An htmlwidget interface to the ApexCharts javascript chart library

Description

This package allow you to use ApexCharts.js (https://apexcharts.com/), to create interactive and modern SVG charts.

Author(s)

Victor Perrier (@dreamRs_fr)

See Also

Useful links:

• https://github.com/dreamRs/apexcharter

• https://dreamrs.github.io/apexcharter/

• Report bugs at https://github.com/dreamRs/apexcharter/issues

Add a line to a chart

Description

Add a line to an existing chart (bar, scatter and line types supported). On scatter charts you can also add a smooth line.

Usage

add_line(
  ax,
  mapping,
  data = NULL,
  type = c("line", "spline"),
  serie_name = NULL
)

add_smooth_line(
  ax,
  formula = y ~ x,
  model = c("lm", "loess"),
  n = 100,
  ...,
  type = c("line", "spline"),
  serie_name = NULL
)

Arguments

Value

An apexchart() htmlwidget object.

Examples

library(apexcharter)


# Bar ----

data("climate_paris")

# Add a line on a column's chart
apex(climate_paris, aes(month, precipitation), type = "column") %>% 
  add_line(aes(month, temperature))

# Add secondary axis
apex(climate_paris, aes(month, precipitation), type = "column") %>% 
  add_line(aes(month, temperature)) %>%
  ax_yaxis(
    title = list(text = "Precipitation (in mm)")
  ) %>% 
  ax_yaxis2(
    opposite = TRUE,
    decimalsInFloat = 0,
    title = list(text = "Temperature (in degree celsius)")
  ) %>% 
  ax_dataLabels(
    enabled = TRUE, enabledOnSeries = list(1)
  )



# Scatter ----

# add smooth line on scatter plot
apex(cars, aes(speed, dist), type = "scatter") %>% 
  add_line(aes(x, y), data = lowess(cars), serie_name = "lowess")


# or directly
apex(cars, aes(speed, dist), type = "scatter") %>% 
  add_smooth_line()

apex(cars, aes(speed, dist), type = "scatter") %>% 
  add_smooth_line(model = "loess", span = 1)

apex(cars, aes(speed, dist), type = "scatter") %>% 
  add_smooth_line(model = "loess", degree = 1)


apex(cars, aes(speed, dist), type = "scatter") %>% 
  add_smooth_line(formula = y ~ poly(x, 2))

apex(cars, aes(speed, dist), type = "scatter") %>% 
  add_smooth_line(model = "lm", serie_name = "lm") %>% 
  add_smooth_line(model = "loess", serie_name = "loess")

Add a shaded area to a chart

Description

add_shade() allow to add a shaded area on specified range, add_shade_weekend() add a shadow on every week-end.

Usage

add_shade(ax, from, to, color = "#848484", opacity = 0.2, label = NULL, ...)

add_shade_weekend(ax, color = "#848484", opacity = 0.2, label = NULL, ...)

Arguments

Value

An apexchart() htmlwidget object.

Note

add_shade_weekend only works if variable used for x-axis is of class Date or POSIXt.

Examples

library(apexcharter)
data("consumption")

# specify from and to date
apex(consumption, aes(date, value, group = type), "spline") %>% 
  add_shade(from = "2020-01-06", to = "2020-01-20")

# you can add several shadows
apex(consumption, aes(date, value, group = type), "spline") %>% 
  add_shade(from = "2020-01-06", to = "2020-01-20") %>% 
  add_shade(from = "2020-02-04", to = "2020-02-10")

# or use a vector
apex(consumption, aes(date, value, group = type), "spline") %>% 
  add_shade(
    from = c("2020-01-06", "2020-02-04"),
    to = c("2020-01-20", "2020-02-10")
  )


# Add a label
apex(consumption, aes(date, value, group = type), "spline") %>% 
  add_shade(
    from = "2020-01-06", to = "2020-01-20",
    label = "interesting period"
  )

# add label with more options
apex(consumption, aes(date, value, group = type), "spline") %>% 
  add_shade(
    from = "2020-01-06", to = "2020-01-20",
    color = "firebrick",
    label = label(
      text = "something happened",
      background = "firebrick",
      color = "white", 
      fontWeight = "bold",
      padding = c(3, 5, 3, 5)
    )
  )


# automatically add shadow on week-ends
apex(consumption, aes(date, value, group = type), "spline") %>% 
  add_shade_weekend()

Add horizontal or vertical line

Description

Add horizontal or vertical line

Usage

add_hline(ax, value, color = "#000", dash = 0, label = NULL, ...)

add_vline(ax, value, color = "#000", dash = 0, label = NULL, ...)

Arguments

Value

An apexchart() htmlwidget object.

Examples

library(apexcharter)

# On a column chart
unhcr_ts %>%
  subset(year == 2017 & population_type == "Asylum-seekers") %>%
  apex(
    aes(continent_origin, n),
    "column"
  ) %>%
  add_hline(value = 5e5)


# On a scatter chart
apex(
  data = cars,
  aes(speed, dist),
  "scatter"
) %>%
  add_hline(value = mean(cars$dist)) %>%
  add_vline(value = mean(cars$speed))

# With labels
apex(
  data = cars,
  aes(speed, dist),
  "scatter"
) %>%
  add_hline(
    value = mean(cars$dist),
    label = "Mean of dist"
  ) %>%
  add_vline(
    value = mean(cars$speed),
    label = label(
      text = "Mean of speed",
      borderColor = "red"
    )
  )

Add an event to a chart

Description

Add a vertical line to mark a special event on a chart.

Usage

add_event(ax, when, color = "#E41A1C", dash = 4, label = NULL, ...)

Arguments

Value

An apexchart() htmlwidget object.

See Also

add_event_marker to add a point.

Examples

library(apexcharter)
data("consumption")

# specify from and to date
apex(consumption, aes(date, value, group = type), "spline") %>% 
  add_event(when = "2020-01-11")

# several events
apex(consumption, aes(date, value, group = type), "spline") %>% 
  add_event(when = c("2020-01-11", "2020-01-29"))

# Add labels on events
apex(consumption, aes(date, value, group = type), "spline") %>% 
  add_event(
    when = c("2020-01-11", "2020-01-29"),
    label = label(text = c("Am", "Ar"))
  )

# can be combined with shade
apex(consumption, aes(date, value, group = type), "spline") %>% 
  add_shade(from = "2020-01-06", to = "2020-01-20")%>% 
  add_event(when = c("2020-01-11", "2020-01-29"))

Add an event marker to a chart

Description

Add a point with a label based on a datetime.

Usage

add_event_marker(
  ax,
  when,
  y,
  size = 5,
  color = "#000",
  fill = "#FFF",
  width = 2,
  shape = "circle",
  radius = 2,
  label = NULL,
  ...
)

Arguments

Value

An apexchart() htmlwidget object.

See Also

add_event to add a vertical line.

Examples

library(apexcharter)
data("consumption")

# add a marker
apex(consumption, aes(date, value, group = type), "spline") %>% 
  add_event_marker(when = "2020-01-22", y = 1805)

# with a label
apex(consumption, aes(date, value, group = type), "spline") %>% 
  add_event_marker(when = "2020-01-22", y = 1805, label = "Consumption peak")

# add several markers
apex(consumption, aes(date, value, group = type), "spline") %>% 
  add_event_marker(
    when = c("2020-01-02", "2020-01-06", "2020-01-13", 
             "2020-01-22", "2020-01-28", "2020-02-06",
             "2020-02-13", "2020-02-19", "2020-02-27"),
    y = c(1545, 1659, 1614,
          1805, 1637, 1636, 
          1597, 1547, 1631),
    size = 10,
    color = "firebrick"
  )

Add an annotation point

Description

Add an annotation point

Usage

add_point(
  ax,
  x,
  y,
  size = 5,
  color = "#000",
  fill = "#FFF",
  width = 2,
  shape = "circle",
  radius = 2,
  label = NULL,
  ...
)

Arguments

Value

An apexchart() htmlwidget object.

See Also

add_event_marker to add a point when x-axis is a datetime.

