An htmlwidget interface to the VChart javascript chart library

Description

This package allow you to use VChart.js (https://www.visactor.io/vchart), to create interactive charts.

Author(s)

Victor Perrier (@dreamRs_fr)

See Also

Useful links:

• https://dreamrs.github.io/vchartr/

Pipe operator

Description

See magrittr::%>% for details.

Usage

lhs %>% rhs

Arguments

Value

The result of calling rhs(lhs).

Mark character strings as literal JavaScript code

Description

See htmlwidgets::JS() for details.

Usage

JS(...)

Arguments

Value

A string that will be interpreted as JavaScript code in htmlwidgets.

Construct aesthetic mappings

Description

See ggplot2::aes() for details.

Usage

aes(x, y, ...)

Arguments

Value

A list with class uneval. Components of the list are either quosures or constants.

CO2 emissions

Description

This dataset represents CO2 emissions for a subset of country over the period 1990 - 2022.

Usage

co2_emissions

Format

A data frame with 495 observations and 11 variables:

• country : Country - Geographic location.

• year : Year - Year of observation.

• co2 : Annual CO2 emissions - Annual total emissions of carbon dioxide (CO2), excluding land-use change, measured in million tonnes.

• co2_per_gdp : Annual CO2 emissions per GDP (kg per international-$) - Annual total emissions of carbon dioxide (CO2), excluding land-use change, measured in kilograms per dollar of GDP (2011 international-$).

• co2_per_capita : Annual CO2 emissions (per capita) - Annual total emissions of carbon dioxide (CO2), excluding land-use change, measured in tonnes per person.

• co2_growth_abs : Annual CO2 emissions growth (abs) - Annual growth in total emissions of carbon dioxide (CO2), excluding land-use change, measured in million tonnes.

• co2_growth_prct : Annual CO2 emissions growth (%) - Annual percentage growth in total emissions of carbon dioxide (CO2), excluding land-use change.

• co2_per_unit_energy : Annual CO2 emissions per unit energy (kg per kilowatt-hour) - Annual total emissions of carbon dioxide (CO2), excluding land-use change, measured in kilograms per kilowatt-hour of primary energy consumption.

• consumption_co2 : Annual consumption-based CO2 emissions - Annual consumption-based emissions of carbon dioxide (CO2), measured in million tonnes.

• consumption_co2_per_capita : Per capita consumption-based CO2 emissions - Annual consumption-based emissions of carbon dioxide (CO2), measured in tonnes per person.

• consumption_co2_per_gdp : Annual consumption-based CO2 emissions per GDP (kg per international-$) - Annual consumption-based emissions of carbon dioxide (CO2), measured in kilograms per dollar of GDP (2011 international-$).

Note

Documentation is from Our World In Data, see https://github.com/owid/co2-data for the data and https://ourworldindata.org/co2-and-greenhouse-gas-emissions for more about CO2 emissions.

Source

Our World In Data

World CO2 emissions

Description

This dataset contains world polygons with CO2 emissions.

Usage

co2_world

Format

A data frame with 495 observations and 11 variables:

• iso_code : ISO code A3 for country.

• name : Name of country.

• co2 : Annual CO2 emissions - Annual total emissions of carbon dioxide (CO2), excluding land-use change, measured in million tonnes.

• co2_per_capita : Annual CO2 emissions (per capita) - Annual total emissions of carbon dioxide (CO2), excluding land-use change, measured in tonnes per person.

• geometry : Geographical attributes.

Note

Documentation is from Our World In Data, see https://github.com/owid/co2-data for the data and https://ourworldindata.org/co2-and-greenhouse-gas-emissions for more about CO2 emissions.

Source

Our World In Data

Countries GDP

Description

These data represent the GDP of the world's countries, classified by continent and sub-region. This is a subset of the dataset rnaturalearth::countries110.

Usage

countries_gdp

Format

A data frame with 177 observations and 3 variables:

• REGION_UN : Continent

• SUBREGION : Sub-region in the continent

• ADMIN : Administrative name of country

• GDP_MD : GDP

Source

Package rnaturalearth

Monthly electricity generation by source in France

Description

This dataset represents monthly electricity generation by source in France over the period 2012 - 2024.

Usage

eco2mix

Format

A data frame with 151 observations and 10 variables:

• date : Date

• fuel : Fuel generation in MW

• coal : Coal generation in MW

• gas : Gas generation in MW

• nuclear : Nuclear generation in MW

• wind : Wind generation in MW

• solar : Solar generation in MW

• hydraulic : Hydraulic generation in MW

• pumping : Pumping generation in MW

• bioenergies : Bioenergies generation in MW

Source

eco2mix

Monthly electricity generation by source in France (long format)

Description

This dataset represents monthly electricity generation by source in France over the period 2012 - 2024.

Usage

eco2mix_long

Format

A data frame with 1359 observations and 3 variables:

• date : Date

• source : Production according to the different sectors making up the energy mix.

• production : Generation in MW

Source

eco2mix

Electricity mix for 10 countries

Description

This dataset represents the electricity mix of 10 countries (those with the highest electricity generation) in 2023.

Usage

electricity_mix

Format

A data frame with 70 observations and 3 variables:

• country : Country name

• source : source of electricity

• generation : Total electricity generation - Measured in terawatt-hours.

• type : Low carbon or fossil fuels type of source.

Source

Our World In Data

Data for Sankey Chart

Description

These data represent how energy is converted or transmitted before being consumed or lost.

Usage

energy_sankey

Format

A data frame with 177 observations and 3 variables:

• source : Source

• target : Target

• value : Energy in TWh

Source

Department of Energy & Climate Change via Tom Counsell

Format date with dayjs JavaScript library

Description

Format date with dayjs JavaScript library

Usage

format_date_dayjs(format, prefix = "", suffix = "", locale = "en")

format_datetime_dayjs(
  format,
  prefix = "",
  suffix = "",
  locale = "en",
  tz = NULL
)

label_format_date(format)

label_format_datetime(format, tz = NULL)

Arguments

Value

a JS function.

Examples

library(vchartr)



### Format date

# date in french in %B %y format
vchart(eco2mix) %>%
  v_line(aes(date, solar)) %>%
  v_scale_x_date(
    date_labels = format_date_dayjs("MMMM YY", locale = "fr")
  )

# date in arabic in %A %d %b %Y format
vchart(eco2mix) %>%
  v_line(aes(date, solar)) %>%
  v_scale_x_date(
    date_labels = format_date_dayjs("dddd D MMM YYYY", locale = "ar")
  )

Format numbers with D3

Description

Format numbers with D3

Usage

format_num_d3(format, prefix = "", suffix = "", locale = "en-US")

Arguments

Value

a JS function.

Examples

library(vchartr)

Useful labeller functions

Description

See ggplot2::label_value() for details.

Usage

label_value(labels, multi_line = TRUE)

Arguments

Value

Labels to be used in a facetted chart.

