charts(day) |> 
  e_line(temperature) |> 
  e_facet(rows = 4, cols=4, legend_pos = "top", legend_space = 12) 

Flip coordinates

Description

Flip cartesian 2D coordinates.

Usage

e_flip_coords(e)

Arguments

Examples

df <- data.frame(
  x = LETTERS[1:5],
  y = runif(5, 1, 5),
  z = runif(5, 3, 10)
)

df |>
  e_charts(x) |>
  e_bar(y) |>
  e_line(z) -> plot

plot # normal
e_flip_coords(plot) # flip

Flow GL

Description

Flow GL

Usage

e_flow_gl(
  e,
  y,
  sx,
  sy,
  color,
  name = NULL,
  coord_system = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

e_flow_gl_(
  e,
  y,
  sx,
  sy,
  color = NULL,
  name = NULL,
  coord_system = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

Arguments

See Also

Additional arguments

Examples

# coordinates
vectors <- expand.grid(0:9, 0:9)
names(vectors) <- c("x", "y")
vectors$sx <- rnorm(100)
vectors$sy <- rnorm(100)
vectors$color <- log10(runif(100, 1, 10))

vectors |>
  e_charts(x) |>
  e_flow_gl(y, sx, sy, color) |>
  e_visual_map(
    min = 0,
    max = 1,
    # log 10
    dimension = 4,
    # x = 0, y = 1, sx = 3, sy = 4
    show = FALSE,
    # hide
    inRange = list(
      color = c(
        "#313695",
        "#4575b4",
        "#74add1",
        "#abd9e9",
        "#e0f3f8",
        "#ffffbf",
        "#fee090",
        "#fdae61",
        "#f46d43",
        "#d73027",
        "#a50026"
      )
    )
  ) |>
  e_x_axis(
    splitLine = list(show = FALSE)
  ) |>
  e_y_axis(
    splitLine = list(show = FALSE)
  )

# map
latlong <- seq(-180, 180, by = 5)
wind <- expand.grid(lng = latlong, lat = latlong)
wind$slng <- rnorm(nrow(wind), 0, 200)
wind$slat <- rnorm(nrow(wind), 0, 200)
wind$color <- abs(wind$slat) - abs(wind$slng)
rng <- range(wind$color)

trans <- list(opacity = 0.5) # transparency

wind |>
  e_charts(lng, backgroundColor = "#333") |>
  e_geo() |>
  e_flow_gl(
    lat,
    slng,
    slat,
    color,
    itemStyle = trans,
    particleSize = 2
  ) |>
  e_visual_map(
    color,
    # range
    dimension = 4,
    # lng = 0, lat = 1, slng = 2, slat = 3, color = 4
    show = FALSE,
    # hide
    inRange = list(
      color = c(
        "#313695",
        "#4575b4",
        "#74add1",
        "#abd9e9",
        "#e0f3f8",
        "#ffffbf",
        "#fee090",
        "#fdae61",
        "#f46d43",
        "#d73027",
        "#a50026"
      )
    )
  ) |>
  e_x_axis(show = FALSE) |>
  e_y_axis(show = FALSE)

Node Adjacency

Description

Focus or unfocus on node adjacency.

Usage

e_focus_adjacency_p(proxy, index, ...)

e_unfocus_adjacency_p(proxy, ...)

Arguments

Details

Must pass seriesId, seriesIndex, or seriesName, generally seriesIndex = 0 will work.

Examples

value <- rnorm(10, 10, 2)

nodes <- data.frame(
  name = sample(LETTERS, 10),
  value = value,
  size = value,
  grp = rep(c("grp1", "grp2"), 5),
  stringsAsFactors = FALSE
)

edges <- data.frame(
  source = sample(nodes$name, 20, replace = TRUE),
  target = sample(nodes$name, 20, replace = TRUE),
  stringsAsFactors = FALSE
)
## Not run: 

library(shiny)

ui <- fluidPage(
  fluidRow(
    column(
      2,
      numericInput("index", "Node", value = 3, min = 1, max = 9)
    ),
    column(
      2,
      br(),
      actionButton("focus", "Focus")
    ),
    column(
      2,
      br(),
      actionButton("unfocus", "Unfocus")
    )
  ),
  fluidRow(
    column(12, echarts4rOutput("graph"))
  )
)

server <- function(input, output, session) {
  output$graph <- renderEcharts4r({
    e_charts() |>
      e_graph() |>
      e_graph_nodes(nodes, name, value, size, grp) |>
      e_graph_edges(edges, source, target)
  })

  observeEvent(input$focus, {
    echarts4rProxy("graph") |>
      e_focus_adjacency_p(
        seriesIndex = 0,
        index = input$index
      )
  })

  observeEvent(input$unfocus, {
    echarts4rProxy("graph") |>
      e_unfocus_adjacency_p(seriesIndex = 0)
  })
}

if (interactive()) {
  shinyApp(ui, server)
}

## End(Not run)

Formatters

Description

Simple formatters as helpers.

Usage

e_format_axis(e, axis = "y", suffix = NULL, prefix = NULL, ...)

e_format_x_axis(e, suffix = NULL, prefix = NULL, ...)

e_format_y_axis(e, suffix = NULL, prefix = NULL, ...)

Arguments

Examples

# Y = %
df <- data.frame(
  x = 1:10,
  y = round(
    runif(10, 1, 100),
    2
  )
)

df |>
  e_charts(x) |>
  e_line(y) |>
  e_format_y_axis(suffix = "%") |>
  e_format_x_axis(prefix = "A")

Funnel

Description

Add a funnel.

Usage

e_funnel(
  e,
  values,
  labels,
  name = NULL,
  legend = TRUE,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

e_funnel_(
  e,
  values,
  labels,
  name = NULL,
  legend = TRUE,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

Arguments

Details

No bind argument here, with a funnel bind = labels.

See Also

Additional arguments

Examples

funnel <- data.frame(
  stage = c("View", "Click", "Purchase"),
  value = c(80, 30, 20)
)

funnel |>
  e_charts() |>
  e_funnel(value, stage)

Gauge

Description

Plot a gauge.

Usage

e_gauge(e, value, name, rm_x = TRUE, rm_y = TRUE, ...)

e_gauge_(e, value, name, rm_x = TRUE, rm_y = TRUE, ...)

Arguments

See Also

Additional arguments

Examples

e_charts() |>
  e_gauge(57, "PERCENT")

# timeline 
data.frame(time = 2015:2017) |> 
  group_by(time) |> 
  e_charts(timeline = TRUE) |>
    e_gauge(
      c(57, 23, 65),
      c("percent", "percentage", "cases")
    )

Geo

Description

Initialise geo.

Usage

e_geo(e, map = "world", ..., rm_x = TRUE, rm_y = TRUE)

Arguments

See Also

Additional arguments

Examples

flights <- read.csv(
  paste0(
    "https://raw.githubusercontent.com/plotly/datasets/",
    "master/2011_february_aa_flight_paths.csv"
  )
)

flights |>
  e_charts() |>
  e_geo() |>
  e_lines(
    start_lon,
    start_lat,
    end_lon,
    end_lat,
    name = "flights",
    lineStyle = list(normal = list(curveness = 0.3))
  )

Geo 3D

Description

Initialise geo 3D.

Usage

e_geo_3d(e, serie, color, type = "world", rm_x = TRUE, rm_y = TRUE, ...)

e_geo_3d_(
  e,
  serie = NULL,
  color = NULL,
  type = "world",
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

Arguments

See Also

e_country_names, Additional arguments

Examples

choropleth <- data.frame(
  countries = c(
    "France",
    "Brazil",
    "China",
    "Russia",
    "Canada",
    "India",
    "United States",
    "Argentina",
    "Australia"
  ),
  height = runif(9, 1, 5),
  color = c(
    "#F7FBFF",
    "#DEEBF7",
    "#C6DBEF",
    "#9ECAE1",
    "#6BAED6",
    "#4292C6",
    "#2171B5",
    "#08519C",
    "#08306B"
  )
)

choropleth |>
  e_charts(countries) |>
  e_geo_3d(height, color)

Get data

Description

Get data passed to e_charts.

Usage

e_get_data(e)

Arguments

Value

A list of data.frames, one for each group.

Examples

echart <- cars |>
  e_charts(speed) |>
  e_scatter(dist) |>
  e_lm(dist ~ speed)

echart

e_get_data(echart)[[1]]

Blank Area

Description

Use this function to capture a click on a blank area of the canvas. Note that this may stops other "click" events from working.

Usage

e_get_zr()

Globe

Description

Add globe.

Usage

e_globe(e, environment = NULL, base_texture = NULL, height_texture = NULL, ...)

Arguments

See Also

e_country_names, Additional arguments

Examples

## Not run: 
url <- paste0(
  "https://echarts.apache.org/examples/",
  "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_globe(
    displacementScale = 0.04
  ) |>
  e_bar_3d(lat, value, "globe") |>
  e_visual_map(show = FALSE)

## End(Not run)

Graph

Description

Create a graph.

Usage

e_graph(e, layout = "force", name = NULL, rm_x = TRUE, rm_y = TRUE, ...)

e_graph_gl(
  e,
  layout = "force",
  name = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  ...,
  itemStyle = list(opacity = 1)
)

e_graph_nodes(
  e,
  nodes,
  names,
  value,
  size,
  category,
  symbol = NULL,
  legend = TRUE
)

e_graph_edges(e, edges, source, target, value, size)

Arguments

See Also

Additional arguments, e_modularity

Examples

value <- rnorm(10, 10, 2)

nodes <- data.frame(
  name = sample(LETTERS, 10),
  value = value,
  size = value,
  symbol = sample(c("circle", "rect", "triangle"), 10, replace = TRUE),
  grp = rep(c("grp1", "grp2"), 5),
  stringsAsFactors = FALSE
)

value_edges <- sample(1:100, 20, replace = TRUE)
edges <- data.frame(
  source = sample(nodes$name, 20, replace = TRUE),
  target = sample(nodes$name, 20, replace = TRUE),
  value = value_edges,
  size = ceiling(value_edges/20),
  stringsAsFactors = FALSE
)

e_charts() |>
  e_graph() |>
  e_graph_nodes(nodes, name, value, size, grp, symbol) |>
  e_graph_edges(edges, source, target, value, size) |>
  e_tooltip()

# Use graphGL for larger networks
nodes <- data.frame(
  name = paste0(LETTERS, 1:1000),
  value = rnorm(1000, 10, 2),
  size = rnorm(1000, 10, 2),
  grp = rep(c("grp1", "grp2"), 500),
  stringsAsFactors = FALSE
)

edges <- data.frame(
  source = sample(nodes$name, 2000, replace = TRUE),
  target = sample(nodes$name, 2000, replace = TRUE),
  stringsAsFactors = FALSE
)

e_charts() |>
  e_graph_gl() |>
  e_graph_nodes(nodes, name, value, size, grp) |>
  e_graph_edges(edges, source, target)

Graphic

Description

Low level API to define graphic elements.