Examples

library(apexcharter)

# On scatter chart
apex(
  data = iris,
  aes(Sepal.Length, Sepal.Width),
  "scatter"
) %>% 
  add_point(
    x = mean(iris$Sepal.Length),
    y = mean(iris$Sepal.Width)
  )

# Some options
apex(
  data = iris,
  aes(Sepal.Length, Sepal.Width),
  "scatter"
) %>% 
  add_point(
    x = mean(iris$Sepal.Length),
    y = mean(iris$Sepal.Width), 
    fill = "firebrick",
    color = "firebrick",
    size = 8,
    label = label(text = "Mean", offsetY = 0)
  )


# Several points
clusters <- kmeans(iris[, 1:2], 3)
apex(
  data = iris,
  aes(Sepal.Length, Sepal.Width),
  "scatter"
) %>% 
  add_point(
    x = clusters$centers[, 1],
    y = clusters$centers[, 2]
  )

Quick ApexCharts

Description

Initialize a chart with three main parameters : data, mapping and type of chart.

Usage

apex(
  data,
  mapping,
  type = "column",
  ...,
  auto_update = TRUE,
  synchronize = NULL,
  serie_name = NULL,
  width = NULL,
  height = NULL,
  elementId = NULL
)

Arguments

Value

An apexchart() htmlwidget object.

Examples

library(ggplot2)
library(apexcharter)

# make a barchart with a frequency table
data("mpg", package = "ggplot2")
apex(mpg, aes(manufacturer), type = "bar")


# timeseries
data("economics", package = "ggplot2")
apex(
  data = economics, 
  mapping = aes(x = date, y = uempmed), 
  type = "line"
)

# you can add option to apex result :
apex(
  data = economics, 
  mapping = aes(x = date, y = uempmed), 
  type = "line"
) %>% 
  ax_stroke(width = 1)


# with group variable
data("economics_long", package = "ggplot2")
apex(
  data = economics_long, 
  mapping = aes(x = date, y = value01, group = variable), 
  type = "line"
)

Facets for ApexCharts

Description

Create matrix of charts by row and column faceting variable (ax_facet_grid), or by specified number of row and column for faceting variable(s) (ax_facet_wrap).

Usage

ax_facet_wrap(
  ax,
  facets,
  nrow = NULL,
  ncol = NULL,
  scales = c("fixed", "free", "free_y", "free_x"),
  labeller = label_value,
  chart_height = "300px",
  grid_width = "100%"
)

ax_facet_grid(
  ax,
  rows = NULL,
  cols = NULL,
  scales = c("fixed", "free", "free_y", "free_x"),
  labeller = label_value,
  chart_height = "300px",
  grid_width = "100%"
)

Arguments

Value

An apexchart() htmlwidget object with an additionnal class "apex_facet".

Warning

To properly render in Shiny applications, use apexfacetOutput() (in UI) and renderApexfacet() (in Server).

Examples

### Wrap --------

if (interactive()) {
  library(apexcharter)
  
  # Scatter ----
  
  data("mpg", package = "ggplot2")
  
  # Create facets
  apex(mpg, aes(displ, cty), type = "scatter") %>% 
    ax_facet_wrap(vars(drv))
  
  # Change number of columns
  apex(mpg, aes(displ, cty), type = "scatter") %>% 
    ax_facet_wrap(vars(drv), ncol = 2)
  
  # Free axis
  apex(mpg, aes(displ, cty), type = "scatter") %>% 
    ax_facet_wrap(vars(drv), ncol = 2, scales = "free")
  
  # labels
  apex(mpg, aes(displ, cty), type = "scatter") %>% 
    ax_facet_wrap(
      vars(drv), ncol = 2,
      labeller = function(x) {
        switch(
          x,
          "f" = "front-wheel drive", 
          "r" = "rear wheel drive",
          "4" = "4wd"
        )
      }
    )
  
  # Title and subtitle are treated as global
  apex(mpg, aes(displ, cty), type = "scatter") %>%
    ax_labs(
      title = "Facet wrap example",
      subtitle = "mpg data from ggplot2"
    ) %>% 
    ax_facet_wrap(vars(drv), ncol = 2)
  
  
  # Multiple variables
  apex(mpg, aes(displ, cty), type = "scatter") %>% 
    ax_facet_wrap(vars(year, drv))
  
  apex(mpg, aes(displ, cty), type = "scatter") %>% 
    ax_facet_wrap(vars(year, drv), ncol = 2, nrow = 3)
  
  apex(mpg, aes(displ, cty), type = "scatter") %>% 
    ax_chart(toolbar = list(show = FALSE)) %>% 
    ax_facet_wrap(
      vars(year, drv),
      labeller = function(x) {
        paste(x, collapse = " / ")
      }
    )
  
  
  
  # Lines ----
  
  data("unhcr_ts")
  refugees <- unhcr_ts %>% 
    subset(population_type == "Refugees (incl. refugee-like situations)") %>% 
    transform(date = as.Date(paste0(year, "-01-01")))
  
  
  apex(refugees, aes(date, n), type = "line") %>% 
    ax_yaxis(tickAmount = 5) %>% 
    ax_facet_wrap(vars(continent_origin))
  
  
  
  # Free y-axis and synchronize
  apex(refugees, aes(date, n), type = "line", synchronize = "my-id") %>% 
    ax_yaxis(tickAmount = 5) %>% 
    ax_xaxis(tooltip = list(enabled = FALSE)) %>% 
    ax_tooltip(x = list(format = "yyyy")) %>% 
    ax_facet_wrap(vars(continent_origin), scales = "free_y")
  
  
  
  # Bars ----
  
  data("unhcr_ts")
  refugees <- unhcr_ts %>% 
    subset(year == 2017)
  
  apex(refugees, aes(continent_origin, n), type = "column") %>% 
    ax_yaxis(
      labels = list(
        formatter = format_num("~s")
      ),
      tickAmount = 5
    ) %>% 
    ax_facet_wrap(vars(population_type), ncol = 2)
  
}

### Grid --------
if (interactive()) {
  library(apexcharter)
  
  # Scatter ----
  
  data("mpg", package = "ggplot2")
  
  # Only rows
  apex(mpg, aes(displ, cty), type = "scatter") %>% 
    ax_facet_grid(rows = vars(drv), chart_height = "200px")
  
  # Only cols
  apex(mpg, aes(displ, cty), type = "scatter") %>% 
    ax_facet_grid(cols = vars(year))
  
  # Rows and Cols
  apex(mpg, aes(displ, cty), type = "scatter") %>% 
    ax_facet_grid(rows = vars(drv), cols = vars(year))
  
  apex(mpg, aes(displ, cty), type = "scatter") %>% 
    ax_chart(toolbar = list(show = FALSE)) %>% 
    ax_facet_grid(vars(drv), vars(cyl))
  
  
  # Labels
  apex(mpg, aes(displ, cty), type = "scatter") %>% 
    ax_facet_grid(
      vars(drv),
      labeller = function(x) {
        switch(
          x,
          "f" = "front-wheel drive", 
          "r" = "rear wheel drive",
          "4" = "4wd"
        )
      }
    )
  
  
  # Title and subtitle are treated as global
  apex(mpg, aes(displ, cty), type = "scatter") %>% 
    ax_labs(
      title = "Facet grid example",
      subtitle = "mpg data from ggplot2"
    ) %>% 
    ax_facet_grid(rows = vars(drv), cols = vars(year))
  
}

Create a grid of ApexCharts

Description

Create a grid of ApexCharts

Usage

apex_grid(
  ...,
  nrow = NULL,
  ncol = NULL,
  row_gap = "10px",
  col_gap = "0px",
  grid_area = NULL,
  height = NULL,
  width = NULL,
  .list = NULL
)

Arguments

Value

Custom apex_grid object.

Note

You have to provide either height for the grid or individual chart height to make it work.

Examples

if (interactive()) {
  library(apexcharter)
  data("mpg", package = "ggplot2")
  
  # Two chart side-by-side 
  a1 <- apex(mpg, aes(manufacturer), type = "bar")
  
  a2 <- apex(mpg, aes(trans), type = "column")
  
  apex_grid(a1, a2, height = "400px")
  
  
  # More complex layout:
  a3 <- apex(mpg, aes(drv), type = "pie")
  
  apex_grid(
    a1, a2, a3, 
    grid_area = c("1 / 1 / 3 / 2", "1 / 2 / 2 / 4", "2 / 2 / 3 / 4"),
    ncol = 3, nrow = 2,
    height = "600px"
  )
}

Create an ApexCharts widget

Description

Create an ApexCharts widget

Usage

apexchart(
  ax_opts = list(),
  auto_update = TRUE,
  width = NULL,
  height = NULL,
  elementId = NULL
)

Arguments

Value

An apexchart() htmlwidget object.