Add a rectangle annotation to a chart

Description

Add a rectangle annotation to a chart

Usage

v_mark_rect(
  vc,
  xmin = NULL,
  xmax = NULL,
  ymin = NULL,
  ymax = NULL,
  .area.style.fill = "grey35",
  .area.style.fillOpacity = 0.3,
  .label.text = NULL,
  .label.position = "insideTop",
  .label.refY = 0,
  .label.refX = 0
)

v_mark_polygon(
  vc,
  coords,
  .area.style.fill = "grey35",
  .area.style.fillOpacity = 0.3,
  .label.text = NULL,
  .label.position = "insideTop",
  .label.refY = 0,
  .label.refX = 0
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

# Draw a rectangle
vchart(cars) %>%
  v_scatter(aes(speed, dist)) %>%
  v_mark_rect(
    xmin = 10,
    xmax = 18,
    ymin = 20,
    ymax = 50
  )

# don't provide x or y to reach chart's limit
vchart(cars) %>%
  v_scatter(aes(speed, dist)) %>%
  v_mark_rect(
    xmin = 10,
    xmax = 18
  )
vchart(cars) %>%
  v_scatter(aes(speed, dist)) %>%
  v_mark_rect(
    ymin = 10,
    ymax = 18
  )


vchart(cars) %>%
  v_scatter(aes(speed, dist)) %>%
  v_mark_rect(
    xmin = "50%",
    xmax = "100%", # from right to left
    ymin = "50%",
    ymax = "100%" # note that for y it's from top to bottom
  )


# Whith date scale
vchart(temperatures) %>%
  v_line(aes(date, average)) %>%
  v_mark_rect(
    xmin = as.Date("2024-06-20"),
    xmax = as.Date("2024-09-22"),
    .label.text = "Summer"
  )


# Draw a polygon
vchart(cars) %>%
  v_scatter(aes(speed, dist)) %>%
  v_mark_polygon(
    coords = list(
      x = c(7, 22, 15),
      y = c(10, 50, 80)
    )
  )

Add an horizontal or vertical line to a chart

Description

Add an horizontal or vertical line to a chart

Usage

v_mark_vline(
  vc,
  x,
  ...,
  .line.style.stroke = "#000",
  .line.style.lineDash = list(8, 8),
  .label.text = NULL,
  .label.position = "end",
  .label.refY = 0,
  .label.refX = 0,
  .endSymbol.style.visible = FALSE,
  .startSymbol.style.visible = FALSE
)

v_mark_hline(
  vc,
  y,
  ...,
  .line.style.stroke = "#000",
  .line.style.lineDash = list(8, 8),
  .label.text = NULL,
  .label.position = "insideEndBottom",
  .label.refY = -10,
  .label.refX = 0,
  .endSymbol.style.visible = FALSE,
  .startSymbol.style.visible = FALSE
)

v_mark_segment(
  vc,
  x,
  xend,
  y,
  yend,
  ...,
  .line.style.stroke = "#000",
  .line.style.lineDash = list(8, 8),
  .label.text = NULL,
  .label.position = "insideEndBottom",
  .label.refY = -10,
  .label.refX = 0,
  .endSymbol.style.visible = FALSE,
  .startSymbol.style.visible = FALSE
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

# Vertical line
vchart(meteo_paris) %>%
  v_line(aes(month, temperature_avg)) %>%
  v_mark_vline(x = "May")

# Vertical lines with labels
vchart(meteo_paris) %>%
  v_line(aes(month, temperature_avg)) %>%
  v_mark_vline(
    x = c("May", "September"),
    .label.text = c("May", "September")
  )

# Horizontal line
vchart(meteo_paris) %>%
  v_line(aes(month, temperature_avg)) %>%
  v_mark_hline(y = 12)

# Both horizontal and vertical lines
vchart(meteo_paris) %>%
  v_line(aes(month, temperature_avg)) %>%
  v_mark_vline(x = "May") %>%
  v_mark_hline(y = 12)

# lines on a scatter plot
vchart(cars) %>%
  v_scatter(aes(speed, dist)) %>%
  v_mark_vline(x = mean(cars$speed)) %>%
  v_mark_hline(y = mean(cars$dist))

# segment
vchart(cars) %>%
  v_scatter(aes(speed, dist)) %>%
  v_mark_segment(x = 8, xend = 22, y = 12, yend = 100)

# line on date scale
vchart(temperatures) %>%
  v_line(aes(date, average)) %>%
  v_mark_vline(x = as.Date("2024-06-20"))

# segment on date scale
vchart(temperatures) %>%
  v_line(aes(date, average)) %>%
  v_mark_segment(
    x = as.Date("2024-04-01"), xend = as.Date("2024-07-01"),
    y = 12, yend = 24,
    .line.style.lineDash = 0,
    .line.style.stroke = "firebrick"
  )

Paris climate

Description

This data contains information about the climate in Paris, France.

Usage

meteo_paris

Format

A data frame with 177 observations and 3 variables:

• month : Month of the year

• temperature_avg : Average temperature (°C)

• temperature_min : Average minimum temperature (°C)

• temperature_max : Average maximum temperature (°C)

• precipitation : Precipitation (mm)

• humidity : Humidity (%)

• rainy_days : Rainy days (days)

• sunshine_hours : Sunshine hours (h)

Source

Climate-data.org

Manual color scale

Description

Manual color scale

Discrete color scale

Usage

v_scale_color_manual(vc, values)

v_scale_fill_manual(vc, values)

v_scale_color_discrete(vc, palette)

v_scale_fill_discrete(vc, palette)

Arguments

Value

A vchart() htmlwidget object.

A vchart() htmlwidget object.

Examples

library(vchartr)

subset(electricity_mix, country %in% c("France", "Canada")) %>% 
  vchart() %>% 
  v_bar(aes(country, generation, fill = source)) %>% 
  v_scale_fill_manual(c(
    "oil" = "#80549f",
    "coal" = "#a68832",
    "solar" = "#d66b0d",
    "gas" = "#f20809",
    "wind" = "#72cbb7",
    "hydro" = "#2672b0",
    "nuclear" = "#e4a701"
  ))

vchart(palmerpenguins::penguins) %>%
  v_scatter(
    aes(x = flipper_length_mm, y = body_mass_g, color = species)
  ) %>%
  v_scale_color_manual(c(
    Adelie = "#ffa232",
    Chinstrap = "#33a2a2",
    Gentoo = "#b34df2"
  ))

library(vchartr)

subset(electricity_mix, country %in% c("France", "Canada")) %>% 
  vchart() %>% 
  v_bar(aes(country, generation, fill = source)) %>% 
  v_scale_fill_discrete("Okabe-Ito")

subset(electricity_mix, country %in% c("France", "Canada")) %>% 
  vchart() %>% 
  v_bar(aes(country, generation, fill = source)) %>% 
  v_scale_fill_discrete("ggplot2")

# or 
subset(electricity_mix, country %in% c("France", "Canada")) %>% 
  vchart() %>% 
  v_bar(aes(country, generation, fill = source)) %>% 
  v_scale_fill_discrete(palette.colors(palette = "ggplot2")[-1])