Usage

e_graphic_g(e, ...)

e_group_g(e, ...)

e_image_g(e, ...)

e_text_g(e, ...)

e_rect_g(e, ...)

e_circle_g(e, ...)

e_ring_g(e, ...)

e_sector_g(e, ...)

e_arc_g(e, ...)

e_polygon_g(e, ...)

e_polyline_g(e, ...)

e_line_g(e, ...)

e_bezier_curve_g(e, ...)

Arguments

Functions

• e_graphic_g to initialise graphics, entirely optional.

• e_group_g to create group, the children of which will share attributes.

• e_image_g to a png or jpg image.

• e_text_g to add text.

• e_rect_g to add a rectangle.

• e_circle_g to add a circle.

• e_ring_g to add a ring.

• e_sector_g

• e_arc_g to create an arc.

• e_polygon_g to create a polygon.

• e_polyline_g to create a polyline.

• e_line_g to draw a line.

• e_bezier_curve_g to draw a quadratic bezier curve or cubic bezier curve.

Note

Some elements, i.e.: e_image_g may not display in the RStudio browwser but will work fine in your browser, R markdown documents and Shiny applications.

See Also

official documentation

Examples

# may not work in RStudio viewer
# Open in browser
cars |>
  e_charts(speed) |>
  e_scatter(dist) |>
  e_image_g(
    right = 20,
    top = 20,
    z = -999,
    style = list(
      image = "https://www.r-project.org/logo/Rlogo.png",
      width = 150,
      height = 150,
      opacity = .6
    )
  )

Grid

Description

Customise grid.

Usage

e_grid(e, index = NULL, ...)

Arguments

See Also

Additional arguments

Examples

USArrests |>
  e_charts(UrbanPop) |>
  e_line(Assault, smooth = TRUE) |>
  e_area(Murder, y.index = 1, x.index = 1) |>
  e_y_axis(gridIndex = 1) |>
  e_x_axis(gridIndex = 1) |>
  e_grid(height = "40%") |>
  e_grid(height = "40%", top = "55%")

Grid

Description

Customise grid.

Usage

e_grid_3d(e, index = 0, ...)

Arguments

See Also

Additional arguments

Examples

# phony data
v <- LETTERS[1:10]
matrix <- data.frame(
  x = sample(v, 300, replace = TRUE),
  y = sample(v, 300, replace = TRUE),
  z1 = rnorm(300, 10, 1),
  z2 = rnorm(300, 10, 1),
  stringsAsFactors = FALSE
) |>
  dplyr::group_by(x, y) |>
  dplyr::summarise(
    z1 = sum(z1),
    z2 = sum(z2)
  ) |>
  dplyr::ungroup()

trans <- list(opacity = 0.4) # transparency
emphasis <- list(itemStyle = list(color = "#313695"))

matrix |>
  e_charts(x) |>
  e_bar_3d(y, z1, stack = "stack", name = "Serie 1", itemStyle = trans, emphasis = emphasis) |>
  e_bar_3d(y, z2, stack = "stack", name = "Serie 2", itemStyle = trans, emphasis = emphasis) |>
  e_grid_3d(splitLine = list(lineStyle = list(color = "blue")))

Heatmap

Description

Draw heatmap by coordinates.

Usage

e_heatmap(
  e,
  y,
  z,
  bind,
  name = NULL,
  coord_system = "cartesian2d",
  rm_x = TRUE,
  rm_y = TRUE,
  calendar = NULL,
  ...
)

e_heatmap_(
  e,
  y,
  z = NULL,
  bind = NULL,
  name = NULL,
  coord_system = "cartesian2d",
  rm_x = TRUE,
  rm_y = TRUE,
  calendar = NULL,
  ...
)

Arguments

See Also

Additional arguments

Examples

v <- LETTERS[1:10]
matrix <- data.frame(
  x = sample(v, 300, replace = TRUE),
  y = sample(v, 300, replace = TRUE),
  z = rnorm(300, 10, 1),
  stringsAsFactors = FALSE
) |>
  dplyr::group_by(x, y) |>
  dplyr::summarise(z = sum(z)) |>
  dplyr::ungroup()

matrix |>
  e_charts(x) |>
  e_heatmap(y, z, itemStyle = list(emphasis = list(shadowBlur = 10))) |>
  e_visual_map(z)

# calendar
dates <- seq.Date(as.Date("2017-01-01"), as.Date("2018-12-31"), by = "day")
values <- rnorm(length(dates), 20, 6)

year <- data.frame(date = dates, values = values)

year |>
  e_charts(date) |>
  e_calendar(range = "2018") |>
  e_heatmap(values, coord_system = "calendar") |>
  e_visual_map(max = 30)

# calendar multiple years
year |>
  dplyr::mutate(year = format(date, "%Y")) |>
  group_by(year) |>
  e_charts(date) |>
  e_calendar(range = "2017", top = 40) |>
  e_calendar(range = "2018", top = 260) |>
  e_heatmap(values, coord_system = "calendar") |>
  e_visual_map(max = 30)

# map
quakes |>
  e_charts(long) |>
  e_geo(
    boundingCoords = list(
      c(190, -10),
      c(180, -40)
    )
  ) |>
  e_heatmap(
    lat,
    mag,
    coord_system = "geo",
    blurSize = 5,
    pointSize = 3
  ) |>
  e_visual_map(mag)

# timeline
library(dplyr)

axis <- LETTERS[1:10]
df <- expand.grid(axis, axis)

bind_rows(df, df) |>
  mutate(
    values = runif(n(), 1, 10),
    grp = c(
      rep("A", 100),
      rep("B", 100)
    )
  ) |>
  group_by(grp) |>
  e_charts(Var1, timeline = TRUE) |>
  e_heatmap(Var2, values) |>
  e_visual_map(values)

' Hide Grid Lines

Description

A convenience function to easily hide grid lines.

Usage

e_hide_grid_lines(e, which = c("x", "y"))

Arguments

Examples

cars |>
  e_charts(speed) |>
  e_scatter(dist) |>
  e_hide_grid_lines()

Highlight & Downplay Proxy

Description

Proxies to highlight and downplay series.

Usage

e_highlight_p(proxy, series_index = NULL, series_name = NULL)

e_downplay_p(proxy, series_index = NULL, series_name = NULL)

Arguments

Examples

## Not run: 
library(shiny)

ui <- fluidPage(
  fluidRow(
    column(
      3,
      actionButton("highlightmpg", "Highlight MPG")
    ),
    column(
      3,
      actionButton("highlighthp", "Highlight HP")
    ),
    column(
      3,
      actionButton("downplaympg", "Downplay MPG")
    ),
    column(
      3,
      actionButton("downplayhp", "Downplay HP")
    )
  ),
  echarts4rOutput("plot")
)

server <- function(input, output, session) {
  output$plot <- renderEcharts4r({
    mtcars |>
      e_charts(mpg) |>
      e_line(disp) |>
      e_line(hp, name = "HP") # explicitly pass name
  })

  # highlight

  observeEvent(input$highlightmpg, {
    echarts4rProxy("plot") |>
      e_highlight_p(series_index = 0) # using index
  })

  observeEvent(input$highlighthp, {
    echarts4rProxy("plot") |>
      e_highlight_p(series_name = "HP") # using name
  })

  # downplay

  observeEvent(input$downplaympg, {
    echarts4rProxy("plot") |>
      e_downplay_p(series_name = "disp")
  })

  observeEvent(input$downplayhp, {
    echarts4rProxy("plot") |>
      e_downplay_p(series_index = 1)
  })
}

if (interactive()) {
  shinyApp(ui, server)
}

## End(Not run)

Histogram & Density

Description

Add a histogram or density plots.

Usage

e_histogram(
  e,
  serie,
  breaks = "Sturges",
  name = NULL,
  legend = TRUE,
  bar_width = "99%",
  x_index = 0,
  y_index = 0,
  ...
)

e_density(
  e,
  serie,
  breaks = "Sturges",
  name = NULL,
  legend = TRUE,
  x_index = 0,
  y_index = 0,
  smooth = TRUE,
  ...
)

e_histogram_(
  e,
  serie,
  breaks = "Sturges",
  name = NULL,
  legend = TRUE,
  bar_width = "90%",
  x_index = 0,
  y_index = 0,
  ...
)

e_density_(
  e,
  serie,
  breaks = "Sturges",
  name = NULL,
  legend = TRUE,
  x_index = 0,
  y_index = 0,
  smooth = TRUE,
  ...
)

Arguments

See Also

Additional arguments for histogram, Additional arguments for density

Examples

mtcars |>
  e_charts() |>
  e_histogram(mpg, name = "histogram") |>
  e_density(mpg, areaStyle = list(opacity = .4), smooth = TRUE, name = "density", y_index = 1) |>
  e_tooltip(trigger = "axis")

# timeline
mtcars |>
  group_by(cyl) |>
  e_charts(timeline = TRUE) |>
  e_histogram(mpg, name = "histogram") |>
  e_density(mpg, name = "density", y_index = 1)

To & From JSON

Description

Get JSON options from an echarts4r object and build one from JSON.

Usage

e_inspect(e, json = FALSE, ...)

echarts_from_json(txt)

Arguments

Details

txt should contain the full list of options required to build a chart. This is subsequently passed to the setOption ECharts (JavaScript) function.

Value

e_inspect Returns a list if json is FALSE and a JSON string otherwise. echarts_from_json returns an object of class echarts4r.

Note

Must be passed as last option.

Examples

p <- cars |>
  e_charts(dist) |>
  e_scatter(speed, symbol_size = 10)

p # plot

# extract the JSON
json <- p |>
  e_inspect(
    json = TRUE,
    pretty = TRUE
  )

# print json
json

# rebuild plot
echarts_from_json(json) |>
  e_theme("dark") # modify

Format labels

Description

Format labels

Usage

e_labels(e, show = TRUE, position = "top", ...)

Arguments

Examples

mtcars |>
  e_chart(wt) |>
  e_scatter(qsec, cyl) |>
  e_labels(fontSize = 9)

mtcars |>
  group_by(cyl) |>
  e_chart(wt) |>
  e_scatter(qsec, mpg) |>
  e_labels(fontSize = 9)

# timeline
mtcars |>
  group_by(cyl) |>
  e_chart(wt) |>
  e_scatter(qsec, mpg) |>
  e_labels(fontSize = 9)

Leaflet

Description

Leaflet extension.

Usage

e_leaflet(e, roam = TRUE, ...)

e_leaflet_tile(
  e,
  template = "https://{s}.tile.openstreetmap.fr/hot/{z}/{x}/{y}.png",
  options = NULL,
  ...
)

Arguments

Note

Will not render in the RStudio, open in browser.