See Also

For quickly create a chart, see apex().

Examples

library(apexcharter)

# Use raw API by passing a list of
# parameters to the function

apexchart(ax_opts = list(
  chart = list(
    type = "bar"
  ),
  series = list(list(
    name = "Example",
    data = sample(1:100, 5)
  )),
  xaxis = list(
    categories = LETTERS[1:5]
  )
))


# Or use apexchart() to initialize the chart
# before passing parameters

apexchart() %>%
  ax_chart(type = "bar") %>%
  ax_series(
    list(
      name = "Example",
      data = sample(1:100, 5)
    )
  ) %>%
  ax_xaxis(
    categories = LETTERS[1:5]
  )

Proxy for apexchart

Description

Allow to update a chart in Shiny application.

Usage

apexchartProxy(shinyId, session = shiny::getDefaultReactiveDomain())

Arguments

apexcharter exported operators and S3 methods

Description

The following functions are imported and then re-exported from the apexcharter package to avoid listing the magrittr as Depends of apexcharter

Shiny bindings for apexcharter

Description

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

Usage

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

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

sparkBoxOutput(outputId, width = "100%", height = "160px")

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

Arguments

Value

Output element that can be included in UI. Render function to create output in server.

Note

To render a chart with facets (using ax_facet_wrap() or ax_facet_grid()) in Shiny, see apexfacetOutput() (in UI) and renderApexfacet() (in Server).

Examples

if (interactive()) {
  library(shiny)
  library(apexcharter)
  
  ui <- fluidPage(
    fluidRow(
      column(
        width = 8, offset = 2,
        tags$h2("Apexchart in Shiny"),
        actionButton("redraw", "Redraw chart"),
        apexchartOutput("chart")
      )
    )
  )
  
  server <- function(input, output, session) {
    
    output$chart <- renderApexchart({
      input$redraw
      apexchart() %>%
        ax_chart(type = "bar") %>%
        ax_series(
          list(
            name = "Example",
            data = sample(1:100, 5)
          )
        ) %>%
        ax_xaxis(
          categories = LETTERS[1:5]
        )
    })
    
  }
  
  shinyApp(ui, server)
}

Shiny bindings for faceting with apexcharter

Description

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

Usage

apexfacetOutput(outputId)

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

Arguments

Value

An Apexcharts output that can be included in the application UI.

See Also

ax_facet_wrap(), ax_facet_grid()

Examples

library(shiny)
library(apexcharter)

data("unhcr_ts")
refugees <- unhcr_ts %>% 
  subset(
    population_type == "Refugees (incl. refugee-like situations)"
  ) %>% 
  transform(date = as.Date(paste0(year, "-01-01")))


ui <- fluidPage(
  
  tags$h2("Apexcharts Facets Example"),
  
  apexfacetOutput("myfacet")
  
)

server <- function(input, output, session) {
  
  output$myfacet <- renderApexfacet({
    apex(refugees, aes(date, n), type = "column") %>% 
      ax_yaxis(tickAmount = 5) %>% 
      ax_facet_wrap(
        vars(continent_origin), 
        scales = "free"
      )
  })
  
}

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

Shiny bindings for grid with apexcharter

Description

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

Usage

apexgridOutput(outputId)

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

Arguments

Value

An Apexcharts output that can be included in the application UI.

Examples

library(shiny)
library(apexcharter)

ui <- fluidPage(
  
  tags$h2("Apexcharts Grid Example"),
  
  apexgridOutput("myfacet")
  
)

server <- function(input, output, session) {
  
  output$myfacet <- renderApexgrid({
    a1 <- apex(mpg, aes(manufacturer), type = "bar")
    a2 <- apex(mpg, aes(trans), type = "column")
    a3 <- apex(mpg, aes(drv), type = "pie")
    
    apex_grid(
      a1, a2, a3, 
      grid_area = c("1 / 1 / 3 / 2", "1 / 2 / 2 / 4", "2 / 2 / 3 / 4"),
      ncol = 3, 
      nrow = 2,
      height = "600px"
    )
  })
  
}

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

Add data to a chart

Description

Add data to a chart

Usage

ax_series(ax, ...)

ax_series2(ax, l)

Arguments

Value

An apexchart() htmlwidget object.

Examples

# One serie
apexchart() %>% 
  ax_series(list(
    name = "rnorm",
    data = rnorm(10)
  ))

# Two series
apexchart() %>% 
  ax_series(
    list(
      name = "rnorm 1",
      data = rnorm(10)
    ),
    list(
      name = "rnorm 2",
      data = rnorm(10)
    )
  )

Annotations properties

Description

Annotations properties

Usage

ax_annotations(
  ax,
  position = NULL,
  yaxis = NULL,
  xaxis = NULL,
  points = NULL,
  ...
)

Arguments

Value

An apexchart() htmlwidget object.

Note

See https://apexcharts.com/docs/options/annotations/.

Examples

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

# Horizontal line
apex(
  data = tail(economics, 200),
  mapping = aes(x = date, y = uempmed),
  type = "line"
) %>% 
  ax_annotations(
    yaxis = list(list(
      y = 11.897,
      borderColor = "firebrick", 
      opacity = 1,
      label = list(
        text = "Mean uempmed",
        position = "left", 
        textAnchor = "start"
      )
    ))
  )


# Vertical line
apex(
  data = tail(economics, 200),
  mapping = aes(x = date, y = uempmed),
  type = "line"
) %>% 
  ax_annotations(
    xaxis = list(list(
      x = htmlwidgets::JS("new Date('1 Mar 2007').getTime()"),
      strokeDashArray = 0, 
      borderColor = "#775DD0",
      label = list(
        text = "A label",
        borderColor = "#775DD0", 
        style = list(
          color = "#fff",
          background = "#775DD0"
        )
      )
    ))
  )


# Vertical range
apex(
  data = tail(economics, 200),
  mapping = aes(x = date, y = uempmed),
  type = "line"
) %>% 
  ax_annotations(
    xaxis = list(list(
      x = htmlwidgets::JS("new Date('1 Jan 2009').getTime()"),
      x2 = htmlwidgets::JS("new Date('1 Feb 2010').getTime()"),
      fillColor = "#B3F7CA",
      opacity = 0.4,
      label = list(
        text = "A label",
        borderColor = "#B3F7CA", 
        style = list(
          color = "#fff",
          background = "#B3F7CA"
        )
      )
    ))
  )


# Point annotation
apex(
  data = tail(economics, 200),
  mapping = aes(x = date, y = uempmed),
  type = "line"
) %>% 
  ax_annotations(
    points = list(list(
      x = htmlwidgets::JS("new Date('1 Jun 2010').getTime()"),
      y = 25.2,
      marker = list(
        size = 8,
        fillColor = "#fff",
        strokeColor = "red",
        radius = 2
      ),
      label = list(
        text = "Highest",
        offsetY = 0,
        borderColor = "#FF4560", 
        style = list(
          color = "#fff",
          background = "#FF4560"
        )
      )
    ))
  )

Chart parameters

Description

Chart parameters

Usage

ax_chart(
  ax,
  type = NULL,
  stacked = NULL,
  stackType = NULL,
  defaultLocale = NULL,
  locales = NULL,
  animations = NULL,
  background = NULL,
  foreColor = NULL,
  dropShadow = NULL,
  events = NULL,
  offsetX = NULL,
  offsetY = NULL,
  selection = NULL,
  sparkline = NULL,
  toolbar = NULL,
  zoom = NULL,
  width = NULL,
  height = NULL,
  ...
)

Arguments

Value

An apexchart() htmlwidget object.