Axis scale for continuous data

Description

Axis scale for continuous data

Usage

v_scale_x_continuous(
  vc,
  name = NULL,
  breaks = NULL,
  pretty = TRUE,
  labels = NULL,
  labels_tooltip = labels,
  zero = NULL,
  min = NULL,
  max = NULL,
  ...,
  position = "bottom"
)

v_scale_y_continuous(
  vc,
  name = NULL,
  breaks = NULL,
  pretty = TRUE,
  labels = NULL,
  labels_tooltip = labels,
  zero = NULL,
  min = NULL,
  max = NULL,
  ...,
  position = "left"
)

v_scale_x_log(
  vc,
  name = NULL,
  breaks = NULL,
  pretty = TRUE,
  labels = NULL,
  labels_tooltip = labels,
  zero = NULL,
  min = NULL,
  max = NULL,
  ...,
  position = "bottom"
)

v_scale_y_log(
  vc,
  name = NULL,
  breaks = NULL,
  pretty = TRUE,
  labels = NULL,
  labels_tooltip = labels,
  zero = NULL,
  min = NULL,
  max = NULL,
  ...,
  position = "left"
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

# Add a title to the axis
vchart(top_generation) %>%
  v_bar(aes(country, electricity_generation)) %>%
  v_scale_y_continuous(name = "Electricity generation")

vchart(subset(world_electricity, type == "total")) %>% 
  v_bar(aes(year, generation, fill = source)) %>%
  v_scale_y_continuous(name = "Electricity generation")

# Specify number of breaks
vchart(top_generation) %>%
  v_bar(aes(country, electricity_generation)) %>%
  v_scale_y_continuous(breaks = 10)

# Specify breaks position
vchart(top_generation) %>%
  v_bar(aes(country, electricity_generation)) %>%
  v_scale_y_continuous(breaks = c(0, 5000, 10000))

# Format labels
vchart(top_generation) %>%
  v_bar(aes(country, electricity_generation)) %>%
  v_scale_y_continuous(labels = "~s")

# Format labels with options
vchart(top_generation) %>%
  v_bar(aes(country, electricity_generation)) %>%
  v_scale_y_continuous(labels = format_num_d3(",", suffix = " TWh", locale = "fr-FR"))

vchart(subset(world_electricity, type == "total")) %>% 
  v_bar(aes(year, generation, fill = source)) %>%
  v_scale_y_continuous(labels = format_num_d3(",", suffix = " TWh", locale = "fr-FR"))

Axis scale for date/time data

Description

Axis scale for date/time data

Usage

v_scale_x_date(
  vc,
  name = NULL,
  date_breaks = NULL,
  date_labels = NULL,
  date_labels_tooltip = date_labels,
  min = NULL,
  max = NULL,
  ...,
  position = "bottom"
)

v_scale_y_date(
  vc,
  name = NULL,
  date_breaks = NULL,
  date_labels = NULL,
  date_labels_tooltip = date_labels,
  min = NULL,
  max = NULL,
  ...,
  position = "left"
)

v_scale_x_datetime(
  vc,
  name = NULL,
  date_breaks = NULL,
  date_labels = NULL,
  date_labels_tooltip = date_labels,
  tz = NULL,
  min = NULL,
  max = NULL,
  ...,
  position = "bottom"
)

v_scale_y_datetime(
  vc,
  name = NULL,
  date_breaks = NULL,
  date_labels = NULL,
  date_labels_tooltip = date_labels,
  tz = NULL,
  min = NULL,
  max = NULL,
  ...,
  position = "left"
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

# Add a title to the axis
vchart(eco2mix) %>%
  v_line(aes(date, solar)) %>%
  v_scale_x_date(name = "Date")

# Specify number of labels
vchart(eco2mix) %>%
  v_line(aes(date, solar)) %>%
  v_scale_x_date(date_breaks = 5)

# Specify intervals between labels
vchart(eco2mix) %>%
  v_line(aes(date, solar)) %>%
  v_scale_x_date(date_breaks = "2 years")

# Format labels
vchart(eco2mix) %>%
  v_line(aes(date, solar)) %>%
  v_scale_x_date(date_labels = "MM-YYYY")

# Other format for labels
vchart(eco2mix) %>%
  v_line(aes(date, solar)) %>%
  v_scale_x_date(date_labels = "MMM YYYY")

# Format labels with locale
vchart(eco2mix) %>%
  v_line(aes(date, solar)) %>%
  v_scale_x_date(
    date_labels = format_date_dayjs("MMMM YY", locale = "fr")
  )

# Different formats in labels and tootlip
vchart(eco2mix) %>%
  v_line(aes(date, solar)) %>%
  v_scale_x_date(
    date_labels = "YYYY-MM",
    date_labels_tooltip = "MMMM YYYY"
  )

Axis scale for discrete data

Description

Axis scale for discrete data

Usage

v_scale_x_discrete(vc, name = NULL, ..., position = "bottom")

v_scale_y_discrete(vc, name = NULL, ..., position = "left")

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

Color scale for continuous data

Description

Color scale for continuous data

Usage

v_scale_colour_gradient(
  vc,
  name = NULL,
  low = "#132B43",
  high = "#56B1F7",
  limits = NULL,
  position = c("right", "bottom", "left", "top"),
  align = c("middle", "start", "end")
)

v_scale_fill_gradient(
  vc,
  name = NULL,
  low = "#132B43",
  high = "#56B1F7",
  limits = NULL,
  position = c("right", "bottom", "left", "top"),
  align = c("middle", "start", "end")
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)
data("penguins", package = "palmerpenguins")

vchart(penguins) %>%
  v_scatter(aes(
    x = bill_length_mm, 
    y = bill_depth_mm,
    color = body_mass_g
  )) %>% 
  v_scale_colour_gradient(
    name = "Body mass",
    low = "yellow",
    high = "red"
  )

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

Top CRAN downloads

Description

The dataset contains data about CRAN downloads retrieved with cranlogs::cran_top_downloads.

Usage

top_cran_downloads

Format

A data frame with 100 observations and 5 variables.

Source

cranlogs

Top electricity-generating countries

Description

This dataset represents the 10 countries with the highest electricity generation in 2023.

Usage

top_generation

Format

A data frame with 10 observations and 2 variables:

• country : Country name

• electricity_generation : Total electricity generation - Measured in terawatt-hours.