Examples

## Not run: 
url <- paste0(
  "https://echarts.apache.org/examples/",
  "data-gl/asset/data/population.json"
)
data <- jsonlite::fromJSON(url)
data <- as.data.frame(data)
names(data) <- c("lon", "lat", "value")
data$value <- log(data$value)

data |>
  e_charts(lon) |>
  e_leaflet() |>
  e_leaflet_tile() |>
  e_scatter(lat, size = value, coord_system = "leaflet")

## End(Not run)

Legend

Description

Customise the legend.

Usage

e_legend(e, show = TRUE, type = c("plain", "scroll"), icons = NULL, ...)

Arguments

See Also

Additional arguments

Examples

e <- cars |>
  e_charts(speed) |>
  e_scatter(dist, symbol_size = 5)

# with legend
e

# without legend
e |>
  e_legend(show = FALSE)

# with icon
# path is taken from http://svgicons.sparkk.fr/
path <- paste0(
  "path://M11.344,5.71c0-0.73,0.074-1.122,1.199-1.122",
  "h1.502V1.871h-2.404c-2.886,0-3.903,1.36-3.903,3.646",
  "v1.765h-1.8V10h1.8v8.128h3.601V10h2.403l0.32-2.718h",
  "-2.724L11.344,5.71z"
)

e |>
  e_legend(
    icons = list(path)
  )

Line

Description

Add line serie.

Usage

e_line(
  e,
  serie,
  bind,
  name = NULL,
  legend = TRUE,
  y_index = 0,
  x_index = 0,
  coord_system = "cartesian2d",
  ...
)

e_line_(
  e,
  serie,
  bind = NULL,
  name = NULL,
  legend = TRUE,
  y_index = 0,
  x_index = 0,
  coord_system = "cartesian2d",
  ...
)

Arguments

See Also

Additional arguments

Examples

iris |>
  group_by(Species) |>
  e_charts(Sepal.Length) |>
  e_line(Sepal.Width) |>
  e_tooltip(trigger = "axis")

# timeline
iris |>
  group_by(Species) |>
  e_charts(Sepal.Length, timeline = TRUE) |>
  e_line(Sepal.Width) |>
  e_tooltip(trigger = "axis")

Lines

Description

Add lines.

Usage

e_lines(
  e,
  source_lon,
  source_lat,
  target_lon,
  target_lat,
  source_name,
  target_name,
  value,
  coord_system = "geo",
  name = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

e_lines_(
  e,
  source_lon,
  source_lat,
  target_lon,
  target_lat,
  source_name = NULL,
  target_name = NULL,
  value = NULL,
  coord_system = "geo",
  name = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

Arguments

See Also

Additional arguments

Examples

flights <- read.csv(
  paste0(
    "https://raw.githubusercontent.com/plotly/datasets/",
    "master/2011_february_aa_flight_paths.csv"
  )
)

flights |>
  e_charts() |>
  e_geo() |>
  e_lines(
    start_lon,
    start_lat,
    end_lon,
    end_lat,
    airport1,
    airport2,
    cnt,
    name = "flights",
    lineStyle = list(normal = list(curveness = 0.3))
  ) |>
  e_tooltip(
    trigger = "item",
    formatter = htmlwidgets::JS("
      function(params){
        return(
          params.seriesName +'<br />' +
          params.data.source_name + ' -> ' +
          params.data.target_name + ':'+ params.value
        )
      }
   ")
  )

# timeline
flights$grp <- rep(LETTERS[1:2], 89)

flights |>
  group_by(grp) |>
  e_charts(timeline = TRUE) |>
  e_geo() |>
  e_lines(
    start_lon,
    start_lat,
    end_lon,
    end_lat,
    cnt,
    coord_system = "geo"
  )

Lines 3D

Description

Add 3D lines.

Usage

e_lines_3d(
  e,
  source_lon,
  source_lat,
  target_lon,
  target_lat,
  source_name,
  target_name,
  value,
  name = NULL,
  coord_system = "globe",
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

e_line_3d(
  e,
  y,
  z,
  name = NULL,
  coord_system = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

e_lines_3d_(
  e,
  source_lon,
  source_lat,
  target_lon,
  target_lat,
  source_name = NULL,
  target_name = NULL,
  value = NULL,
  name = NULL,
  coord_system = "globe",
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

e_line_3d_(
  e,
  y,
  z,
  name = NULL,
  coord_system = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

Arguments

See Also

Additional arguments for lines 3D, Additional arguments for line 3D

https://echarts4r-assets.john-coene.com

Examples

# get data
flights <- read.csv(
  paste0(
    "https://raw.githubusercontent.com/plotly/datasets/",
    "master/2011_february_aa_flight_paths.csv"
  )
)

# Lines 3D
# Globe
# get tetures: echarts4r-assets.john-coene.com
flights |>
  e_charts() |>
  e_globe(
    displacementScale = 0.05
  ) |>
  e_lines_3d(
    start_lon,
    start_lat,
    end_lon,
    end_lat,
    name = "flights",
    effect = list(show = TRUE)
  ) |>
  e_legend(FALSE)

# Geo 3D
flights |>
  e_charts() |>
  e_geo_3d() |>
  e_lines_3d(
    start_lon,
    start_lat,
    end_lon,
    end_lat,
    coord_system = "geo3D"
  )

# groups
flights$grp <- rep(LETTERS[1:2], 89)

flights |>
  group_by(grp) |>
  e_charts() |>
  e_geo_3d() |>
  e_lines_3d(
    start_lon,
    start_lat,
    end_lon,
    end_lat,
    coord_system = "geo3D"
  )

# line 3D
df <- data.frame(
  x = 1:100,
  y = runif(100, 10, 25),
  z = rnorm(100, 100, 50)
)

df |>
  e_charts(x) |>
  e_line_3d(y, z) |>
  e_visual_map() |>
  e_title("nonsense")

# timeline
df$grp <- rep(LETTERS[1:5], 20)

df |>
  group_by(grp) |>
  e_charts(x) |>
  e_line_3d(y, z) |>
  e_visual_map() |>
  e_title("nonsense")

Lines WebGL

Description

Draw WebGL lines.

Usage

e_lines_gl(e, data, coord_system = "geo", ...)

Arguments

Liquid fill

Description

Draw liquid fill.

Usage

e_liquid(e, serie, color, rm_x = TRUE, rm_y = TRUE, ...)

e_liquid_(e, serie, color = NULL, rm_x = TRUE, rm_y = TRUE, ...)

Arguments

See Also

official documentation

Examples

df <- data.frame(val = c(0.6, 0.5, 0.4))

df |>
  e_charts() |>
  e_liquid(val) |>
  e_theme("dark")

List

Description

simply pass a list of options, similar to a JSON.

Usage

e_list(e, list, append = FALSE)

Arguments

Examples

N <- 20 # data points

opts <- list(
  xAxis = list(
    type = "category",
    data = LETTERS[1:N]
  ),
  yAxis = list(
    type = "value"
  ),
  series = list(
    list(
      type = "line",
      data = round(runif(N, 5, 20))
    )
  )
)

e_charts() |>
  e_list(opts)

Smooth

Description

Plot formulas.

Usage

e_lm(
  e,
  formula,
  name = NULL,
  legend = TRUE,
  symbol = "none",
  smooth = TRUE,
  model_args = list(),
  ...
)

e_glm(
  e,
  formula,
  name = NULL,
  legend = TRUE,
  symbol = "none",
  smooth = TRUE,
  model_args = list(),
  ...
)

e_loess(
  e,
  formula,
  name = NULL,
  legend = TRUE,
  symbol = "none",
  smooth = TRUE,
  x_index = 0,
  y_index = 0,
  model_args = list(),
  ...
)

Arguments

Examples

iris |>
  group_by(Species) |>
  e_charts(Sepal.Length) |>
  e_scatter(Sepal.Width) |>
  e_lm(Sepal.Width ~ Sepal.Length) |>
  e_x_axis(min = 4)

mtcars |>
  e_charts(disp) |>
  e_scatter(mpg, qsec) |>
  e_loess(mpg ~ disp, smooth = TRUE, showSymbol = FALSE)

# timeline
iris |>
  group_by(Species) |>
  e_charts(Sepal.Length, timeline = TRUE) |>
  e_scatter(Sepal.Width) |>
  e_lm(Sepal.Width ~ Sepal.Length) |>
  e_x_axis(min = 4, max = 8) |>
  e_y_axis(max = 5)

Locale

Description

Change the locale to auto-translate days of the week, etc.

Usage

e_locale(e, locale)

e_locale_manual(e, locale, path)

Arguments

Details

The "manual" function expects a file to use for translations. You can browse the '.js' files [here](https://github.com/apache/echarts/tree/master/i18n) to have an idea of what they should look like.

Locales

- CS - DE - EN - ES - FI - FR - JA - PT (brazil) - SI - TH - ZH

Examples

# top right corner zoom is in 
# French
cars |> 
 e_charts(speed) |> 
 e_scatter(dist) |> 
 e_datazoom() |> 
 e_locale("FR")

Choropleth

Description

Draw maps.

Usage

e_map(e, serie, map = "world", name = NULL, rm_x = TRUE, rm_y = TRUE, ...)

e_map_(
  e,
  serie = NULL,
  map = "world",
  name = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

e_svg(e, serie, map = "world", name = NULL, rm_x = TRUE, rm_y = TRUE, ...)

e_svg_(
  e,
  serie = NULL,
  map = "world",
  name = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

e_map_3d(
  e,
  serie,
  map = "world",
  name = NULL,
  coord_system = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

e_map_3d_(
  e,
  serie = NULL,
  map = "world",
  name = NULL,
  coord_system = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

e_map_3d_custom(
  e,
  id,
  value,
  height,
  map = NULL,
  name = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

Arguments

See Also

e_country_names, Additional map arguments, Additional map 3D arguments

Examples

## Not run: 
choropleth <- data.frame(
  countries = c(
    "France",
    "Brazil",
    "China",
    "Russia",
    "Canada",
    "India",
    "United States",
    "Argentina",
    "Australia"
  ),
  values = round(runif(9, 10, 25))
)

choropleth |>
  e_charts(countries) |>
  e_map(values) |>
  e_visual_map(min = 10, max = 25)

choropleth |>
  e_charts(countries) |>
  e_map_3d(values, shading = "lambert") |>
  e_visual_map(min = 10, max = 30)

# custom
buildings <- jsonlite::read_json(
  paste0(
    "https://echarts.apache.org/examples/",
    "data-gl/asset/data/buildings.json"
  )
)

heights <- purrr::map(buildings$features, "properties") |>
  purrr::map("height") |>
  unlist()

names <- purrr::map(buildings$features, "properties") |>
  purrr::map("name") |>
  unlist()

data <- dplyr::tibble(
  name = names,
  value = round(runif(length(names), 0, 1), 6),
  height = heights / 10
)

data |>
  e_charts() |>
  e_map_register("buildings", buildings) |>
  e_map_3d_custom(name, value, height) |>
  e_visual_map(
    show = FALSE,
    min = 0.4,
    max = 1
  )

# timeline
choropleth <- data.frame(
  countries = rep(choropleth$countries, 3)
) |>
  dplyr::mutate(
    grp = c(
      rep(2016, nrow(choropleth)),
      rep(2017, nrow(choropleth)),
      rep(2018, nrow(choropleth))
    ),
    values = runif(27, 1, 10)
  )

choropleth |>
  group_by(grp) |>
  e_charts(countries, timeline = TRUE) |>
  e_map(values) |>
  e_visual_map(min = 1, max = 10)

choropleth |>
  group_by(grp) |>
  e_charts(countries, timeline = TRUE) |>
  e_map_3d(values) |>
  e_visual_map(min = 1, max = 10)

## End(Not run)

Register map

Description

Register a geojson map.