Examples

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

##  Stack bar type
# default is dodge
apex(
  data = diamonds,
  mapping = aes(x = cut, fill = color)
)

# stack
apex(
  data = diamonds,
  mapping = aes(x = cut, fill = color)
) %>%
  ax_chart(stacked = TRUE)

# stack filled
apex(
  data = diamonds,
  mapping = aes(x = cut, fill = color)
) %>%
  ax_chart(stacked = TRUE, stackType = "100%")




# Toolbar --------------------------------------

# Hide the toolbar
apex(
  data = diamonds,
  mapping = aes(x = cut, fill = color)
) %>%
  ax_chart(toolbar = list(show = FALSE))

# Hide download buttons
data("economics", package = "ggplot2")
apex(
  data = economics,
  mapping = aes(x = date, y = pce), 
  type = "line"
) %>%
  ax_chart(
    toolbar = list(tools= list(download = FALSE))
  )



# Zoom -----------------------------------------

# Disable
apex(
  data = economics,
  mapping = aes(x = date, y = pce), 
  type = "line"
) %>%
  ax_chart(
    zoom = list(enabled = FALSE)
  )


# Auto-scale Y axis
apex(
  data = economics,
  mapping = aes(x = date, y = pce), 
  type = "line"
) %>%
  ax_chart(
    zoom = list(autoScaleYaxis = TRUE)
  )

# Localization ---------------------------------


# Use included localization config
dat <- data.frame(
  x = Sys.Date() + 1:20,
  y = sample.int(20, 20)
)

# French
apex(dat, aes(x, y), "line") %>% 
  ax_chart(defaultLocale = "fr")

# Italian
apex(dat, aes(x, y), "line") %>% 
  ax_chart(defaultLocale = "it")



# Custom config
apex(dat, aes(x, y), "line") %>% 
  ax_chart(locales = list(
    list(
      name = "en", # override 'en' locale
      options = list(
        toolbar = list(
          exportToSVG = "GET SVG",
          exportToPNG = "GET PNG"
        )
      )
    )
  ))

Colors

Description

Colors

Usage

ax_colors(ax, ...)

Arguments

Value

An apexchart() htmlwidget object.

Note

See https://apexcharts.com/docs/options/colors/

Examples

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

# Change default color(s)
apex(
  data = diamonds,
  mapping = aes(x = cut)
) %>%
  ax_colors("#F7D358")


library(scales)
apex(
  data = diamonds,
  mapping = aes(x = cut, fill = color)
) %>%
  ax_colors(brewer_pal(palette = "Set2")(7))

Set specific color's series

Description

Set specific color's series

Usage

ax_colors_manual(ax, values)

Arguments

Value

An apexchart() htmlwidget object.

Examples

## scatter

apex(
  data = mtcars, 
  type = "scatter",
  mapping = aes(x = wt, y = mpg, fill = cyl)
) %>% 
  ax_colors_manual(list(
    "4" = "steelblue",
    "6" = "firebrick",
    "8" = "forestgreen"
  ))

# If missing level, colors are recycled
apex(
  data = mtcars, 
  type = "scatter",
  mapping = aes(x = wt, y = mpg, fill = cyl)
) %>% 
  ax_colors_manual(list(
    "4" = "steelblue",
    "8" = "forestgreen"
  ))

# Ignore levels not present in data
apex(
  data = mtcars, 
  type = "scatter",
  mapping = aes(x = wt, y = mpg, fill = cyl)
) %>% 
  ax_colors_manual(list(
    "4" = "steelblue",
    "6" = "firebrick",
    "8" = "forestgreen",
    "99" = "yellow"
  ))



## Bar

tab <- table(sample(letters[1:5], 100, TRUE), sample(LETTERS[1:5], 100, TRUE))
dat <- as.data.frame(tab)

apex(
  data = dat,
  type = "column",
  mapping = aes(x = Var1, y = Freq, group = Var2)
) %>% 
  ax_colors_manual(list(
    A = "steelblue",
    C = "firebrick",
    D = "forestgreen",
    B = "peachpuff",
    E = "chartreuse"
  ))

Labels on data

Description

Labels on data

Usage

ax_dataLabels(
  ax,
  enabled = NULL,
  textAnchor = NULL,
  offsetX = NULL,
  offsetY = NULL,
  style = NULL,
  dropShadow = NULL,
  formatter = NULL,
  ...
)

Arguments

Value

An apexchart() htmlwidget object.

Note

See https://apexcharts.com/docs/options/datalabels/

Examples

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

# Add data labels
apex(
  data = diamonds,
  mapping = aes(x = cut)
) %>%
  ax_dataLabels(enabled = TRUE)

Fill property

Description

Fill property

Usage

ax_fill(
  ax,
  type = NULL,
  colors = NULL,
  opacity = NULL,
  gradient = NULL,
  image = NULL,
  pattern = NULL,
  ...
)

Arguments

Value

An apexchart() htmlwidget object.

Note

See https://apexcharts.com/docs/options/fill/

Examples

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

# Use a pattern to fill bars
apex(
  data = diamonds,
  mapping = aes(x = color, fill = cut)
) %>% 
  ax_fill(
    type = "pattern", 
    opacity = 1, 
    pattern = list(
      style = c("circles", "slantedLines", "verticalLines", "horizontalLines", "squares")
    )
  )


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

# Customise gradient
apex(
  data = economics,
  mapping = aes(x = date, y = psavert),
  type = "area"
) %>%
  ax_fill(gradient = list(
    enabled = TRUE,
    shadeIntensity = 1,
    inverseColors = FALSE,
    opacityFrom = 0,
    opacityTo = 1,
    stops = c(0, 2000)
  ))

Forecast data points

Description

Forecast data points

Usage

ax_forecast_data_points(
  ax,
  count = NULL,
  fillOpacity = NULL,
  strokeWidth = NULL,
  dashArray = NULL,
  ...
)

Arguments

Value

An apexchart() htmlwidget object.

Examples

# add 5 predictions to data then plot it
data.frame(
  time = seq_len(53),
  lh = c(
    as.vector(lh),
    as.vector(predict(arima(lh, order = c(1,0,1)), 5)$pred)
  )
) %>% 
  apex(aes(time, lh), type = "line") %>% 
  ax_xaxis(type = "numeric") %>% 
  ax_forecast_data_points(count = 5)

Add grids on chart

Description

Add grids on chart

Usage

ax_grid(
  ax,
  show = NULL,
  borderColor = NULL,
  strokeDashArray = NULL,
  position = NULL,
  xaxis = NULL,
  yaxis = NULL,
  row = NULL,
  column = NULL,
  padding = NULL,
  ...
)

Arguments

Value

An apexchart() htmlwidget object.

Note

See https://apexcharts.com/docs/options/grid/

Examples

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

# Hide Y-axis and gridelines
apex(
  data = mpg,
  mapping = aes(x = manufacturer)
) %>% 
  ax_grid(show = FALSE)

# just grid lines
apex(
  data = mpg,
  mapping = aes(x = manufacturer)
) %>% 
  ax_grid(yaxis = list(lines = list(show = FALSE)))


# both x & y
data("economics", package = "ggplot2")
apex(
  data = economics,
  mapping = aes(x = date, y = psavert),
  type = "line"
) %>% 
  ax_grid(
    yaxis = list(lines = list(show = TRUE)),
    xaxis = list(lines = list(show = TRUE))
  )

Alternative axis labels

Description

Alternative axis labels

Usage

ax_labels(ax, ...)

ax_labels2(ax, labels)

Arguments

Value

An apexchart() htmlwidget object.

Note

See https://apexcharts.com/docs/options/labels/

Examples

apexchart() %>% 
  ax_chart(type = "pie") %>% 
  ax_series(23, 45, 56) %>% 
  ax_labels("A", "B", "C")

# same as 
apexchart() %>% 
  ax_chart(type = "pie") %>% 
  ax_series2(c(23, 45, 56)) %>% 
  ax_labels2(c("A", "B", "C"))

Modify axis, legend, and chart labels

Description

Modify axis, legend, and chart labels

Usage

ax_labs(ax, title = NULL, subtitle = NULL, x = NULL, y = NULL)

Arguments

Value

An apexchart() htmlwidget object.