Source

Our World In Data

Create an Area Chart

Description

Create an Area Chart

Usage

v_area(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  stack = FALSE,
  area = list(style = list(curveType = "linear", fill = NULL, fillOpacity = NULL)),
  point = list(visible = FALSE),
  line = list(visible = FALSE),
  ...,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

# Basic Area Chart
vchart(eco2mix) %>%
  v_area(aes(date, solar))

# Two areas
vchart(eco2mix, aes(date)) %>%
  v_area(aes(y = wind)) %>%
  v_area(aes(y = solar))

# Line chart with discrete x axis
vchart(data.frame(month = month.abb, value = sample(1:50, 12))) %>%
  v_area(aes(month, value))

# Fill color
vchart(data.frame(month = month.abb, value = sample(1:50, 12))) %>%
  v_area(
    aes(month, value),
    area = list(
      style = list(fill = "firebrick", fill_opacity = 0.9)
    )
  )

# Smooth Area Chart
vchart(data.frame(month = month.abb, value = sample(1:50, 12))) %>%
  v_area(
    aes(month, value),
    area =  list(
      style = list(curveType = "monotone")
    )
  )

# Step Area Chart
vchart(data.frame(month = month.abb, value = sample(1:50, 12))) %>%
  v_area(
    aes(month, value),
    area = list(
      style = list(curveType = "stepAfter")
    )
  )

# Multiple areas
vchart(eco2mix_long) %>%
  v_area(aes(date, production, fill = source))

vchart(eco2mix_long) %>%
  v_area(
    aes(date, production, fill = source),
    stack = TRUE,
    area = list(
      style = list(fillOpacity = 1)
    )
  )


# Range area chart
vchart(temperatures, aes(date)) %>%
  v_area(aes(ymin = low, ymax = high)) %>%
  v_line(aes(y = average))

within(temperatures, {difference = `2024` - average}) %>%
  vchart(aes(date)) %>%
  v_area(
    aes(ymin = average, ymax = `2024`, difference = difference),
    area = list(
      style = list(
        fill = JS(
          "data => { return data.difference > 0 ? '#F68180' : '#2F64FF' ; }"
        ),
        fillOpacity = 1
      )
    )
  )

Create a Bar Chart

Description

Create a Bar Chart

Usage

v_bar(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  stack = FALSE,
  percent = FALSE,
  direction = c("vertical", "horizontal"),
  ...,
  serie_id = NULL,
  data_id = NULL,
  data_specs = list()
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

# Classic Bar Chart
vchart(top_generation) %>% 
  v_bar(aes(country, electricity_generation))

# Horizontal Bar Chart
vchart(top_generation) %>% 
  v_bar(aes(country, electricity_generation), direction = "horizontal")

# Grouped Bar Chart
vchart(subset(world_electricity, type == "total")) %>% 
  v_bar(aes(year, generation, fill = source))

# Horizontal Grouped Bar Chart
vchart(subset(world_electricity, type == "total")) %>% 
  v_bar(aes(year, generation, fill = source), direction = "horizontal")

# Stacked Bar Chart
vchart(subset(world_electricity, type == "total")) %>% 
  v_bar(aes(year, generation, fill = source), stack = TRUE)

# Percentage Stacked Bar Chart
vchart(subset(world_electricity, type == "total")) %>% 
  v_bar(aes(year, generation, fill = source), stack = TRUE, percent = TRUE)

Create a BoxPlot

Description

Create a BoxPlot

Usage

v_boxplot(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  ...,
  outliers = TRUE,
  args_outliers = NULL,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

data("penguins", package = "palmerpenguins")

vchart(penguins) %>% 
  v_boxplot(aes(species, flipper_length_mm))

vchart(penguins) %>% 
  v_boxplot(aes(species, flipper_length_mm, color = sex))


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

vchart(mpg) %>% 
  v_boxplot(aes(as.character(year), hwy))

vchart(mpg) %>% 
  v_boxplot(aes(class, hwy))

vchart(mpg) %>% 
  v_boxplot(aes(class, hwy, color = as.character(year)))

Create a Circle Packing Chart

Description

Create a Circle Packing Chart

Usage

v_circlepacking(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  drill = TRUE,
  use_root = FALSE,
  fill_opacity = JS("d => d.isLeaf ? 0.75 : 0.25;"),
  label_visible = JS("d => d.depth === 1;"),
  ...,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

vchart(countries_gdp) %>%
  v_circlepacking(
    aes(lvl1 = REGION_UN, lvl2 = SUBREGION, lvl3 = ADMIN, value = GDP_MD)
  )


# With root level
vchart(countries_gdp) %>%
  v_circlepacking(
    aes(lvl1 = REGION_UN, lvl2 = SUBREGION, lvl3 = ADMIN, value = GDP_MD),
    use_root = "World"
  )


# Custom colors
vchart(countries_gdp) %>%
  v_circlepacking(
    aes(lvl1 = REGION_UN, lvl2 = SUBREGION, lvl3 = ADMIN, value = GDP_MD)
  ) %>%
  v_scale_color_manual(c(
    Oceania = "#E6AB02",
    Africa = "#1B9E77",
    Americas = "#D95F02",
    Asia = "#E7298A",
    Europe = "#66A61E",
    Antarctica = "#7570B3"
  ))

# Bubble Chart
vchart(countries_gdp) %>%
  v_circlepacking(
    aes(ADMIN, GDP_MD),
    label_visible = JS("d => d.value > 261921;"), # 261921 = 3rd Qu.
  )

VChart events

Description

VChart events

Usage

v_event(vc, name, params, fun, ...)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

vchart(top_generation) %>% 
  v_bar(aes(country, electricity_generation)) %>% 
  v_event(
    name = "click",
    params = list(level = "mark", type = "bar"),
    fun = JS(
      "e => {",
      " console.log(e);",
      " alert(e.datum.x);",
      "}"
    )
  )

Facets for vchart

Description

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

Usage

v_facet_wrap(
  vc,
  facets,
  nrow = NULL,
  ncol = NULL,
  scales = c("fixed", "free", "free_y", "free_x"),
  labeller = label_value
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)
library(ggplot2)

# Use vars() to supply faceting variables:
vchart(mpg) %>% 
  v_scatter(aes(displ, hwy)) %>% 
  v_facet_wrap(vars(class))

# Control the number of rows and columns with nrow and ncol
vchart(mpg) %>% 
  v_scatter(aes(displ, hwy)) %>% 
  v_facet_wrap(vars(class), ncol = 3)

# You can facet by multiple variables
vchart(mpg) %>% 
  v_scatter(aes(displ, hwy)) %>% 
  v_facet_wrap(vars(cyl, drv))

# Use the `labeller` option to control how labels are printed:
vchart(mpg) %>% 
  v_scatter(aes(displ, hwy)) %>% 
  v_facet_wrap(vars(cyl, drv), labeller = label_both)

# To change the order in which the panels appear, change the levels
# of the underlying factor.
mpg$class2 <- reorder(mpg$class, mpg$displ)
vchart(mpg) %>% 
  v_scatter(aes(displ, hwy)) %>% 
  v_facet_wrap(vars(class2), ncol = 3)

# By default, the same scales are used for all panels. You can allow
# scales to vary across the panels with the `scales` argument.
vchart(mpg) %>% 
  v_scatter(aes(displ, hwy)) %>% 
  v_facet_wrap(vars(class), scales = "free")

Create a Gauge Chart

Description

Create a Gauge Chart

Usage

v_gauge(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  outerRadius = 0.8,
  innerRadius = 0.75,
  startAngle = -240,
  endAngle = 60,
  ...,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

vchart() %>%
  v_gauge(aes("My gauge", 0.8))

vchart() %>%
  v_gauge(
    aes("My gauge", 0.8),
    gauge = list(
      type = "circularProgress",
      cornerRadius = 20,
      progress = list(
        style = list(
          fill = "forestgreen"
        )
      ),
      track = list(
        style = list(
          fill = "#BCBDBC"
        )
      )
    ),
    pointer = list(
      style = list(
        fill = "#2F2E2F"
      )
    )
  )


vchart() %>%
  v_gauge(aes("My gauge", 0.8)) %>%
  v_scale_y_continuous(labels = ".0%")