Usage

e_map_register(e, name, json, ...)

e_svg_register(e, name, svg)

e_map_register_p(
  name,
  json,
  async = FALSE,
  session = shiny::getDefaultReactiveDomain()
)

e_map_register_ui(name, json, async = FALSE)

Arguments

Details

e_map_register_p is not truly a proxy as it does not require a chart to function. While the function e_map_register_ui is meant to register the map globally in the Shiny UI, not that then json must be accessible from the UI (generally www folder).

Examples

## Not run: 
json <- jsonlite::read_json("https://echarts.apache.org/examples/data/asset/geo/USA.json")

USArrests |>
  tibble::rownames_to_column("states") |> 
  e_charts(states) |>
  e_map_register("USA", json) |>
  e_map(Murder, map = "USA") |>
  e_visual_map(Murder)

## End(Not run)

Mark

Description

Mark points, lines, and areas with a proxy ([echarts4rProxy()]).

Usage

e_mark_p(e, type, serie_index, data, ...)

e_mark_p_(e, type, serie_index, data = NULL, ...)

Arguments

Details

Allows the three type of marks to work with [echarts4rProxy()]

Examples

library(shiny)
library(dplyr)

ui <- fluidPage(
  fluidRow(
    column(3, actionButton("pxy", "Marks")),
    column(
      3,
      checkboxInput("tln", "Timeline", value = FALSE)
    )
  ),
  echarts4rOutput("plot")
)

server <- function(input, output) {
  data(EuStockMarkets)

  bb <- as.data.frame(EuStockMarkets) |>
    slice_head(n = 150) |>
    mutate(day = 1:n())

  output$plot <- renderEcharts4r({
    react()
  })

  observeEvent(input$pxy, {
    echarts4rProxy("plot", data = NULL) |>
      e_mark_p(
        type = "line",
        serie_index = 1,
        data = list(type = "average"),
        lineStyle = list(type = "dashed", color = "cyan")
      ) |>
      e_mark_p(
        serie_index = 2,
        data = list(
          xAxis = bb$day[60],
          yAxis = bb$SMI[60],
          value = "pnt"
        )
      ) |>
      e_mark_p(
        type = "line",
        serie_index = 2,
        data = list(
          list(xAxis = bb$day[10], yAxis = bb$SMI[10]),
          list(xAxis = bb$day[37], yAxis = bb$SMI[37])
        ),
        lineStyle = list(type = "solid", color = "yellow")
      ) |>
      e_mark_p(
        type = "area",
        serie_index = 1,
        data = list(
          list(xAxis = bb$day[95]),
          list(xAxis = bb$day[105])
        ),
        itemStyle = list(color = "lightblue"),
        label = list(formatter = "X-area", position = "middle")
      ) |>
      e_merge()
  })

  react <- eventReactive(input$tln, {
    tmp <- bb
    if (input$tln) tmp <- tmp |> group_by(day < 75)

    tmp |>
      e_charts(
        day,
        backgroundColor = "#181818",
        legend = list(textStyle = list(color = "#aaa")),
        timeline = input$tln
      ) |>
      e_y_axis(scale = TRUE, axisLabel = list(color = "#aaa")) |>
      e_line(CAC, symbol = "none", color = "#ff33b8") |>
      e_line(SMI, symbol = "none", color = "green")
  })
}
if (interactive()) {
  shinyApp(ui, server)
}

Mark point

Description

Mark points and lines.

Usage

e_mark_point(
  e,
  serie = NULL,
  data = NULL,
  ...,
  title = NULL,
  title_position = NULL
)

e_mark_line(
  e,
  serie = NULL,
  data = NULL,
  ...,
  title = NULL,
  title_position = NULL
)

e_mark_area(
  e,
  serie = NULL,
  data = NULL,
  ...,
  title = NULL,
  title_position = NULL
)

Arguments

Details

To set a label you need to either use the title argument or pass a list specifying the label formatter. label = list(formatter = "label"). The former is more convenient but more limited, e.g.: you cannot specify the placement of the label. When the e_mark series function is used with e_timeline at the same time, if the number of marks provided does not match the series, the mark information will follow the setting of the previous frame.

See Also

Additional point arguments, Additional line arguments

Examples

max <- list(
  name = "Max",
  type = "max"
)

min <- list(
  name = "Min",
  type = "min"
)

avg <- list(
  type = "average",
  name = "AVG"
)

mtcars |>
  e_charts(mpg) |>
  e_line(wt) |>
  e_line(drat) |>
  e_line(cyl) |>
  e_mark_point("wt", data = max) |>
  e_mark_point(c("cyl", "drat"), data = min) |>
  e_mark_line(data = avg) |> # applies to all
  e_mark_area(
    serie = "wt",
    data = list(
      list(xAxis = "min", yAxis = "min"),
      list(xAxis = "max", yAxis = "max")
    )
  )

# Serie options, since the mark of "virginica" is not set, the mark setting 
# of the previous frame is used
iris |>
  group_by(Species) |>
  e_charts(Sepal.Length, timeline = TRUE) |>
  e_line(Sepal.Width) |>
  e_timeline_serie(
    title = list(
      list(text = "setosa"),
      list(text = "versicolor"),
      list(text = "virginica")
    )
  ) |>
  e_mark_area(
    serie = "setosa",
    data = list(
      list(xAxis = 4, yAxis = 2),
      list(xAxis = 6, yAxis = 4.5)
    ),
    itemStyle = list(color = "lightgreen")
  ) |>
  e_mark_area(
    serie = "versicolor",
    data = list(
      list(xAxis = 4.5),
      list(xAxis = 7)
    ),
    itemStyle = list(color = "lightblue")
  )

Merge options in chart, used in e_mark

Description

Merge options in chart, used in e_mark

Usage

e_merge(proxy)

Arguments

Modularity

Description

Graph modularity extension will do community detection and partian a graph's vertices in several subsets. Each subset will be assigned a different color.

Usage

e_modularity(e, modularity = TRUE)

Arguments

Modularity

• resolution Resolution

• sort Whether to sort to comunities

Note

Does not work in RStudio viewer, open in browser.

See Also

Official documentation

Examples

nodes <- data.frame(
  name = paste0(LETTERS, 1:100),
  value = rnorm(100, 10, 2),
  stringsAsFactors = FALSE
)

edges <- data.frame(
  source = sample(nodes$name, 200, replace = TRUE),
  target = sample(nodes$name, 200, replace = TRUE),
  stringsAsFactors = FALSE
)

e_charts() |>
  e_graph() |>
  e_graph_nodes(nodes, name, value) |>
  e_graph_edges(edges, source, target) |>
  e_modularity(
    list(
      resolution = 5,
      sort = TRUE
    )
  )

Morphing

Description

__This is experimental__

Usage

e_morph(e, ..., callback, default = 1L)

Arguments

Details

Morph between graphs.

Examples

mtcars2 <- mtcars |> 
  head() |> 
  tibble::rownames_to_column("model")

e1 <- mtcars2 |> 
  e_charts(model) |> 
  e_bar(
    carb, 
    universalTransition = TRUE,
    animationDurationUpdate = 1000L
  )

e2 <- mtcars2 |> 
  e_charts(model) |> 
  e_pie(
    carb, 
    universalTransition = TRUE,
    animationDurationUpdate = 1000L
  )

cb <- "() => {
  let x = 0;
  setInterval(() => {
    x++
    chart.setOption(opts[x % 2], true);
  }, 3000);
}"

e_morph(e1, e2, callback = cb)

Parallel

Description

Draw parallel coordinates.

Usage

e_parallel(e, ..., name = NULL, rm_x = TRUE, rm_y = TRUE, opts = list())

e_parallel_(e, ..., name = NULL, rm_x = TRUE, rm_y = TRUE, opts = list())

Arguments

See Also

Additional arguments

Examples

df <- data.frame(
  price = rnorm(5, 10),
  amount = rnorm(5, 15),
  letter = LETTERS[1:5]
)

df |>
  e_charts() |>
  e_parallel(price, amount, letter, opts = list(smooth = TRUE))

Pictorial

Description

Pictorial bar chart is a type of bar chart that custimzed glyph (like images, SVG PathData) can be used instead of rectangular bar.

Usage

e_pictorial(
  e,
  serie,
  symbol,
  bind,
  name = NULL,
  legend = TRUE,
  y_index = 0,
  x_index = 0,
  ...
)

e_pictorial_(
  e,
  serie,
  symbol,
  bind = NULL,
  name = NULL,
  legend = TRUE,
  y_index = 0,
  x_index = 0,
  ...
)

Arguments

Symbols

• Built-in circle, rect, roundRect, triangle, diamond, pin, arrow.

• SVG Path

• Images Path to image, don't forget to precede it with image://, see examples.