Examples

meteo_paris <- data.frame(
  month = month.name,
  tmax = c(7, 8, 12, 15, 19, 23, 25, 25, 21, 16, 11, 8),
  tmin = c(3, 3, 5, 7, 11, 14, 16, 16, 13, 10, 6, 3)
)

apex(meteo_paris, type = "column", aes(x = month, y = tmin)) %>%
  ax_labs(
    title = "Average minimal temperature in Paris",
    subtitle = "Data from NOAA",
    x = "Month",
    y = "Temperature (\u00b0C)"
  )

Legend properties

Description

Legend properties

Usage

ax_legend(
  ax,
  show = NULL,
  position = NULL,
  showForSingleSeries = NULL,
  showForNullSeries = NULL,
  showForZeroSeries = NULL,
  horizontalAlign = NULL,
  fontSize = NULL,
  textAnchor = NULL,
  offsetY = NULL,
  offsetX = NULL,
  formatter = NULL,
  labels = NULL,
  markers = NULL,
  itemMargin = NULL,
  containerMargin = NULL,
  onItemClick = NULL,
  onItemHover = NULL,
  floating = NULL,
  ...
)

Arguments

Value

An apexchart() htmlwidget object.

Note

See https://apexcharts.com/docs/options/legend/

Examples

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

# Legend position
apex(
  data = mpg,
  mapping = aes(x = manufacturer, fill = year)
) %>% 
  ax_legend(position = "right")

# hide legend
apex(
  data = mpg,
  mapping = aes(x = manufacturer, fill = year)
) %>% 
  ax_legend(show = FALSE)

Markers properties

Description

Markers properties

Usage

ax_markers(
  ax,
  size = NULL,
  colors = NULL,
  strokeColor = NULL,
  strokeWidth = NULL,
  strokeOpacity = NULL,
  fillOpacity = NULL,
  shape = NULL,
  radius = NULL,
  offsetX = NULL,
  offsetY = NULL,
  hover = NULL,
  ...
)

Arguments

Value

An apexchart() htmlwidget object.

Note

See https://apexcharts.com/docs/options/markers/

Examples

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

# show points
apex(
  data = tail(economics, 20),
  type = "line", 
  mapping = aes(x = date, y = uempmed)
) %>% 
  ax_markers(size = 6) 

Configuration for charts with no data

Description

Configuration for charts with no data

Usage

ax_nodata(
  ax,
  text = "No data",
  align = "center",
  verticalAlign = "middle",
  color = NULL,
  fontSize = NULL,
  fontFamily = NULL,
  offsetX = NULL,
  offsetY = NULL
)

Arguments

Value

An apexchart() htmlwidget object.

Examples

empty <- data.frame(
  var1 = character(0),
  var2 = numeric(0)
)
apex(empty, aes(var1, var2), "column") %>% 
  ax_nodata(
    text = "Sorry no data to visualize",
    fontSize = "30px"
  )

Specific options for chart

Description

Specific options for chart

Usage

ax_plotOptions(
  ax,
  bar = NULL,
  heatmap = NULL,
  radialBar = NULL,
  pie = NULL,
  bubble = NULL,
  boxPlot = NULL,
  ...
)

Arguments

Value

An apexchart() htmlwidget object.

Examples

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

# Stack bar type
apex(
  data = diamonds,
  mapping = aes(x = cut)
) %>%
  ax_plotOptions(
    bar = bar_opts(endingShape = "rounded", columnWidth = "10%")
  )

# Pie
apex(
  data = diamonds,
  mapping = aes(x = cut), 
  type = "pie"
) %>%
  ax_plotOptions(
    pie = pie_opts(customScale = 0.5)
  )


# Radial
apexchart() %>% 
  ax_chart(type = "radialBar") %>% 
  ax_plotOptions(
    radialBar = radialBar_opts(
      hollow = list(size = "70%")
    )
  ) %>% 
  ax_series(70) %>% 
  ax_labels("Indicator")

Proxy for updating options

Description

Allows you to update the configuration object.

Usage

ax_proxy_options(proxy, options)

Arguments

Examples

if (interactive()) {
  library(shiny)

  ui <- fluidPage(
    fluidRow(
      column(
        width = 8, offset = 2,
        tags$h2("Update options"),
        apexchartOutput(outputId = "chart"),
        checkboxInput(
          inputId = "show_label_xaxis",
          label = "Show x-axis labels"
        ),
        textInput(
          inputId = "yaxis_title",
          label = "Y-axis title"
        )
      )
    )
  )
  server <- function(input, output, session) {

    output$chart <- renderApexchart({
      apexchart() %>%
        ax_chart(type = "bar") %>%
        ax_series(list(
          name = "Example",
          data = c(23, 43, 76, 31)
        )) %>%
        ax_xaxis(
          categories = c("Label A", "Label B",
                         "Label C", "Label D")
        )
    })

    observe({
      apexchartProxy("chart") %>%
        ax_proxy_options(list(
          xaxis = list(
            labels = list(show = input$show_label_xaxis)
          ),
          yaxis = list(
            title = list(text = input$yaxis_title)
          )
        ))
    })

  }

  shinyApp(ui, server)
}

Proxy for updating series.

Description

Allows you to update the series array overriding the existing one.

Usage

ax_proxy_series(proxy, newSeries, animate = TRUE)

Arguments

Examples

if (interactive()) {
  library(shiny)

  ui <- fluidPage(
    fluidRow(
      column(
        width = 8, offset = 2,
        tags$h2("Real time chart"),
        apexchartOutput(outputId = "chart")
      )
    )
  )

  server <- function(input, output, session) {

    rv <- reactiveValues()
    rv$df <- data.frame(
      date = Sys.Date() + 1:20,
      values = sample(10:90, 20, TRUE)
    )

    observe({
      invalidateLater(1000, session)
      df <- isolate(rv$df)
      # Append new line of data
      df <- rbind(
        df, data.frame(
          date = df$date[length(df$date)] + 1,
          values = sample(10:90, 1, TRUE)
        )
      )
      rv$df <- df
    })

    output$chart <- renderApexchart({
      # Generate chart once
      apex(isolate(rv$df), aes(date, values), "spline") %>%
        ax_xaxis(
          range = 10 * 24 * 60 * 60 * 1000
          # Fixed range for x-axis : 10 days
          # days*hours*minutes*seconds*milliseconds
        )
    })

    observe({
      # Update chart to add new data
      apexchartProxy("chart") %>%
        ax_proxy_series(
          parse_df(rv$df),
          T
        )
    })

  }

  shinyApp(ui, server)
}

Responsive options

Description

Responsive options

Usage

ax_responsive(ax, ...)

Arguments

Value

An apexchart() htmlwidget object.

Note

See https://apexcharts.com/docs/options/responsive/

Examples

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

# Open in browser and resize window
apex(
  data = mpg,
  mapping = aes(x = manufacturer, fill = year),
  type = "bar"
) %>% 
  ax_legend(position = "right") %>% 
  ax_responsive(
    list(
      breakpoint = 1000,
      options = list(
        plotOptions = list(
          bar = list(
            horizontal = FALSE
          )
        ),
        legend = list(
          position = "bottom"
        )
      )
    )
  )

Charts' states

Description

Charts' states

Usage

ax_states(ax, normal = NULL, hover = NULL, active = NULL, ...)

Arguments

Value

An apexchart() htmlwidget object.

Note

See https://apexcharts.com/docs/options/states/

Examples

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

# Inverse effect on hover
apex(
  data = mpg,
  mapping = aes(x = manufacturer),
  type = "bar"
) %>% 
  ax_states(
    hover = list(
      filter = list(
        type = "darken"
      )
    )
  )

Stroke properties

Description

Stroke properties

Usage

ax_stroke(
  ax,
  show = NULL,
  curve = NULL,
  lineCap = NULL,
  width = NULL,
  colors = NULL,
  dashArray = NULL,
  ...
)

Arguments

Value

An apexchart() htmlwidget object.

Note

See https://apexcharts.com/docs/options/stroke/

Examples

data("economics", package = "ggplot2")
apex(
  data = economics,
  mapping = aes(x = date, y = uempmed),
  type = "line"
) %>%
  ax_stroke(
    width = 1, 
    dashArray = 4
  )

data("economics_long", package = "ggplot2")
apex(
  data = economics_long,
  mapping = aes(x = date, y = value01, group = variable),
  type = "line"
) %>%
  ax_stroke(
    width = c(1, 2, 3, 4, 5), 
    dashArray = c(1, 2, 3, 4, 5)
  )

Chart's subtitle

Description

Chart's subtitle

Usage

ax_subtitle(
  ax,
  text = NULL,
  align = NULL,
  margin = NULL,
  offsetX = NULL,
  offsetY = NULL,
  floating = NULL,
  style = NULL,
  ...
)

Arguments

Value

An apexchart() htmlwidget object.