Create a Heatmap Chart

Description

Create a Heatmap Chart

Usage

v_heatmap(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  ...,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

# Heatmap with continuous fill variable
vchart(co2_emissions) %>%
  v_heatmap(aes(x = year, y = country, fill = co2_per_capita))

# Change colors
vchart(co2_emissions) %>%
  v_heatmap(aes(x = year, y = country, fill = co2_per_capita)) %>%
  v_specs_colors(
    range = rev(
      c("#8C510A", "#BF812D", "#DFC27D", "#F6E8C3",
        "#C7EAE5", "#80CDC1", "#35978F", "#01665E")
    )
  )

# Heatmap with discrete fill variable
vchart(co2_emissions) %>%
  v_heatmap(aes(x = year, y = country, fill = co2_growth_change))

# Change colors
vchart(co2_emissions) %>%
  v_heatmap(aes(x = year, y = country, fill = co2_growth_change)) %>%
  v_scale_fill_manual(c(
    Increase = "firebrick",
    Decrease = "forestgreen"
  ))

Create an Histogram

Description

Create an Histogram

Usage

v_hist(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  stack = FALSE,
  bins = 30,
  binwidth = NULL,
  ...,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)
library(palmerpenguins)

# Create an histogram using a numeric variable
vchart(penguins) %>%
  v_hist(aes(flipper_length_mm))

# Customize some style properties
vchart(penguins) %>%
  v_hist(
    aes(flipper_length_mm),
    bar = list(
      style = list(
        stroke = "white",
        line_width = 1,
        fill = "forestgreen"
      )
    )
  )

# Use fill aesthetic to differentiate series
vchart(penguins) %>%
  v_hist(aes(flipper_length_mm, fill = species))

# Stack results
vchart(penguins) %>%
  v_hist(aes(flipper_length_mm, fill = species), stack = TRUE)

# Use custom colors
vchart(penguins) %>%
  v_hist(
    aes(flipper_length_mm, fill = species),
    bar = list(
      style = list(opacity = 0.5)
    )
  ) %>%
  v_scale_color_manual(c(
    Adelie = "#ffa232",
    Chinstrap = "#33a2a2",
    Gentoo = "#b34df2"
  ))

Create Jittered Points Scatter Chart

Description

Create Jittered Points Scatter Chart

Usage

v_jitter(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  width = NULL,
  height = NULL,
  ...,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

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

# With continuous x
vchart(mpg) %>% 
  v_jitter(aes(cyl, hwy))

# with discrete x
vchart(penguins) %>%  
  v_jitter(aes(species, bill_length_mm))

# Colour points
vchart(mpg) %>% 
  v_jitter(aes(cyl, hwy, colour = class))

# Use smaller width/height to emphasise categories
vchart(mpg) %>% 
  v_jitter(aes(cyl, hwy), width = 0.25)

# Use larger width/height to completely smooth away discreteness
vchart(mpg) %>% 
  v_jitter(aes(cty, hwy), width = 0.5, height = 0.5)

Set chart title and subtitle

Description

Set chart title and subtitle

Usage

v_labs(vc, title = NULL, subtitle = NULL, x = NULL, y = NULL)

Arguments

Value

A vchart() htmlwidget object.

Examples

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

vchart(table(Class = mpg$class), aes(Class, Freq)) %>%
  v_bar() %>%
  v_labs(
    title = "Title for the chart",
    subtitle = "A subtitle to be placed under the title"
  )

Create a Line Chart

Description

Create a Line Chart

Usage

v_line(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  line = list(style = list(curveType = "linear", lineDash = 0, stroke = NULL)),
  point = list(visible = FALSE),
  ...,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

# Basic Line Chart
vchart(eco2mix) %>% 
  v_line(aes(date, solar))

# Two lines
vchart(tail(eco2mix, 30), aes(date)) %>% 
  v_line(aes(y = solar)) %>% 
  v_line(aes(y = wind))

# Line chart with discrete x axis
vchart(data.frame(month = month.abb, value = sample(1:50, 12))) %>% 
  v_line(aes(month, value))

# Stroke color 
vchart(data.frame(month = month.abb, value = sample(1:50, 12))) %>% 
  v_line(
    aes(month, value),
    line = list(style = list(stroke = "firebrick"))
  )

# Smooth Line Chart
vchart(data.frame(month = month.abb, value = sample(1:50, 12))) %>% 
  v_line(
    aes(month, value), 
    line = list(style = list(curveType = "monotone"))
  )

# Step Line Chart
vchart(data.frame(month = month.abb, value = sample(1:50, 12))) %>% 
  v_line(
    aes(month, value),
    line = list(style = list(curveType = "stepAfter"))
  )

# Dash array 
vchart(data.frame(month = month.abb, value = sample(1:50, 12))) %>% 
  v_line(
    aes(month, value),
    line = list(style = list(lineDash = c(10, 10)))
  )

# Multiple lines
vchart(eco2mix_long) %>% 
  v_line(aes(date, production, color = source))

Create a Pie Chart

Description

Create a Pie Chart

Usage

v_pie(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  label = list(visible = TRUE),
  ...,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

# Basic Pie Chart
subset(world_electricity, year == 2023 & type == "total") %>%
  vchart() %>% 
  v_pie(aes(x = source, y = generation))

# Use custom colors
subset(world_electricity, year == 2023 & type == "total") %>%
  vchart() %>% 
  v_pie(aes(x = source, y = generation)) %>%
  v_scale_color_manual(c(
    "Low carbon" = "#a3be8c",
    "Fossil fuels" = "#4C566A"
  ))

# Customize tooltip
subset(world_electricity, year == 2023 & type == "total") %>%
  vchart() %>% 
  v_pie(aes(x = source, y = generation)) %>%
  v_specs_tooltip(
    mark = list(
      content = list(
        list(
          key = JS("datum => datum['x']"),
          value = JS("datum => Math.round(datum['y']) + ' TWh'")
        ),
        list(
          hasShape = FALSE,
          key = "Proportion",
          value = JS("datum => datum._percent_ + '%'")
        )
      )
    )
  )


# Nested Pie Chart
vchart() %>% 
  v_pie(
    data = subset(world_electricity, year == 2023 & type == "total"),
    mapping = aes(x = source, y = generation),
    outerRadius = 0.65,
    innerRadius = 0,
    label = list(
      visible = TRUE,
      position = "inside",
      rotate = FALSE,
      style = list(fill = "white")
    ),
    pie = list(
      style = list(
        stroke = "#FFFFFF",
        lineWidth = 2
      )
    )
  ) %>% 
  v_pie(
    data = subset(world_electricity, year == 2023 & type == "detail"),
    mapping = aes(x = source, y = generation),
    outerRadius = 0.8,
    innerRadius = 0.67,
    pie = list(
      style = list(
        stroke = "#FFFFFF",
        lineWidth = 2
      )
    )
  ) 