See Also

Additional arguments

Examples

# built-in symbols
y <- rnorm(10, 10, 2)
df <- data.frame(
  x = 1:10,
  y = y,
  z = y - rnorm(10, 5, 1)
)

df |>
  e_charts(x) |>
  e_bar(z, barWidth = 10) |>
  e_pictorial(
    y,
    symbol = "rect",
    symbolRepeat = TRUE,
    z = -1,
    symbolSize = c(10, 4)
  ) |>
  e_theme("westeros")

# svg path
path <- "path://M0,10 L10,10 C5.5,10 5.5,5 5,0 C4.5,5 4.5,10 0,10 z"

style <- list(
  normal = list(opacity = 0.5),
  # normal
  emphasis = list(opacity = 1) # on hover
)

df |>
  e_charts(x) |>
  e_pictorial(
    y,
    symbol = path,
    barCategoryGap = "-130%",
    itemStyle = style
  )

# image
# might not work in RStudio viewer
# open in browser
qomo <- paste0(
  "https://ecomfe.github.io/echarts-examples/public/",
  "data/asset/img/hill-Qomolangma.png"
)

kili <- paste0(
  "https://ecomfe.github.io/echarts-examples/public/",
  "data/asset/img/hill-Kilimanjaro.png"
)

data <- data.frame(
  x = c("Qomolangma", "Kilimanjaro"),
  value = c(8844, 5895),
  symbol = c(
    paste0("image://", qomo),
    paste0("image://", kili)
  )
)

data |>
  e_charts(x) |>
  e_pictorial(value, symbol) |>
  e_legend(FALSE)

# timeline
df <- data.frame(
  x = rep(1:5, 2),
  y = runif(10, 1, 10),
  year = c(
    rep(2017, 5),
    rep(2018, 5)
  )
)

df |>
  group_by(year) |>
  e_charts(x, timeline = TRUE) |>
  e_pictorial(
    y,
    symbol = "rect",
    symbolRepeat = TRUE,
    z = -1,
    symbolSize = c(10, 4)
  )

Pie

Description

Draw pie and donut charts.

Usage

e_pie(e, serie, name = NULL, legend = TRUE, rm_x = TRUE, rm_y = TRUE, ...)

e_pie_(e, serie, name = NULL, legend = TRUE, rm_x = TRUE, rm_y = TRUE, ...)

Arguments

See Also

Additional arguments

Examples

mtcars |>
  head() |>
  tibble::rownames_to_column("model") |> 
  e_charts(model) |>
  e_pie(carb)

# timeline
df <- data.frame(
  grp = c("A", "A", "A", "B", "B", "B"),
  labels = rep(LETTERS[1:3], 2),
  values = runif(6, 1, 5)
)

df |>
  group_by(grp) |>
  e_charts(labels, timeline = TRUE) |>
  e_pie(values)

Polar

Description

Customise polar coordinates.

Usage

e_polar(e, show = TRUE, ...)

Arguments

See Also

Additional arguments

Examples

df <- data.frame(x = 1:10, y = seq(1, 20, by = 2))

df |>
  e_charts(x) |>
  e_polar() |>
  e_angle_axis() |>
  e_radius_axis() |>
  e_line(y, coord.system = "polar", smooth = TRUE)

Radar

Description

Add a radar chart

Usage

e_radar(
  e,
  serie,
  max = 100,
  name = NULL,
  legend = TRUE,
  rm_x = TRUE,
  rm_y = TRUE,
  ...,
  radar = list()
)

e_radar_(
  e,
  serie,
  max = 100,
  name = NULL,
  legend = TRUE,
  rm_x = TRUE,
  rm_y = TRUE,
  ...,
  radar = list()
)

Arguments

Examples

df <- data.frame(
  x = LETTERS[1:5],
  y = runif(5, 1, 5),
  z = runif(5, 3, 7)
)

df |>
  e_charts(x) |>
  e_radar(y, max = 7) |>
  e_radar(z) |>
  e_tooltip(trigger = "item")

Radar axis

Description

Radar axis setup and options.

Usage

e_radar_opts(e, index = 0, ...)

Arguments

Examples

df <- data.frame(
  x = LETTERS[1:5],
  y = runif(5, 1, 5),
  z = runif(5, 3, 7)
)

df |>
  e_charts(x) |>
  e_radar(y, max = 7) |>
  e_radar(z) |>
  e_radar_opts(center = c("25%", "25%")) |>
  e_tooltip(trigger = "item")

Remove Serie

Description

Remove a serie by name or precising its index.

Usage

e_remove_serie_p(proxy, serie_name = NULL, serie_index = NULL)

e_remove_serie(proxy, serie_name = NULL, serie_index = NULL)

Arguments

Examples

library(shiny)

ui <- fluidPage(
  actionButton("rm", "Remove z serie"),
  echarts4rOutput("plot")
)

server <- function(input, output, session) {
  data <- data.frame(
    x = rnorm(10, 5, 3),
    y = rnorm(10, 50, 12),
    z = rnorm(10, 50, 5)
  )

  output$plot <- renderEcharts4r({
    data |>
      e_charts(x) |>
      e_scatter(y) |>
      e_scatter(z)
  })

  observeEvent(input$rm, {
    echarts4rProxy("plot") |>
      e_remove_serie_p(serie_name = "z")
  })
}
## Not run: 
shinyApp(ui, server)

## End(Not run)

Resize

Description

Force resize the chart.

Usage

e_resize(proxy)

Arguments

Restore Toolbox

Description

Restore Toolbox.

Usage

e_restore(e, btn = NULL)

Arguments

Examples

cars |>
  e_charts(speed) |>
  e_scatter(dist) |>
  e_datazoom() |>
  e_restore("btn") |>
  e_button("btn", "Reset")

River

Description

Build a theme river.

Usage

e_river(e, serie, name = NULL, legend = TRUE, rm_x = TRUE, rm_y = TRUE, ...)

e_river_(e, serie, name = NULL, legend = TRUE, rm_x = TRUE, rm_y = TRUE, ...)

Arguments

See Also

Additional arguments

Examples

dates <- seq.Date(Sys.Date() - 30, Sys.Date(), by = "day")
grps <- lapply(LETTERS[1:3], rep, 31) |> unlist()

df <- data.frame(
  dates = rep(dates, 3),
  groups = grps,
  values = runif(length(grps), 1, 50)
)

df |>
  group_by(groups) |>
  e_charts(dates) |>
  e_river(values) |>
  e_tooltip(trigger = "axis")

Sankey

Description

Draw a sankey diagram.

Usage

e_sankey(
  e,
  source,
  target,
  value,
  layout = "none",
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

e_sankey_(
  e,
  source,
  target,
  value,
  layout = "none",
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

Arguments

See Also

Additional arguments

Examples

sankey <- data.frame(
  source = c("a", "b", "c", "d", "c"),
  target = c("b", "c", "d", "e", "e"),
  value = ceiling(rnorm(5, 10, 1)),
  stringsAsFactors = FALSE
)

sankey |>
  e_charts() |>
  e_sankey(source, target, value)

Scatter

Description

Add scatter serie.

Usage

e_scatter(
  e,
  serie,
  size,
  bind,
  symbol = NULL,
  symbol_size = 1,
  scale = e_scale,
  scale_js = "function(data){ return data[3];}",
  name = NULL,
  coord_system = "cartesian2d",
  jitter_factor = 0,
  jitter_amount = NULL,
  legend = TRUE,
  y_index = 0,
  x_index = 0,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

e_effect_scatter(
  e,
  serie,
  size,
  bind,
  symbol = NULL,
  symbol_size = 1,
  scale = e_scale,
  scale_js = "function(data){ return data[3];}",
  name = NULL,
  coord_system = "cartesian2d",
  legend = TRUE,
  y_index = 0,
  x_index = 0,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

e_scale(x)

e_scatter_(
  e,
  serie,
  size = NULL,
  bind = NULL,
  symbol = NULL,
  symbol_size = 1,
  scale = e_scale,
  scale_js = "function(data){ return data[3];}",
  name = NULL,
  coord_system = "cartesian2d",
  jitter_factor = 0,
  jitter_amount = NULL,
  legend = TRUE,
  y_index = 0,
  x_index = 0,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

e_effect_scatter_(
  e,
  serie,
  size = NULL,
  bind = NULL,
  symbol = NULL,
  symbol_size = 1,
  scale = e_scale,
  scale_js = "function(data){ return data[3];}",
  name = NULL,
  coord_system = "cartesian2d",
  legend = TRUE,
  y_index = 0,
  x_index = 0,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

Arguments

Scaling function

defaults to e_scale which is a basic function that rescales size between 1 and 20 for that makes for decent sized points on the chart.

See Also

Additional arguments scatter, Additional arguments for effect scatter

Examples

# scaling
e_scale(c(1, 1000))

mtcars |>
  e_charts(mpg) |>
  e_scatter(wt, qsec)

# custom function
my_scale <- function(x) scales::rescale(x, to = c(2, 50))

echart <- mtcars |>
  e_charts(mpg) |>
  e_scatter(wt, qsec, scale = my_scale)

echart

# rescale color too
echart |>
  e_visual_map(wt, scale = my_scale)

# or
echart |>
  e_visual_map(min = 2, max = 50)

# disable scaling
mtcars |>
  e_charts(qsec) |>
  e_scatter(wt, mpg, scale = NULL)

# jitter point
mtcars |>
  e_charts(cyl) |>
  e_scatter(wt, symbol_size = 5) |>
  e_scatter(wt, jitter_factor = 2, legend = FALSE)

# examples
USArrests |>
  e_charts(Assault) |>
  e_scatter(Murder, Rape) |>
  e_effect_scatter(Rape, Murder, y_index = 1) |>
  e_grid(index = c(0, 1)) |>
  e_tooltip()

iris |>
  e_charts_("Sepal.Length") |>
  e_scatter_(
    "Sepal.Width",
    symbol_size = c(8, 2),
    symbol = "rect"
  ) |>
  e_x_axis(min = 4)

quakes |>
  e_charts(long) |>
  e_geo(
    roam = TRUE,
    boundingCoords = list(
      c(185, -10),
      c(165, -40)
    )
  ) |>
  e_scatter(lat, mag, coord_system = "geo") |>
  e_visual_map(min = 4, max = 6.5)

# timeline
iris |>
  group_by(Species) |>
  e_charts(Petal.Width, timeline = TRUE) |>
  e_scatter(Sepal.Width, Sepal.Length) |>
  e_tooltip(trigger = "axis")

Scatter 3D

Description

Add 3D scatter.