Note

See https://apexcharts.com/docs/options/subtitle/

Examples

data("economics", package = "ggplot2")
apex(
  data = economics,
  mapping = aes(x = date, y = uempmed),
  type = "line"
) %>%
  ax_title(
    text = "Median duration of unemployment"
  ) %>%
  ax_subtitle(
    text = "in weeks"
  )

Theme for charts

Description

Theme for charts

Usage

ax_theme(ax, mode = c("light", "dark"), palette = NULL, monochrome = NULL, ...)

Arguments

Value

An apexchart() htmlwidget object.

Note

See https://apexcharts.com/docs/options/theme/

Examples

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

# Dark mode
apex(
  data = mpg,
  mapping = aes(x = manufacturer)
) %>% 
  ax_theme(mode = "dark")

# Use predefined palette (1 to 10)
apex(
  data = diamonds,
  mapping = aes(x = color, fill = cut)
) %>% 
  ax_theme(palette = "palette2")

# monochrome palette
apex(
  data = diamonds,
  mapping = aes(x = color, fill = cut)
) %>% 
  ax_theme(monochrome = list(enabled = TRUE, color = "#0B6121"))

Chart's title

Description

Chart's title

Usage

ax_title(
  ax,
  text = NULL,
  align = NULL,
  margin = NULL,
  offsetX = NULL,
  offsetY = NULL,
  floating = NULL,
  style = NULL,
  ...
)

Arguments

Value

An apexchart() htmlwidget object.

Note

See https://apexcharts.com/docs/options/title/

Examples

data("economics", package = "ggplot2")
apex(
  data = economics,
  mapping = aes(x = date, y = uempmed),
  type = "line"
) %>% 
  ax_title(
    text = "Median duration of unemployment, in weeks"
  )

Tooltip options

Description

Tooltip options

Usage

ax_tooltip(
  ax,
  enabled = NULL,
  shared = NULL,
  followCursor = NULL,
  intersect = NULL,
  inverseOrder = NULL,
  custom = NULL,
  fillSeriesColor = NULL,
  onDatasetHover = NULL,
  theme = NULL,
  x = NULL,
  y = NULL,
  z = NULL,
  marker = NULL,
  items = NULL,
  fixed = NULL,
  ...
)

Arguments

Value

An apexchart() htmlwidget object.

Note

See https://apexcharts.com/docs/options/tooltip/

Examples

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

# Hide tooltip
apex(
  data = mpg,
  mapping = aes(x = manufacturer, fill = year)
) %>% 
  ax_tooltip(enabled = FALSE)

# Share between series
apex(
  data = mpg,
  mapping = aes(x = manufacturer, fill = year)
) %>% 
  ax_tooltip(shared = TRUE)

# Fixed tooltip
data("economics", package = "ggplot2")
apex(
  data = economics,
  mapping = aes(x = date, y = psavert),
  type = "line"
) %>% 
  ax_tooltip(
    fixed = list(enabled = TRUE, position = "topLeft")
  )

X-axis options

Description

X-axis options

Usage

ax_xaxis(
  ax,
  type = NULL,
  categories = NULL,
  labels = NULL,
  axisBorder = NULL,
  axisTicks = NULL,
  tickAmount = NULL,
  min = NULL,
  max = NULL,
  range = NULL,
  floating = NULL,
  position = NULL,
  title = NULL,
  crosshairs = NULL,
  tooltip = NULL,
  ...
)

Arguments

Value

An apexchart() htmlwidget object.

Note

See https://apexcharts.com/docs/options/xaxis/

Examples

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

# X axis title
apex(
  data = mpg,
  mapping = aes(x = manufacturer)
) %>% 
  ax_xaxis(title = list(text = "Car's manufacturer"))

# force labels to rotate and increase height
apex(
  data = mpg,
  mapping = aes(x = manufacturer)
) %>% 
  ax_xaxis(labels = list(rotateAlways = TRUE, maxHeight = 180))

# force to not rotate
apex(
  data = mpg,
  mapping = aes(x = manufacturer)
) %>% 
  ax_xaxis(labels = list(rotate = 0, trim = FALSE))


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

# Custom crosshair
apex(
  data = tail(economics, 50),
  mapping = aes(x = date, y = psavert),
  type = "line"
) %>% 
  ax_xaxis(
    crosshairs = list(
      opacity = 1,
      width = 2,
      fill = list(color = "red"),
      stroke = list(width = 0)
    )
  )


# Date format (zoom to see changes)
apex(
  data = tail(economics, 150),
  mapping = aes(x = date, y = psavert),
  type = "line"
) %>% 
  ax_xaxis(
    labels = list(
      datetimeFormatter = list(
        year = "yyyy-MM",
        month = "yyyy-MM-dd",
        day = "yyyy-MM-dd HH:mm"
      )
    )
  )

Y-axis options

Description

Y-axis options

Usage

ax_yaxis(
  ax,
  opposite = NULL,
  tickAmount = NULL,
  max = NULL,
  min = NULL,
  floating = NULL,
  labels = NULL,
  axisBorder = NULL,
  axisTicks = NULL,
  title = NULL,
  tooltip = NULL,
  crosshairs = NULL,
  ...
)

Arguments

Value

An apexchart() htmlwidget object.

Note

See https://apexcharts.com/docs/options/yaxis/

Examples

data("economics_long", package = "ggplot2")
apex(
  data = economics_long,
  mapping = aes(x = date, y = value01, group = variable),
  type = "line"
) %>%
  ax_yaxis(
    decimalsInFloat = 2, title = list(text = "Rescaled to [0,1]")
  )
  
# Format tick labels
temperature <- data.frame(
  month = head(month.name),
  tp = c(4, -2, 2, 7, 11, 14)
)
apex(temperature, aes(month, tp), "line") %>% 
  ax_yaxis(
    labels = list(
      formatter = htmlwidgets::JS("function(value) {return value + '\u00b0C';}")
    )
  )

Secondary Y-axis options

Description

Secondary Y-axis options

Usage

ax_yaxis2(ax, ...)

Arguments

Value

An apexchart() htmlwidget object.

Examples

library(apexcharter)
data("economics_long", package = "ggplot2")

eco <- economics_long %>%
  subset(variable %in% c("pce", "pop")) %>% 
  transform(value = round(value))

# add second y-axis
apex(eco, aes(x = date, y = value, color = variable), type = "line") %>%
  ax_yaxis(title = list(text = "Pce")) %>%
  ax_yaxis2(opposite = TRUE, title = list(text = "Pop"))

# Customize axis a bit more
apex(eco, aes(x = date, y = value, color = variable), type = "line") %>%
  ax_yaxis(
    title = list(text = "Pce"),
    axisBorder = list(
      show = TRUE,
      color = "#008FFB"
    ),
    labels = list(
      style = list(
        colors = "#008FFB"
      )
    ),
    tooltip = list(
      enabled = TRUE
    )
  ) %>%
  ax_yaxis2(
    opposite = TRUE, 
    min = 160000,
    forceNiceScale = TRUE,
    title = list(text = "Pop"),
    axisBorder = list(
      show = TRUE,
      color = "#00E396"
    ),
    labels = list(
      style = list(
        colors = "#00E396"
      )
    ),
    tooltip = list(
      enabled = TRUE
    )
  )

Bar options

Description

Use these options in ax_plotOptions().

Usage

bar_opts(
  horizontal = NULL,
  endingShape = NULL,
  columnWidth = NULL,
  barHeight = NULL,
  distributed = NULL,
  colors = NULL,
  dataLabels = NULL,
  ...
)

Arguments

Value

A list of options that can be used in ax_plotOptions().

Note

See https://apexcharts.com/docs/options/plotoptions/bar/.

Examples

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

apex(mpg, aes(manufacturer)) %>% 
  ax_plotOptions(
    bar = bar_opts(
      endingShape = "rounded",
      columnWidth = 100,
      distributed = TRUE
    )
  )
  

Boxplot options

Description

Use these options in ax_plotOptions().

Usage

boxplot_opts(color.upper, color.lower, ...)

Arguments

Value

A list of options that can be used in ax_plotOptions().

Note

See https://apexcharts.com/docs/options/plotoptions/boxplot/.