Create a Progress Chart

Description

Create a Progress Chart

Usage

v_progress(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  ...,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

vchart() %>%
  v_progress(aes(0.85, "My progress"))

data.frame(
  x = c(0.4, 0.3, 0.8, 0.6),
  y = paste("Course", 1:4)
) %>%
  vchart() %>%
  v_progress(
    aes(x, y),
    cornerRadius = 20,
    bandWidth = 30
  ) %>%
  v_scale_y_discrete(
    label = list(visible = TRUE),
    domainLine = list(visible = FALSE)
  )

Create a Radar Chart

Description

Create a Radar Chart

Usage

v_radar(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  ...,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

# Default radar chart
subset(electricity_mix, country == "Germany") %>%
  vchart() %>%
  v_radar(aes(source, generation))

# Without area
subset(electricity_mix, country == "Germany") %>%
  vchart() %>%
  v_radar(
    aes(source, generation),
    area = list(visible = FALSE)
  )


# Mutliple series
subset(electricity_mix, country %in% c("Germany", "Canada")) %>%
  vchart() %>%
  v_radar(aes(source, generation, color = country))



# Custom axes
subset(electricity_mix, country == "Germany") %>%
  vchart() %>%
  v_radar(aes(source, generation)) %>%
  v_scale_y_continuous(min = 0, max = 200)

subset(electricity_mix, country == "Germany") %>%
  vchart() %>%
  v_radar(aes(source, generation)) %>%
  v_scale_y_continuous(
    grid = list(smooth = FALSE),
    domainLine = list(visible = FALSE)
  ) %>%
  v_scale_x_discrete(
    label = list(space = 20),
    domainLine = list(visible = FALSE)
  )

Create a Sankey Chart

Description

Create a Sankey Chart

Usage

v_sankey(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  ...,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

# Basic Sankey Chart
vchart(energy_sankey) %>%
  v_sankey(aes(target, source, value = value))

# Some options
vchart(energy_sankey) %>%
  v_sankey(
    aes(target, source, value = value),
    nodeAlign = "left",
    nodeGap = 8,
    nodeWidth = 10,
    minNodeHeight = 4,
    link = list(
      state = list(
        hover = list(
          fillOpacity = 1
        )
      )
    )
  )


# With data as tree structure
titanic <- as.data.frame(Titanic)
vchart(titanic) %>%
  v_sankey(aes(
    lvl1 = Class,
    lvl2 = Sex,
    lvl3 = Age,
    lvl4 = Survived,
    value = Freq
  ))


# Only one level
titanic_class <- titanic %>%
  aggregate(data = ., Freq ~ Class + Survived, FUN = sum)

vchart(titanic_class) %>%
  v_sankey(aes(Survived, Class, value = Freq))

Size scale for continuous data

Description

Size scale for continuous data

Usage

v_scale_size(
  vc,
  name = NULL,
  range = c(5, 30),
  ...,
  position = c("right", "bottom", "left", "top"),
  align = c("middle", "start", "end")
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)
data("penguins", package = "palmerpenguins")

vchart(penguins) %>%
  v_scatter(aes(
    x = bill_length_mm, 
    y = bill_depth_mm,
    size = body_mass_g
  )) %>% 
  v_scale_size(
    name = "Body mass",
    range = c(1, 20)
  )

Create a Scatter Chart

Description

Create a Scatter Chart

Usage

v_scatter(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  ...,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)
data("penguins", package = "palmerpenguins")

# Basic scatter chart
vchart(penguins) %>%
  v_scatter(aes(x = flipper_length_mm, y = body_mass_g))

# Color series with discrete values
vchart(penguins) %>%
  v_scatter(aes(x = flipper_length_mm, y = body_mass_g, color = species))

# Color series with continuous values
vchart(penguins) %>%
  v_scatter(aes(x = bill_length_mm, y = bill_depth_mm, color = body_mass_g))

# Size of points
vchart(penguins) %>%
  v_scatter(aes(x = bill_length_mm, y = bill_depth_mm, size = body_mass_g))

# Size and color
vchart(penguins) %>%
  v_scatter(aes(
    x = bill_length_mm,
    y = bill_depth_mm,
    color = body_mass_g,
    size = body_mass_g
  ))

# With shapes
vchart(penguins) %>%
  v_scatter(
    aes(
      x = bill_length_mm,
      y = bill_depth_mm,
      color = species,
      shape = species
    )
  )



vchart(penguins) %>%
  v_scatter(
    aes(x = flipper_length_mm, y = body_mass_g, color = species)
  ) %>%
  v_scale_color_manual(c(
    Adelie = "#ffa232",
    Chinstrap = "#33a2a2",
    Gentoo = "#b34df2"
  ))

Create an Smooth Line Chart

Description

Create an Smooth Line Chart

Usage

v_smooth(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  method = NULL,
  formula = NULL,
  se = TRUE,
  n = 80,
  span = 0.75,
  ...,
  args_area = NULL,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

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

vchart(mpg, aes(displ, hwy)) %>%
  v_smooth()

vchart(mpg, aes(displ, hwy)) %>%
  v_smooth(se = FALSE)

vchart(mpg, aes(displ, hwy, color = class)) %>%
  v_smooth()

Specify configuration options for a vchart().

Description

Specify configuration options for a vchart().

Usage

v_specs(vc, ..., serie_id = NULL, drop_nulls = FALSE)

Arguments

Value

A vchart() htmlwidget object.

Examples

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

vchart(table(Class = mpg$class)) %>%
  v_bar(aes(Class, Freq)) %>%
  v_specs(
    label = list(visible = TRUE),
    color = list("firebrick")
  )

Axes configuration

Description

Axes configuration

Usage

v_specs_axes(
  vc,
  position = c("left", "bottom", "right", "top", "angle", "radius"),
  ...,
  remove = FALSE
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

# Configure some options for axes
vchart() %>%
  v_line(aes(x = month.name, y = sample(5:25, 12))) %>%
  v_specs_axes(
    position = "left",
    title = list(
      visible = TRUE,
      text = "Y axis title",
      position = "start"
    ),
    label = list(
      formatMethod = JS("val => `${val}°C`")
    ),
    domainLine = list(
      visible = TRUE,
      style = list(stroke = "#000")
    ),
    tick = list(
      visible = TRUE,
      tickStep = 2,
      tickSize = 6,
      style = list(stroke = "#000")
    ),
    grid = list(
      visible = TRUE,
      style = list(lineDash = list(0), stroke = "#6E6E6E", zIndex = 100)
    )
  )%>%
  v_specs_axes(
    position = "bottom",
    title = list(
      visible = TRUE,
      text = "X axis title",
      position = "end"
    ),
    domainLine = list(
      visible = TRUE,
      style = list(stroke = "#000")
    ),
    tick = list(
      visible = TRUE,
      tickStep = 2,
      tickSize = 6,
      style = list(stroke = "#000")
    ),
    grid = list(
      visible = TRUE,
      style = list(lineDash = list(0)),
      alternateColor = c("#F2F2F2", "#FFFFFF"),
      alignWithLabel = TRUE
    )
  )



# By default vline add an axe on the left
vchart() %>%
  v_line(aes(x = month.name, y = sample(5:25, 12))) %>%
  v_specs_axes(position = "left", remove = TRUE) %>%
  v_specs_axes(position = "right", type = "linear")

# Use secondary axes
vchart() %>%
  v_line(aes(x = month.name, y = sample(5:25, 12)), serie_id = "serie_left") %>%
  v_line(aes(x = month.name, y = sample(5:25 * 100, 12)), serie_id = "serie_right") %>%
  v_specs_axes(position = "left", seriesId = "serie_left") %>%
  v_specs_axes(position = "right", type = "linear", seriesId = "serie_right")

Set color(s) for chart

Description

Set color(s) for chart

Usage

v_specs_colors(vc, ...)