Usage

e_scatter_3d(
  e,
  y,
  z,
  color,
  size,
  bind,
  coord_system = "cartesian3D",
  name = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  legend = FALSE,
  ...
)

e_scatter_3d_(
  e,
  y,
  z,
  color = NULL,
  size = NULL,
  bind = NULL,
  coord_system = "cartesian3D",
  name = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  legend = FALSE,
  ...
)

Arguments

See Also

Additional arguments

Examples

v <- LETTERS[1:10]
matrix <- data.frame(
  x = sample(v, 300, replace = TRUE),
  y = sample(v, 300, replace = TRUE),
  z = rnorm(300, 10, 1),
  color = rnorm(300, 10, 1),
  size = rnorm(300, 10, 1),
  stringsAsFactors = FALSE
) |>
  dplyr::group_by(x, y) |>
  dplyr::summarise(
    z = sum(z),
    color = sum(color),
    size = sum(size)
  ) |>
  dplyr::ungroup()

matrix |>
  e_charts(x) |>
  e_scatter_3d(y, z, size, color) |>
  e_visual_map(
    min = 1,
    max = 100,
    inRange = list(symbolSize = c(1, 30)),
    # scale size
    dimension = 3 # third dimension 0 = x, y = 1, z = 2, size = 3
  ) |>
  e_visual_map(
    min = 1,
    max = 100,
    inRange = list(color = c("#bf444c", "#d88273", "#f6efa6")),
    # scale colors
    dimension = 4,
    # third dimension 0 = x, y = 1, z = 2, size = 3, color = 4
    bottom = 300 # padding to avoid visual maps overlap
  )

airports <- read.csv(
  paste0(
    "https://raw.githubusercontent.com/plotly/datasets/",
    "master/2011_february_us_airport_traffic.csv"
  )
)

airports |>
  e_charts(long) |>
  e_globe(
    globeOuterRadius = 100
  ) |>
  e_scatter_3d(lat, cnt, coord_system = "globe", blendMode = "lighter") |>
  e_visual_map(inRange = list(symbolSize = c(1, 10)))

# timeline
airports |>
  group_by(state) |>
  e_charts(long, timeline = TRUE) |>
  e_globe(
    globeOuterRadius = 100
  ) |>
  e_scatter_3d(lat, cnt, coord_system = "globe", blendMode = "lighter") |>
  e_visual_map(inRange = list(symbolSize = c(1, 10)))

Scatter GL

Description

Draw scatter GL.

Usage

e_scatter_gl(
  e,
  y,
  z,
  name = NULL,
  coord_system = "geo",
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

e_scatter_gl_(
  e,
  y,
  z,
  name = NULL,
  coord_system = "geo",
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

Arguments

See Also

Additional arguments

Examples

quakes |>
  e_charts(long) |>
  e_geo(
    roam = TRUE,
    boundingCoords = list(
      c(185, -10),
      c(165, -40)
    )
  ) |>
  e_scatter_gl(lat, depth)

# timeline
quakes$year <- rep(c("2017", "2018"), 500)

quakes |>
  group_by(year) |>
  e_charts(long, timeline = TRUE) |>
  e_geo(
    roam = TRUE,
    boundingCoords = list(
      c(185, -10),
      c(165, -40)
    )
  ) |>
  e_scatter_gl(lat, depth)

Loading

Description

Show or hide loading.

Usage

e_show_loading(
  e,
  hide_overlay = TRUE,
  text = "loading",
  color = "#c23531",
  text_color = "#000",
  mask_color = "rgba(255, 255, 255, 0.8)",
  zlevel = 0
)

e_hide_loading(e)

Arguments

Details

This only applies to Shiny.

Examples

## Not run: 

# no redraw
# no loading
library(shiny)
ui <- fluidPage(
  fluidRow(
    column(12, actionButton("update", "Update"))
  ),
  fluidRow(
    column(12, echarts4rOutput("plot"))
  )
)

server <- function(input, output) {
  data <- eventReactive(input$update, {
    data.frame(
      x = 1:10,
      y = rnorm(10)
    )
  })

  output$plot <- renderEcharts4r({
    data() |>
      e_charts(x) |>
      e_bar(y)
  })
}

if (interactive()) {
  shinyApp(ui, server)
}

# add loading
server <- function(input, output) {
  data <- eventReactive(input$update, {
    Sys.sleep(1) # sleep one second to show loading
    data.frame(
      x = 1:10,
      y = rnorm(10)
    )
  })

  output$plot <- renderEcharts4r({
    data() |>
      e_charts(x) |>
      e_bar(y) |>
      e_show_loading()
  })
}

if (interactive()) {
  shinyApp(ui, server)
}

## End(Not run)

Tooltip Proxy

Description

Proxies to show or hide tooltip.

Usage

e_showtip_p(proxy, ...)

e_hidetip_p(proxy)

Arguments

Examples

## Not run: 
library(shiny)

ui <- fluidPage(
  fluidRow(
    actionButton("show", "Show tooltip"),
    actionButton("hide", "Hide tooltip")
  ),
  fluidRow(
    echarts4rOutput("plot"),
    h3("clicked Data"),
    verbatimTextOutput("clickedData"),
    h3("clicked Serie"),
    verbatimTextOutput("clickedSerie"),
    h3("clicked Row"),
    verbatimTextOutput("clickedRow")
  )
)

server <- function(input, output, session) {
  output$plot <- renderEcharts4r({
    mtcars |>
      e_charts(mpg) |>
      e_line(disp, bind = carb, name = "displacement") |>
      e_line(hp) |>
      e_x_axis(min = 10) |>
      e_tooltip(show = FALSE) |>
      e_theme("westeros")
  })

  observeEvent(input$show, {
    echarts4rProxy("plot") |>
      e_showtip_p(
        name = "displacement",
        position = list(5, 5)
      )
  })

  observeEvent(input$hide, {
    echarts4rProxy("plot") |>
      e_hidetip_p()
  })

  output$clickedData <- renderPrint({
    input$plot_clicked_data
  })

  output$clickedSerie <- renderPrint({
    input$plot_clicked_serie
  })

  output$clickedRow <- renderPrint({
    input$plot_clicked_row
  })
}

if (interactive()) {
  shinyApp(ui, server)
}

## End(Not run)

Single Axis

Description

Setup single axis.

Usage

e_single_axis(e, index = 0, ...)

Arguments

Examples

df <- data.frame(
  axis = LETTERS[1:10],
  value = runif(10, 3, 20),
  size = runif(10, 3, 20)
)

df |>
  e_charts(axis) |>
  e_single_axis() |> # add the single axis
  e_scatter(
    value,
    size,
    coord_system = "singleAxis"
  )

Step

Description

Add step serie.

Usage

e_step(
  e,
  serie,
  bind,
  step = c("start", "middle", "end"),
  fill = FALSE,
  name = NULL,
  legend = TRUE,
  y_index = 0,
  x_index = 0,
  coord_system = "cartesian2d",
  ...
)

e_step_(
  e,
  serie,
  bind = NULL,
  step = c("start", "middle", "end"),
  fill = FALSE,
  name = NULL,
  legend = TRUE,
  y_index = 0,
  x_index = 0,
  coord_system = "cartesian2d",
  ...
)

Arguments

See Also

Additional arguments

Examples

USArrests |>
  tibble::rownames_to_column("State") |> 
  e_charts(State) |>
  e_step(Murder, name = "Start", step = "start", fill = TRUE) |>
  e_step(Rape, name = "Middle", step = "middle") |>
  e_step(Assault, name = "End", step = "end") |>
  e_tooltip(trigger = "axis")

# timeline
iris |>
  group_by(Species) |>
  e_charts(Sepal.Length, timeline = TRUE) |>
  e_step(Sepal.Width) |>
  e_tooltip(trigger = "axis")

Sunburst

Description

Build a sunburst.

Usage

e_sunburst(
  e,
  styles = NULL,
  names = NULL,
  levels = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

e_sunburst_(
  e,
  styles = NULL,
  names = NULL,
  levels = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

Arguments

Details

Charts e_sunburst, e_treemap and e_tree require hierarchical input data. Such structure could be represented thru json lists or nested tibbles (data.frame). Input data may contain styles, see itemStyle in examples jsonl and df below. The number of lists in the styles parameter should match the number of elements in names and/or levels. If both names and levels are present, name styles will take precedence over level styles. Multiple names may have the same style, see c('land','river') below. Multiple levels may have the same style, see c(3,4) below. styles lists contain items such as color, or borderColor as specified in the official documentation.

See Also

Additional arguments

Examples

# json list hierarchical data representation
jsonl <- jsonlite::fromJSON('[
  {"name": "earth", "value": 30,
    "children": [
      {"name": "land", "value":10,
        "children": [
                {"name": "forest", "value": 3},
                {"name": "river", "value": 7}
        ]},
      {"name": "ocean", "value":20,
        "children": [
          {"name": "fish", "value": 10,
            "children": [
              {"name": "shark", "value":2},
              {"name": "tuna", "value":6}
            ]},
          {"name": "kelp", "value": 5}
        ]}
    ]
  },
  {"name": "mars", "value": 30,
    "children": [
      {"name": "crater", "value": 20},
      {"name": "valley", "value": 20}
    ]},
  {"name": "venus", "value": 40, "itemStyle": {"color": "blue"} }
]', simplifyDataFrame = FALSE)

jsonl |>
  e_charts() |>
  e_sunburst() # demo


# tibble hierarchical data representation
library(dplyr)
df <- tibble(
  name = c("earth", "mars", "venus"),
  value = c(30, 40, 30),
  # 1st level
  itemStyle = tibble(color = c(NA, "red", "blue")),
  # embedded styles, optional
  children = list(
    tibble(
      name = c("land", "ocean"),
      value = c(10, 20),
      # 2nd level
      children = list(
        tibble(name = c("forest", "river"), value = c(3, 7)),
        # 3rd level
        tibble(
          name = c("fish", "kelp"),
          value = c(10, 5),
          children = list(
            tibble(name = c("shark", "tuna"), value = c(2, 6)),
            # 4th level
            NULL # kelp
          )
        )
      )
    ),
    tibble(name = c("crater", "valley"), value = c(20, 20)),
    NULL # venus
  )
)

df |>
  e_charts() |>
  e_sunburst() |>
  e_theme("westeros")

# with styles
myStyles <- c(list(color = "green"), list(color = "magenta")) # custom styles defined
myNames <- list(c("land", "river"), "crater") # names to style
myLevels <- list(2, c(3, 4)) # hierarchical levels to style

df |>
  e_charts() |>
  e_sunburst(myStyles, myNames, myLevels)

Surface

Description

Add a surface plot.

Usage

e_surface(e, y, z, bind, name = NULL, rm_x = TRUE, rm_y = TRUE, ...)

e_surface_(e, y, z, bind = NULL, name = NULL, rm_x = TRUE, rm_y = TRUE, ...)

Arguments

Examples

data("volcano")

surface <- as.data.frame(as.table(volcano))
surface$Var1 <- as.numeric(surface$Var1)
surface$Var2 <- as.numeric(surface$Var2)

surface |>
  e_charts(Var1) |>
  e_surface(Var2, Freq) |>
  e_visual_map(Freq)

Text style

Description

Define global font style.

Usage

e_text_style(e, ...)

Arguments

Note

Do not use e_arrange in R markdown or Shiny.

See Also

official documentation

Examples

cars |>
  e_charts(dist) |>
  e_scatter(speed) |>
  e_labels() |>
  e_text_style(
    color = "blue",
    fontStyle = "italic"
  )

Themes

Description

Add a custom theme or apply a pre-built one.