Examples

data("mpg", package = "ggplot2")
apex(mpg, aes(class, hwy), "boxplot") %>% 
  ax_plotOptions(
    boxPlot = boxplot_opts(color.upper = "#848484", color.lower = "#848484" )
  )

Bubble options

Description

Use these options in ax_plotOptions().

Usage

bubble_opts(minBubbleRadius, maxBubbleRadius, ...)

Arguments

Value

A list of options that can be used in ax_plotOptions().

Note

See https://apexcharts.com/docs/options/plotoptions/bubble/.

Examples

apex(
  data = mtcars, 
  type = "scatter", 
  mapping = aes(x = wt, y = mpg, z = qsec)
) %>% 
  ax_plotOptions(
    bubble = bubble_opts(
      minBubbleRadius = 1,
      maxBubbleRadius = 20
    )
  )

Candlestick demo data

Description

Candlestick demo data

Usage

candles

Format

A data frame with 60 observations and the following 5 variables:

datetime

Timestamp.

open

Open value.

high

Highest value.

low

Lowest value.

close

Close value.

Source

Apexcharts (https://apexcharts.com/javascript-chart-demos/candlestick-charts/basic/)

Paris Climate

Description

Average temperature and precipitation in Paris for the period 1971-2000.

Usage

climate_paris

Format

A data frame with 12 observations and the following 3 variables:

month

Month

temperature

Temperature (in degree celsius).

precipitation

Precipitation (in mm).

Source

Wikipedia (https://fr.wikipedia.org/wiki/Climat_de_Paris)

Configuration for auto update

Description

Configuration for auto update

Usage

config_update(
  series_animate = TRUE,
  update_options = FALSE,
  options_animate = TRUE,
  options_redrawPaths = TRUE,
  update_synced_charts = FALSE
)

Arguments

Electricity consumption and forecasting

Description

Electricity consumption per day in France for january and february of year 2020.

Usage

consumption

Format

A data frame with 120 observations and the following 3 variables:

date

date.

type

Type of data : realized or forecast.

value

Value in giga-watt per hour.

Source

Rte (Electricity Transmission Network in France) (https://data.rte-france.com/)

eco2mix data

Description

The dataset contains data about electricity consumption and production in France between 2012 and 2022.

Usage

eco2mix

Format

A data frame with 3,033 observations and 3 variables.

Source

Rte (Réseau et transport d'électricité) (https://www.rte-france.com/eco2mix and https://opendata.reseaux-energies.fr/)

Events options

Description

Events options

Usage

events_opts(
  click = NULL,
  beforeMount = NULL,
  mounted = NULL,
  updated = NULL,
  legendClick = NULL,
  selection = NULL,
  dataPointSelection = NULL,
  dataPointMouseEnter = NULL,
  dataPointMouseLeave = NULL,
  beforeZoom = NULL,
  zoomed = NULL,
  scrolled = NULL,
  ...
)

Arguments

Value

A list of options that can be used in ax_chart.

Note

All arguments should be JavaScript function defined with htmlwidgets::JS.

See https://apexcharts.com/docs/options/chart/events/.

Examples

if (interactive()) {
  library(shiny)
  
  ui <- fluidPage(
    fluidRow(
      column(
        width = 8, offset = 2,
        tags$h2("Apexchart in Shiny"),
        apexchartOutput("chart"),
        verbatimTextOutput(outputId = "res_click")
      )
    )
  )
  
  server <- function(input, output, session) {
    
    output$chart <- renderApexchart({
      apexchart() %>%
        ax_chart(
          type = "bar",
          events = events_opts(
            dataPointSelection = JS(
              "function(event, chartContext, config) {
               Shiny.setInputValue('click', config.selectedDataPoints)
              }"
            ) 
          )
        ) %>%
        ax_series(
          list(
            name = "Example",
            data = sample(1:100, 5)
          )
        ) %>%
        ax_xaxis(
          categories = LETTERS[1:5]
        )
    })
    
    output$res_click <- renderPrint({
      input$click
    })
  }
  
  shinyApp(ui, server)
}

Format date in JS

Description

Format date in JS

Usage

format_date(x)

Arguments

Value

a JavaScript string

Format numbers (with D3)

Description

Format numbers (with D3)

Usage

format_num(format, prefix = "", suffix = "", locale = "en-US")

Arguments

Value

a JS function

Examples

# Use SI prefix
dat <- data.frame(
  labels = c("apex", "charts"),
  values = c(1e4, 2e4)
)

apex(dat, aes(labels, values), "column") %>% 
  ax_yaxis(labels = list(
    formatter = format_num("~s")
  ))

apex(dat, aes(labels, values * 100), "column") %>% 
  ax_yaxis(labels = list(
    formatter = format_num("~s")
  ))


# Percentage
dat <- data.frame(
  labels = c("apex", "charts"),
  values = c(0.45, 0.55)
)

apex(dat, aes(labels, values), "column") %>% 
  ax_yaxis(labels = list(
    formatter = format_num(".0%")
  ))


# Currency
dat <- data.frame(
  labels = c("apex", "charts"),
  values = c(570, 1170)
)

apex(dat, aes(labels, values), "column") %>% 
  ax_yaxis(labels = list(
    formatter = format_num("$,.2f")
  ))

# Change locale
apex(dat, aes(labels, values), "column") %>% 
  ax_yaxis(labels = list(
    formatter = format_num("$,.2f", locale = "fr-FR")
  ))



# Customize tooltip value
# Use SI prefix
dat <- data.frame(
  labels = c("apex", "charts"),
  values = c(1e4, 2e4)
)

apex(dat, aes(labels, values), "column") %>% 
  ax_tooltip(y = list(
    formatter = format_num(",", suffix = " GW/h")
  ))

Heatmap options

Description

Use these options in ax_plotOptions().

Usage

heatmap_opts(
  radius = NULL,
  enableShades = NULL,
  shadeIntensity = NULL,
  colorScale = NULL,
  ...
)

Arguments

Value

A list of options that can be used in ax_plotOptions().

Note

See https://apexcharts.com/docs/options/plotoptions/heatmap/.

Examples

df <- expand.grid(
  month = month.name,
  person = c("Obi-Wan", "Luke", "Anakin", "Leia")
)
df$value <- sample(0:1, nrow(df), TRUE)

apex(
  data = df,
  mapping = aes(x = month, y = person, fill = value),
  type = "heatmap"
) %>% 
  ax_plotOptions(
    heatmap = heatmap_opts(
      enableShades = FALSE,
      colorScale = list(
        ranges = list(
          list(from = 0, to = 0.5, color = "#FF0000"),
          list(from = 0.5, to = 1, color = "#088A08")
        )
      )
    )
  )
  

Label for annotations

Description

Label for annotations

Usage

label(
  text = NULL,
  borderColor = NULL,
  borderWidth = NULL,
  textAnchor = NULL,
  position = NULL,
  offsetX = NULL,
  offsetY = NULL,
  background = NULL,
  color = NULL,
  fontSize = NULL,
  fontWeight = NULL,
  fontFamily = NULL,
  cssClass = NULL,
  padding = c(2, 5, 2, 5)
)

Arguments

Value

A list that can be used in add_shade, add_point, add_event, add_event_marker.

Life expectancy data

Description

The dataset contains data about life expectancy in 1972 and 2007 for 10 countries.

Usage

life_expec

Format

A data frame with 10 observations and 4 variables.

Source

gapminder package (https://jennybc.github.io/gapminder/ and https://www.gapminder.org/data/)

Life expectancy data (long format)

Description

The dataset contains data about life expectancy in 1972 and 2007 for 10 countries.

Usage

life_expec_long

Format

A data frame with 20 observations and 3 variables.

Source

gapminder package (https://jennybc.github.io/gapminder/ and https://www.gapminder.org/data/)

Convert a data.frame to a list

Description

Convert data to a format suitable for ApexCharts.js

Usage

parse_df(data, add_names = FALSE)

Arguments

Value

A list that can be used to specify data in ax_series for example.

Examples

# All iris dataset
parse_df(iris)

# Keep variables names
parse_df(iris[, 1:2], add_names = TRUE)

# Use custom names

parse_df(iris[, 1:2], add_names = c("x", "y"))

Pie options

Description

Use these options in ax_plotOptions().