Arguments

Value

A vchart() htmlwidget object.

Examples

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

vchart(table(Class = mpg$class)) %>%
  v_bar(aes(Class, Freq)) %>%
  v_specs_colors("#8FBCBB")

Add crosshair to chart

Description

Add crosshair to chart

Usage

v_specs_crosshair(vc, ...)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

data.frame(month = month.abb, value = sample(1:50, 12)) %>% 
  vchart() %>% 
  v_line(aes(month, value)) %>% 
  v_specs_crosshair(
    xField = list(
      visible = TRUE,
      line = list(type = "rect"), 
      defaultSelect = list(
        axisIndex = 0, 
        datum = "May"
      ), 
      label = list(visible = TRUE)
    ), 
    yField = list(
      visible = TRUE, 
      defaultSelect = list(
        axisIndex = 1,
        datum = 30
      ), 
      line = list(
        style = list(
          lineWidth = 1, 
          opacity = 1, 
          stroke = "#000", 
          lineDash = c(2, 2)
        )
      ),
      label = list(visible = TRUE)
    )
  )

Add custom mark to chart

Description

Add custom mark to chart

Usage

v_specs_custom_mark(vc, ...)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

world_electricity %>% 
  subset(type == "detail") %>% 
  vchart() %>%
  v_bar(
    aes(source, generation, player = year),
    direction = "h",
    data_id = "mydata"
  ) %>%
  v_specs_custom_mark(
    type = "text",
    dataId = "mydata",
    style = list(
      textBaseline = "bottom",
      fontSize = 60,
      textAlign = "right",
      fontWeight = 700,
      text = JS("datum => datum.player"),
      x = JS(
        "(datum, ctx) => {",
        " return ctx.vchart.getChart().getCanvasRect().width - 50;",
        "}"
      ),
      y = JS(
        "(datum, ctx) => {",
        " return ctx.vchart.getChart().getCanvasRect().height - 150;",
        "}"
      ),
      fill = "grey",
      fillOpacity = 0.5
    )
  )

Add data zoom to a chart

Description

Add data zoom to a chart

Usage

v_specs_datazoom(
  vc,
  start = "{label:%Y-%m-%d}",
  end = "{label:%Y-%m-%d}",
  ...,
  brush = TRUE
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

data("economics", package = "ggplot2")
vchart(economics, aes(date, unemploy)) %>%
  v_line() %>%
  v_specs_datazoom()


co2_emissions %>%
  subset(country %in% c("China", "United States", "India")) %>%
  vchart() %>%
  v_line(aes(year, co2, color = country)) %>%
  v_specs_datazoom(start = "{label:.0f}", startValue = 1990, end = "{label:.0f}")

Add indicator to chart

Description

Add indicator to chart

Usage

v_specs_indicator(vc, ...)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

electricity_mix %>% 
  subset(country == "France") %>%
  vchart() %>% 
  v_pie(
    aes(x = source, y = generation),
    outerRadius = 0.8,
    innerRadius = 0.5,
    padAngle = 0.6
  ) %>%
  v_specs_tooltip(visible = FALSE) %>% 
  v_specs_indicator(
    visible = TRUE,
    trigger = "hover",
    limitRatio = 0.5,
    title = list(
      visible = TRUE,
      autoFit = TRUE,
      fitStrategy = "inscribed",
      style = list(
        fontWeight = "bolder",
        fill = "#888",
        text = JS("datum => datum !== null ? datum.x : ''")
      )
    ),
    content = list(
      list(
        visible = TRUE,
        autoFit = TRUE,
        fitStrategy = "inscribed",
        style = list(
          fontWeight = "bolder",
          fill = "#000",
          text = JS("datum => datum !== null ? Math.round(datum.y) + 'TWh' : ''")
        )
      )
    )
  )

Set legend options

Description

Set legend options

Usage

v_specs_legend(vc, ..., add = FALSE)

Arguments

Value

A vchart() htmlwidget object.

Examples

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

vchart(table(Class = mpg$class, Year = mpg$year)) %>%
  v_bar(aes(Class, Freq, fill = Year)) %>%
  v_specs_legend(
    title = list(text = "Title", visible = TRUE),
    orient = "right",
    position = "start",
    item = list(focus = TRUE)
  )

Set player options

Description

Set player options

Usage

v_specs_player(vc, ...)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

world_electricity %>% 
  subset(type == "detail") %>% 
  vchart() %>%
  v_bar(
    aes(source, generation, player = year)
  )

Set tooltip options

Description

Set tooltip options

Usage

v_specs_tooltip(vc, ..., .reset = FALSE)

Arguments

Value

A vchart() htmlwidget object.

Examples

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

vchart(table(Class = mpg$class, Year = mpg$year)) %>%
  v_bar(aes(Class, Freq, fill = Year)) %>%
  v_specs_tooltip(
    visible = FALSE
  )

Create a Sunburst Chart

Description

Create a Sunburst Chart

Usage

v_sunburst(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  drill = TRUE,
  gap = 5,
  ...,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

# Create a sunburst and auto hide labels
vchart(countries_gdp) %>%
  v_sunburst(
    aes(lvl1 = REGION_UN, lvl2 = SUBREGION, lvl3 = ADMIN, value = GDP_MD),
    gap = 10,
    labelAutoVisible = list(
      enable = TRUE
    ),
    labelLayout = list(
      align = "center",
      rotate = "radial"
    )
  )


# Custom tooltip
vchart(countries_gdp) %>%
  v_sunburst(
    aes(lvl1 = REGION_UN, lvl2 = SUBREGION, lvl3 = ADMIN, value = GDP_MD)
  ) %>% 
  v_specs_tooltip(
    mark = list(
      title = list(
        value = JS("val => val?.datum?.map(data => data.name).join(' / ')")
      )
    )
  )


# Custom layout options
vchart(countries_gdp) %>%
  v_sunburst(
    aes(lvl1 = REGION_UN, lvl2 = SUBREGION, lvl3 = ADMIN, value = GDP_MD),
    gap = 0,
    innerRadius = c(0, 0.4, 0.8),
    outerRadius = c(0.3, 0.7, 0.85),
    labelAutoVisible = list(
      enable = TRUE,
      circumference = 1
    ),
    labelLayout = list(
      list(
        align = "center",
        rotate = "tangential",
        offset = 0
      ),
      NULL,
      list(
        align = "start",
        rotate = "radial",
        offset = 15
      )
    )
  ) %>% 
  v_specs(padding = 70)