Usage

e_theme(
  e,
  name = c("auritus", "azul", "bee-inspired", "blue", "caravan", "carp", "chalk", "cool",
    "dark-blue", "dark-bold", "dark-digerati", "dark-fresh-cut", "dark-mushroom", "dark",
    "eduardo", "essos", "forest", "fresh-cut", "fruit", "gray", "green", "halloween",
    "helianthus", "infographic", "inspired", "jazz", "london", "macarons", "macarons2",
    "mint", "purple-passion", "red-velvet", "red", "roma", "royal", "sakura", "shine",
    "tech-blue", "vintage", "walden", "wef", "weforum", "westeros", "wonderland")
)

e_theme_custom(e, theme, name = "custom")

e_theme_register(theme, name = "custom")

Arguments

Details

The function e_theme_register can be used to register the theme globally in R markdown or shiny (UI). This is useful because 1) the e_theme_custom registers the theme every time and is more computationally expensive.

Functions

• e_theme - Use a default theme by name.

• e_theme_custom - Use a custom theme.

• e_theme_register - Register a theme globally in shiny or R markdown.

See Also

create your own theme.

Examples

mtcars |>
  e_charts(mpg) |>
  e_line(disp) |>
  e_area(hp) |>
  e_x_axis(min = 10) -> p

p |> e_theme("chalk")
p |> e_theme_custom('{"color":["#ff715e","#ffaf51"]}')

Title

Description

Add title.

Usage

e_title(e, text = NULL, subtext = NULL, link = NULL, sublink = NULL, ...)

Arguments

See Also

Additional arguments

Examples

quakes |>
  dplyr::mutate(mag = exp(mag) / 60) |>
  e_charts(stations) |>
  e_scatter(depth, mag) |>
  e_visual_map(min = 3, max = 7) |>
  e_title("Quakes", "Stations and Magnitude")

Toolbox

Description

Add toolbox interface.

Usage

e_toolbox_feature(e, feature, ...)

e_toolbox(e, ...)

Arguments

Details

Valid feature:

• saveAsImage

• brush

• restore

• dataView

• dataZoom

• magicType

See Also

Additional arguments

Examples

USArrests |>
  e_charts(UrbanPop) |>
  e_line(Assault) |>
  e_area(Murder, y_index = 1, x_index = 1) |>
  e_datazoom(x_index = 0)

mtcars |>
  tibble::rownames_to_column("model") |> 
  e_charts(model) |>
  e_line(qsec) |>
  e_toolbox() |>
  e_toolbox_feature(
    feature = "magicType",
    type = list("line", "bar")
  )

Tooltip

Description

Customise tooltip

Usage

e_tooltip(e, trigger = c("item", "axis"), formatter = NULL, ...)

e_tooltip_item_formatter(
  style = c("decimal", "percent", "currency"),
  digits = 0,
  locale = NULL,
  currency = "USD"
)

e_tooltip_choro_formatter(
  style = c("decimal", "percent", "currency"),
  digits = 0,
  locale = NULL,
  currency = "USD"
)

e_tooltip_pie_formatter(
  style = c("decimal", "percent", "currency"),
  digits = 0,
  locale = NULL,
  currency = "USD",
  ...
)

e_tooltip_pointer_formatter(
  style = c("decimal", "percent", "currency"),
  digits = 0,
  locale = NULL,
  currency = "USD"
)

Arguments

Formatters

• e_tooltip_pie_formatter: special helper for e_pie.

• e_tooltip_item_formatter: general helper, this is passed to the tooltip formatter.

• e_tooltip_pointer_formatter: helper for pointer, this is passed to the label parameter under axisPointer.

See Also

Additional arguments

Examples

# basic
USArrests |>
  e_charts(Assault) |>
  e_scatter(Murder) |>
  e_tooltip()

# formatter
cars |>
  dplyr::mutate(
    dist = dist / 120
  ) |>
  e_charts(speed) |>
  e_scatter(dist, symbol_size = 5) |>
  e_tooltip(
    formatter = e_tooltip_item_formatter("percent")
  )

# axis pointer
cars |>
  e_charts(speed) |>
  e_scatter(dist, symbol_size = 5) |>
  e_tooltip(
    formatter = e_tooltip_pointer_formatter("currency"),
    axisPointer = list(
      type = "cross"
    )
  )

Tree

Description

Build a tree.

Usage

e_tree(e, rm_x = TRUE, rm_y = TRUE, ...)

e_tree_(e, rm_x = TRUE, rm_y = TRUE, ...)

Arguments

See Also

Additional arguments

Examples

library(dplyr)
df <- tibble(
  name = "earth",
  # 1st level
  children = list(
    tibble(
      name = c("land", "ocean"),
      # 2nd level
      children = list(
        tibble(name = c("forest", "river")),
        # 3rd level
        tibble(
          name = c("fish", "kelp"),
          children = list(
            tibble(
              name = c("shark", "tuna")
              ),
              # 4th level
              NULL # kelp
          )
        )
      )
    )
  )
)

df |>
  e_charts() |>
  e_tree(initialTreeDepth = 3, label = list(offset = c(0, -11)))

Treemap

Description

Build a treemap.

Usage

e_treemap(
  e,
  styles = NULL,
  names = NULL,
  levels = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

e_treemap_(
  e,
  styles = NULL,
  names = NULL,
  levels = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  ...
)

Arguments

See Also

Additional arguments

Examples

library(dplyr)
df <- tibble(
  name = c("earth", "mars", "venus"),
  value = c(30, 40, 30),
  # 1st level
  itemStyle = tibble(color = c(NA, "red", "blue")),
  # embedded styles, optional
  children = list(
    tibble(
      name = c("land", "ocean"),
      value = c(10, 20),
      # 2nd level
      children = list(
        tibble(name = c("forest", "river"), value = c(3, 7)),
        # 3rd level
        tibble(
          name = c("fish", "kelp"),
          value = c(10, 5),
          children = list(
            tibble(name = c("shark", "tuna"), value = c(2, 6)),
            # 4th level
            NULL # kelp
          )
        )
      )
    ),
    tibble(name = c("crater", "valley"), value = c(20, 20)),
    NULL # venus
  )
)

df |>
  e_charts() |>
  e_treemap()

Use UTC

Description

Use UTC

Usage

e_utc(e)

Arguments

Visual Map

Description

Visual Map

Usage

e_visual_map(
  e,
  serie,
  calculable = TRUE,
  type = c("continuous", "piecewise"),
  scale = NULL,
  ...
)

e_visual_map_(
  e,
  serie = NULL,
  calculable = TRUE,
  type = c("continuous", "piecewise"),
  scale = NULL,
  ...
)

Arguments

Scaling function

defaults to e_scale which is a basic function that rescales size between 1 and 20 for that makes for decent sized points on the chart.

See Also

Additional arguments

Examples

# scaled data
mtcars |>
  e_charts(mpg) |>
  e_scatter(wt, qsec, scale = e_scale) |>
  e_visual_map(qsec, scale = e_scale)

# dimension
# color according to y axis
mtcars |>
  e_charts(mpg) |>
  e_scatter(wt) |>
  e_visual_map(wt, dimension = 1)

# color according to x axis
mtcars |>
  e_charts(mpg) |>
  e_scatter(wt) |>
  e_visual_map(mpg, dimension = 0)

v <- LETTERS[1:10]
matrix <- data.frame(
  x = sample(v, 300, replace = TRUE),
  y = sample(v, 300, replace = TRUE),
  z = rnorm(300, 10, 1),
  color = rnorm(300, 10, 1),
  size = rnorm(300, 10, 1),
  stringsAsFactors = FALSE
) |>
  dplyr::group_by(x, y) |>
  dplyr::summarise(
    z = sum(z),
    color = sum(color),
    size = sum(size)
  ) |>
  dplyr::ungroup()

matrix |>
  e_charts(x) |>
  e_scatter_3d(y, z, color, size) |>
  e_visual_map(
    z,
    # scale to z
    inRange = list(symbolSize = c(1, 30)),
    # scale size
    dimension = 3 # third dimension 0 = x, y = 1, z = 2, size = 3
  ) |>
  e_visual_map(
    z,
    # scale to z
    inRange = list(color = c("#bf444c", "#d88273", "#f6efa6")),
    # scale colors
    dimension = 4,
    # third dimension 0 = x, y = 1, z = 2, size = 3, color = 4
    bottom = 300 # padding to avoid visual maps overlap
  )

Select Visual Map

Description

Selects data range of visual mapping.

Usage

e_visual_map_range(e, ..., btn = NULL)

Arguments

Examples

data("state")

as.data.frame(state.x77) |>
  e_charts(Population) |>
  e_scatter(Income, Frost) |>
  e_visual_map(Frost, scale = e_scale) |>
  e_legend(FALSE) |>
  e_visual_map_range(
    selected = list(60, 120)
  )

Zoom

Description

Zoom on a region.

Usage

e_zoom(e, ..., btn = NULL)

Arguments

Examples

cars |>
  e_charts(dist) |>
  e_scatter(speed) |>
  e_datazoom() |>
  e_zoom(
    dataZoomIndex = 0,
    start = 20,
    end = 40,
    btn = "BUTTON"
  ) |>
  e_button("BUTTON", "Zoom in")

Shiny bindings for echarts4r

Description

Output and render functions for using echarts4r within Shiny applications and interactive Rmd documents.

Usage

echarts4rOutput(outputId, width = "100%", height = "400px")

renderEcharts4r(expr, env = parent.frame(), quoted = FALSE)

echarts4rProxy(
  id,
  data,
  x,
  timeline = FALSE,
  session = shiny::getDefaultReactiveDomain(),
  reorder = TRUE
)

echarts4r_proxy(
  id,
  data,
  x,
  timeline = FALSE,
  session = shiny::getDefaultReactiveDomain(),
  reorder = TRUE
)

Arguments

Callbacks

• id_brush: returns data on brushed data points.

• id_legend_change: returns series name of legend selected/unselected.

• id_clicked_data: returns data of clicked data point.

• id_clicked_data_value: returns value of clicked data point.

• id_clicked_row: returns row number of clicked data point.

• id_clicked_serie: returns name of serie of clicked data point.

• id_mouseover_data: returns data on hovered data point.

• id_mouseover_data_value: returns value of hovered data point.

• id_mouseover_row: returns row o hovered data point.

• id_mouseover_serie: returns name of serie of hovered data point.

Proxies

The echarts4rProxy function returns a proxy for chart which allows manipulating a drawn chart, adding data, adding or removing series, etc. without redrawing the entire chart.

• e_append1_p & e_append2_p

• e_showtip_p & e_hidetip_p

• e_highlight_p & e_downplay_p

• e_focus_adjacency & e_unfocus_adjacency

• e_dispatch_action_p

• e_execute

• e_remove_serie_p

Box

Description

Renders a data box in shiny.