Usage

pie_opts(
  size = NULL,
  donut = NULL,
  customScale = NULL,
  offsetX = NULL,
  offsetY = NULL,
  dataLabels = NULL,
  ...
)

Arguments

Value

A list of options that can be used in ax_plotOptions().

Note

See https://apexcharts.com/docs/options/plotoptions/pie/.

Examples

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

apex(mpg, aes(cyl), type = "donut") %>%
  ax_plotOptions(
    pie = pie_opts(
      donut = list(size = "90%", background = "#BABABA")
    )
  )

Radial bar options

Description

Use these options in ax_plotOptions().

Usage

radialBar_opts(
  size = NULL,
  inverseOrder = NULL,
  startAngle = NULL,
  endAngle = NULL,
  offsetX = NULL,
  offsetY = NULL,
  hollow = NULL,
  track = NULL,
  dataLabels = NULL,
  ...
)

Arguments

Value

A list of options that can be used in ax_plotOptions().

Note

See https://apexcharts.com/docs/options/plotoptions/radialbar/.

Examples

apexchart() %>% 
  ax_chart(type = "radialBar") %>% 
  ax_plotOptions(
    radialBar = radialBar_opts(
      startAngle = -135,
      endAngle = 135,
      dataLabels = list(
        name = list(
          fontSize = "16px",
          # color = undefined,
          offsetY = 120
        ),
        value = list(
          offsetY = 76,
          fontSize = "22px",
          # color = undefined,
          formatter = htmlwidgets::JS("function (val) {return val + '%';}")
        )
      )
    )
  ) %>% 
  ax_stroke(dashArray = 4) %>% 
  ax_series(70) %>% 
  ax_labels("Indicator")

Run Shiny input events examples

Description

Run Shiny input events examples

Usage

run_demo_input(example = c("click", "zoom", "selection"))

Arguments

Examples

if (interactive()) {

  run_demo_input("click")
  run_demo_input("zoom")
  run_demo_input("selection")

}

Run Shiny spark boxes example

Description

Run Shiny spark boxes example

Usage

run_demo_sparkbox()

Examples

if (interactive()) {

  run_demo_sparkbox()

}

Run Shiny synchronization example

Description

Run Shiny synchronization example

Usage

run_demo_sync()

Examples

if (interactive()) {

  run_demo_sync()

}

Retrieve click information in Shiny

Description

According to type of chart, different values are retrieved:

• bar and column: retrieve category (x-axis).

• pie and donut: retrieve label.

• time-series: retrieve x-axis value, you have to display markers with size > 0 and set tooltip's options intersect = TRUE and shared = FALSE.

• scatter: retrieve XY coordinates.

Usage

set_input_click(
  ax,
  inputId,
  multiple = FALSE,
  effect_type = c("darken", "lighten", "none"),
  effect_value = 0.35,
  session = shiny::getDefaultReactiveDomain()
)

Arguments

Value

An apexchart() htmlwidget object.

Note

If x-axis is of type datetime, value retrieved is of class POSIXct.

Examples

library(apexcharter)

# Not in Shiny but you can still click on bars
data.frame(
  month = month.abb,
  value = sample(1:100, 12)
) %>% 
  apex(aes(month, value)) %>% 
  set_input_click("month_click", multiple = TRUE)


# Interactive examples:
if (interactive()) {

  run_demo_input("click")

}

Retrieve chart's base64 dataURI.

Description

Retrieve chart's base64 dataURI.

Usage

set_input_export(ax, inputId, session = shiny::getDefaultReactiveDomain())

Arguments

Value

An apexchart() htmlwidget object.

Examples

library(shiny)
library(apexcharter)

ui <- fluidPage(
  fluidRow(
    column(
      width = 8, offset = 2,
      tags$h2("Export PNG"),
      actionButton("redraw", "Redraw chart"),
      apexchartOutput("chart"),
      verbatimTextOutput("result"),
      uiOutput(outputId = "image")
    )
  )
)

server <- function(input, output, session) {
  
  output$chart <- renderApexchart({
    input$redraw
    apexchart() %>%
      ax_chart(type = "bar") %>%
      ax_series(
        list(
          name = "Example",
          data = sample(1:100, 5)
        )
      ) %>%
      ax_xaxis(
        categories = LETTERS[1:5]
      ) %>% 
      set_input_export("export")
  })
  
  output$result <- renderPrint({
    input$export
  })

  output$image <- renderUI({
    tags$img(src = input$export)
  })
  
}

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

Retrieve selection information in Shiny

Description

Retrieve selection information in Shiny

Usage

set_input_selection(
  ax,
  inputId,
  type = c("x", "xy", "y"),
  fill_color = "#24292e",
  fill_opacity = 0.1,
  stroke_width = 1,
  stroke_dasharray = 3,
  stroke_color = "#24292e",
  stroke_opacity = 0.4,
  xmin = NULL,
  xmax = NULL,
  ymin = NULL,
  ymax = NULL,
  session = shiny::getDefaultReactiveDomain()
)

Arguments

Value

An apexchart() htmlwidget object.

Examples

library(apexcharter)
data("economics", package = "ggplot2")

# Not in Shiny so no events
# but you can still select an area on chart
apex(economics, aes(date, psavert), type = "line") %>% 
  set_input_selection("selection")

# Default selection at start
apex(economics, aes(date, psavert), type = "line") %>% 
  set_input_selection(
    inputId = "selection", 
    xmin = format_date("1980-01-01"), 
    xmax = format_date("1985-01-01")
  )

Retrieve zoom information in Shiny

Description

Retrieve zoom information in Shiny

Usage

set_input_zoom(ax, inputId, session = shiny::getDefaultReactiveDomain())

Arguments

Value

An apexchart() htmlwidget object.

Note

If x-axis is of type datetime, value retrieved is of class POSIXct.

Examples

if (interactive()) {

  run_demo_input("zoom")

}

Fixed tooltip

Description

Fixed tooltip

Usage

set_tooltip_fixed(
  ax,
  position = c("topLeft", "topRight", "bottomLeft", "bottomRight"),
  offsetX = NULL,
  offsetY = NULL
)

Arguments

Value

An apexchart() htmlwidget object.

Examples

library(apexcharter)
data("economics", package = "ggplot2")

apex(
  data = tail(economics, 350), 
  mapping = aes(x = date, y = uempmed),
  type = "line"
) %>% 
  set_tooltip_fixed()

Create a box with a sparkline

Description

Create a box with a sparkline

Usage

spark_box(
  data,
  title = NULL,
  subtitle = NULL,
  color = "#2E93fA",
  background = "#FFF",
  type = c("area", "line", "spline", "column"),
  synchronize = NULL,
  title_style = NULL,
  subtitle_style = NULL,
  width = NULL,
  height = NULL,
  elementId = NULL
)

Arguments

Value

An apexcharts htmlwidget object.

Note

In Shiny use sparkBoxOutput / renderSparkBox to render boxes, see example. Boxes have CSS class "apexcharter-spark-box" if you need more styling.

Examples

library(apexcharter)

spark_data <- data.frame(
  date = Sys.Date() + 1:20,
  var1 = round(rnorm(20, 50, 10)),
  var2 = round(rnorm(20, 50, 10)),
  var3 = round(rnorm(20, 50, 10))
)

spark_box(
  data = spark_data,
  title = mean(spark_data$var1), 
  subtitle = "Variable 1"
)


# In Shiny
if (interactive()) {
  run_sparkbox_demo()
}

Temperature data

Description

The dataset contains data about temperatures in France between 2018 and 2022.

Usage

temperatures

Format

A data frame with 365 observations and 6 variables.

Source

Enedis (https://data.enedis.fr/explore/dataset/donnees-de-temperature-et-de-pseudo-rayonnement/)

UNHCR data by continent of origin

Description

The dataset contains data about UNHCR's populations of concern summarised by continent of origin.

Usage

unhcr_ts

Format

A data frame with 913 observations and the following 4 variables:

year

Year concerned.

population_type

Populations of concern : Refugees, Asylum-seekers, Internally displaced persons (IDPs), Returned refugees, Returned IDPs, Stateless persons, Others of concern.

continent_origin

Continent of residence of population.

n

Number of people concerned.

Source

UNHCR (The UN Refugee Agency) (https://data.unhcr.org/)