Usage

echarts4rBox(
  data,
  x,
  y,
  text = "",
  subtext = "",
  type = c("bar", "line", "scatter", "area", "step"),
  ...,
  color = "#ffffff",
  text_color = "#ffffff",
  background_color = "#293c55",
  step = c("start", "middle", "end"),
  title_args = list(),
  tooltip = list(trigger = "axis")
)

Arguments

See Also

renderEcharts4rBox, echarts4rBoxOutput

Examples

library(shiny)

ui <- fluidPage(
  fluidRow(
    column(3, echarts4rBoxOutput("box1"))
  )
)

server <- function(input, output) {
  output$box1 <- renderEcharts4rBox({
    echarts4rBox(cars, speed, dist, "Cars", type = "bar")
  })
}
## Not run: 
shinyApp(ui, server)

## End(Not run)

Box Output

Description

Place box output in Shiny ui.

Usage

echarts4rBoxOutput(id, height = 150)

Arguments

Nodes Adjacency

Description

Actions related to e_graph.

Usage

e_focus_adjacency(e, ..., btn = NULL)

e_unfocus_adjacency(e, ..., btn = NULL)

Arguments

Examples

value <- rnorm(10, 10, 2)

nodes <- data.frame(
  name = sample(LETTERS, 10),
  value = value,
  size = value,
  grp = rep(c("grp1", "grp2"), 5),
  stringsAsFactors = FALSE
)

edges <- data.frame(
  source = sample(nodes$name, 20, replace = TRUE),
  target = sample(nodes$name, 20, replace = TRUE),
  stringsAsFactors = FALSE
)

e_charts() |>
  e_graph() |>
  e_graph_nodes(nodes, name, value, size, grp) |>
  e_graph_edges(edges, source, target) |>
  e_focus_adjacency(
    seriesIndex = 0,
    dataIndex = 4
  )

Highlight & Downplay

Description

Highlight series

Usage

e_highlight(e, series_index = NULL, series_name = NULL, btn = NULL)

e_downplay(e, series_index = NULL, series_name = NULL, btn = NULL)

Arguments

Examples

iris |>
  group_by(Species) |>
  e_charts(Sepal.Length) |>
  e_line(Sepal.Width) |>
  e_line(Petal.Length) |>
  e_highlight(series_name = "setosa") # highlight group

Initialise

Description

Initialise a chart.

Usage

e_charts(
  data,
  x,
  width = NULL,
  height = NULL,
  elementId = NULL,
  dispose = TRUE,
  draw = TRUE,
  renderer = "canvas",
  timeline = FALSE,
  ...,
  reorder = TRUE
)

## Default S3 method:
e_charts(
  data,
  x,
  width = NULL,
  height = NULL,
  elementId = NULL,
  dispose = TRUE,
  draw = TRUE,
  renderer = "canvas",
  timeline = FALSE,
  ...,
  reorder = TRUE
)

## S3 method for class 'Node'
e_charts(
  data,
  x,
  width = NULL,
  height = NULL,
  elementId = NULL,
  dispose = TRUE,
  draw = TRUE,
  renderer = "canvas",
  timeline = FALSE,
  ...,
  reorder = TRUE
)

e_charts_(
  data,
  x = NULL,
  width = NULL,
  height = NULL,
  elementId = NULL,
  dispose = TRUE,
  draw = TRUE,
  renderer = "canvas",
  timeline = FALSE,
  ...,
  reorder = TRUE
)

e_chart(
  data,
  x,
  width = NULL,
  height = NULL,
  elementId = NULL,
  dispose = TRUE,
  draw = TRUE,
  renderer = "canvas",
  timeline = FALSE,
  ...,
  reorder = TRUE
)

e_data(e, data, x)

Arguments

Timeline

The timeline feature currently supports the following chart types.

• e_bar

• e_line

• e_step

• e_area

• e_scatter

• e_effect_scatter

• e_candle

• e_heatmap

• e_pie

• e_line_3d

• e_lines_3d

• e_bar_3d

• e_lines

• e_scatter_3d

• e_scatter_gl

• e_histogram

• e_lm

• e_loess

• e_glm

• e_density

• e_pictorial

• e_boxplot

• e_map

• e_map_3d

• e_line_3d

• e_gauge

Examples

mtcars |>
  e_charts(qsec) |>
  e_line(mpg)
points <- mtcars[1:3, ]
mtcars |>
  e_charts_("qsec") |>
  e_line(mpg) |>
  e_data(points, qsec) |>
  e_scatter(mpg, color = "red", symbol_size = 20)

Legend

Description

Legend

Usage

e_legend_select(e, name, btn = NULL)

e_legend_unselect(e, name, btn = NULL)

e_legend_toggle_select(e, name, btn = NULL)

e_legend_scroll(e, scroll_index = NULL, legend_id = NULL, btn = NULL)

Arguments

Examples

e <- CO2 |>
  group_by(Type) |>
  e_charts(conc) |>
  e_scatter(uptake)

e |>
  e_legend_unselect("Quebec")

e |>
  e_legend_unselect("Quebec", btn = "btn") |>
  e_button("btn", "Quebec")

Map Actions

Description

Map-related actions.

Usage

e_map_select(e, ..., btn = NULL)

e_map_unselect(e, ..., btn = NULL)

e_map_toggle_select(e, ..., btn = NULL)

Arguments

See Also

e_map_register

Examples

choropleth <- data.frame(
  countries = c(
    "France",
    "Brazil",
    "China",
    "Russia",
    "Canada",
    "India",
    "United States",
    "Argentina",
    "Australia"
  ),
  values = round(runif(9, 10, 25))
)

choropleth |>
  e_charts(countries) |>
  e_map(values) |>
  e_visual_map(min = 10, max = 25) |>
  e_map_toggle_select(name = "China", btn = "btn") |>
  e_button("btn", "Select China")

Mapbox

Description

Use mapbox.

Usage

e_mapbox(e, token, ...)

Arguments

Note

Mapbox may not work properly in the RSudio console.

See Also

Official documentation, mapbox documentation

Examples

## Not run: 
url <- paste0(
  "https://echarts.apache.org/examples/",
  "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_mapbox(
    token = "YOUR_MAPBOX_TOKEN",
    style = "mapbox://styles/mapbox/dark-v9"
  ) |>
  e_bar_3d(lat, value, coord_system = "mapbox") |>
  e_visual_map()

## End(Not run)

Add nested data

Description

Utility function to add data where the original JavaScript library expects nested data.

Usage

e_add(e, param, ..., .serie = NULL, .data = NULL)

e_add_nested(e, param, ..., .serie = NULL, .data = NULL)

e_add_unnested(e, param, value, .serie = NULL, .data = NULL)

Arguments

Details

For instance, e_funnel lets you pass values and labels (from your initial data.frame) which corresponds to name and value in the original library. However the latter also takes, label, itemStyle, and emphasis but being JSON arrays they translate to lists in R and dealing with nested data.frames is not ideal. e_add remedies to that. It allows adding those nested data points, see the examples below.

Functions

- 'e_add_nested': Adds nested data, e.g.: 'e_add_nested("itemStyle", color, fontBold)' creates 'itemStyle: color: 'red', fontBold: 'bold''. - 'e_add_unnested': Adds unnested data, e.g.: 'e_add_unnested("symbolSize", size)' creates 'symbolSize: 4'.

Examples

# funnel can take nested itemStyle
# https://echarts.apache.org/en/option.html#series-funnel.data
funnel <- data.frame(
  stage = c("View", "Click", "Purchase"),
  value = c(80, 30, 20),
  color = c("blue", "red", "green")
)

funnel |>
  e_charts() |>
  e_funnel(value, stage) |>
  e_add_nested("itemStyle", color)

# Heatmap can take nested label
# https://echarts.apache.org/en/option.html#series-heatmap.data
v <- LETTERS[1:10]
matrix <- data.frame(
  x = sample(v, 300, replace = TRUE),
  y = sample(v, 300, replace = TRUE),
  z = rnorm(300, 10, 1),
  stringsAsFactors = FALSE
) |>
  dplyr::group_by(x, y) |>
  dplyr::summarise(z = sum(z)) |>
  dplyr::ungroup() |>
  dplyr::mutate(
    show = TRUE,
    fontStyle = round(runif(dplyr::n(), 5, 12))
  )

matrix |>
  e_charts(x) |>
  e_heatmap(y, z) |>
  e_visual_map(z) |>
  e_add_nested(
    "label",
    show,
    fontStyle
  )

Select & Unselect Pie

Description

Actions related to e_pie.

Usage

e_pie_select(e, ..., btn = NULL)

e_pie_unselect(e, ..., btn = NULL)

Arguments

Examples

mtcars |>
  head() |>
  tibble::rownames_to_column("model") |> 
  e_charts(model) |>
  e_pie(carb) |>
  e_pie_select(dataIndex = 0)

Radius axis

Description

Customise radius axis.

Usage

e_radius_axis(e, serie, show = TRUE, ...)

e_radius_axis_(e, serie = NULL, show = TRUE, ...)

Arguments

See Also

Additional arguments

Examples

df <- data.frame(x = LETTERS[1:10], y = seq(1, 20, by = 2))

df |>
  e_charts(x) |>
  e_polar() |>
  e_angle_axis() |>
  e_radius_axis(x) |>
  e_bar(y, coord.system = "polar")

Objects exported from other packages

Description

These objects are imported from other packages. Follow the links below to see their documentation.

dplyr

group_by

Render box

Description

Render an echarts4r box.

Usage

renderEcharts4rBox(expr, env = parent.frame(), quoted = FALSE)

Arguments

Timeline

Description

Set timeline options

Usage

e_timeline_opts(e, axis_type = "category", ...)

e_timeline_serie(e, ..., index = 1)

e_timeline_on_serie(e, ..., serie_index)

Arguments

Functions

• e_timeline_opts: Pass general timeline options, see official documentation.

• e_timeline_serie: Pass options to each serie, each options must be a vector or list the same length as their are steps, see examples.

• e_timeline_make: Helper function that wraps your data and e_timeline_serie to dynamically add options to series.

Examples

# general options
iris |>
  group_by(Species) |>
  e_charts(Sepal.Length, timeline = TRUE) |>
  e_line(Sepal.Width) |>
  e_timeline_opts(
    autoPlay = TRUE,
    rewind = TRUE
  )

# serie options
iris |>
  group_by(Species) |>
  e_charts(Sepal.Length, timeline = TRUE) |>
  e_line(Sepal.Width) |>
  e_timeline_serie(
    title = list(
      list(text = "setosa"),
      list(text = "versicolor"),
      list(text = "virginica")
    )
  )

Show & Hide Tooltip

Description

Show or hide tooltip.

Usage

e_showtip(e, ..., btn = NULL)

e_hidetip(e, ..., btn = NULL)

Arguments

Note

The tooltip must be initialised with e_tooltip for this to work.

Examples

cars |>
  e_charts(dist) |>
  e_scatter(speed) |>
  e_tooltip() |>
  e_hidetip(btn = "btn") |>
  e_button("btn", "Hide tooltip")