Theme for Charts

Description

Theme for Charts

Usage

v_theme(
  vc,
  .colorPalette = NULL,
  .backgroundColor = NULL,
  .borderColor = NULL,
  .shadowColor = NULL,
  .hoverBackgroundColor = NULL,
  .sliderRailColor = NULL,
  .sliderHandleColor = NULL,
  .sliderTrackColor = NULL,
  .popupBackgroundColor = NULL,
  .primaryFontColor = NULL,
  .secondaryFontColor = NULL,
  .tertiaryFontColor = NULL,
  .axisLabelFontColor = NULL,
  .disableFontColor = NULL,
  .axisMarkerFontColor = NULL,
  .axisGridColor = NULL,
  .axisDomainColor = NULL,
  .dataZoomHandleStrokeColor = NULL,
  .dataZoomChartColor = NULL,
  .playerControllerColor = NULL,
  .scrollBarSliderColor = NULL,
  .axisMarkerBackgroundColor = NULL,
  .markLabelBackgroundColor = NULL,
  .markLineStrokeColor = NULL,
  .dangerColor = NULL,
  .warningColor = NULL,
  .successColor = NULL,
  .infoColor = NULL,
  .discreteLegendPagerTextColor = NULL,
  .discreteLegendPagerHandlerColor = NULL,
  .discreteLegendPagerHandlerDisableColor = NULL,
  ...
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

chart <- subset(
  electricity_mix,
  country %in% c("Germany", "Brazil", "South Korea")
) %>%
  vchart() %>%
  v_bar(aes(country, generation, fill = source))

# Default appearance
chart

# Change background color
chart %>%
  v_theme(.backgroundColor = "#2F2E2F")

# Change default color palette
chart %>%
  v_theme(
    .colorPalette = palette.colors(n = 8, palette = "Okabe-Ito")[-1]
  )

# Axis grid color
chart %>%
  v_theme(.axisGridColor = "red")
# same as
chart %>%
  v_theme(
    component = list(
      axis = list(
        grid = list(
          style = list(
            # lineWidth = 3, # but more options available
            stroke = "red"
          )
        )
      )
    )
  )
# see https://www.unpkg.com/@visactor/vchart-theme@1.11.6/public/light.json
# for all possibilities

Create a Treemap Chart

Description

Create a Treemap Chart

Usage

v_treemap(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  drill = TRUE,
  ...,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

# Basic Treemap Chart
vchart(countries_gdp) %>%
  v_treemap(aes(lvl1 = REGION_UN, lvl2 = ADMIN, value = GDP_MD))

# With labels
vchart(countries_gdp) %>%
  v_treemap(
    aes(lvl1 = REGION_UN, lvl2 = ADMIN, value = GDP_MD),
    label = list(visible = TRUE)
  )

# Show all levels
vchart(countries_gdp) %>%
  v_treemap(
    aes(lvl1 = REGION_UN, lvl2 = ADMIN, value = GDP_MD),
    label = list(visible = TRUE),
    nonLeaf = list(visible = TRUE),
    nonLeafLabel = list(visible = TRUE, position = "top")
  )

Create a Venn Diagram

Description

Create a Venn Diagram

Usage

v_venn(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  sets_sep = ",",
  ...,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

# Venn diagram with 2 sets
data.frame(
  sets = c("A", "B", "A,B"),
  value = c(5, 10, 4)
) %>% 
  vchart() %>% 
  v_venn(aes(sets = sets, value = value))

# with more sets 
data.frame(
  sets = c("A", "B", "C", "A,B", "A,C", "B,C", "A,B,C"),
  value = c(8, 10, 12, 4, 4, 4, 2)
) %>% 
  vchart() %>% 
  v_venn(aes(sets = sets, value = value))


# More complex example
set.seed(20190708)
genes <- paste("gene",1:1000,sep="")
genes <- list(
  A = sample(genes,300), 
  B = sample(genes,525), 
  C = sample(genes,440),
  D = sample(genes,350)
)

vchart(stack(genes)) %>% 
  v_venn(aes(category = ind, values = values))

Create a Waterfall Chart

Description

Create a Waterfall Chart

Usage

v_waterfall(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  ...,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

balance <- data.frame(
  desc = c("Starting Cash",
           "Sales", "Refunds", "Payouts", "Court Losses",
           "Court Wins", "Contracts", "End Cash"),
  amount = c(2000, 3400, -1100, -100, -6600, 3800, 1400, 2800)
)

vchart(balance) %>% 
  v_waterfall(aes(x = desc, y = amount))


# With total values and formatting
data.frame(
  x = c("Feb.4", "Feb.11", "Feb.20", "Feb.25", "Mar.4", 
        "Mar.11", "Mar.19", "Mar.26", "Apr.1", "Apr.8",
        "Apr.15", "Apr.22", "Apr.29", "May.6", "total"),
  total = c(TRUE, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, TRUE),
  y = c(45L, -5L, 2L, -2L, 2L, 2L, -2L, 1L, 1L, 1L, 2L, 1L, -2L, -1L, NA)
) %>% 
  vchart() %>% 
  v_waterfall(
    aes(x = x, y = y, total = total),
    stackLabel = list(
      valueType = "absolute",
      formatMethod = JS("text => text + '%'")
    )
  ) %>% 
  v_specs_legend(visible = TRUE)

Create a Wordcloud

Description

Create a Wordcloud

Usage

v_wordcloud(
  vc,
  mapping = NULL,
  data = NULL,
  name = NULL,
  ...,
  serie_id = NULL,
  data_id = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Examples

library(vchartr)

vchart(top_cran_downloads) %>%
  v_wordcloud(aes(word = package, count = count))

vchart(top_cran_downloads) %>%
  v_wordcloud(aes(word = package, count = count, color = package))

vchart(top_cran_downloads) %>%
  v_wordcloud(
    aes(word = package, count = count, color = package),
    wordCloudConfig = list(
      zoomToFit = list(
        enlarge = TRUE,
        fontSizeLimitMax = 30
      )
    )
  )


# Use an image to shape the wordcloud
vchart(top_cran_downloads) %>%
  v_wordcloud(
    aes(word = package, count = count, color = package),
    maskShape = "https://jeroen.github.io/images/Rlogo.png"
  )
  

Quote faceting variables

Description

See ggplot2::vars() for details.

Usage

vars(...)

Arguments

Value

A list with class uneval. Components of the list are either quosures or constants.

Create interactive charts with VChart

Description

VChart is a charting component library, see more about it here : https://www.visactor.io/vchart.

Usage

vchart(
  data = NULL,
  mapping = NULL,
  ...,
  width = NULL,
  height = NULL,
  elementId = NULL
)

Arguments

Value

A vchart() htmlwidget object.

Note

This function allow you to use JavaScript function VChart directly, see https://www.visactor.io/vchart/option/ for how to specify options.

Examples

library(vchartr)

# Use JS syntax to construct chart
vchart(
  type = "line",
  data = list(
    list(
      values = list(
        list(month = "January", value = 4.3),
        list(month = "February", value = 4.6),
        list(month = "March", value = 7.4),
        list(month = "April", value = 10.7),
        list(month = "May", value = 14.3),
        list(month = "June", value = 17.7),
        list(month = "July", value = 19.8),
        list(month = "August", value = 19.4),
        list(month = "September", value = 16.4),
        list(month = "October", value = 12.6),
        list(month = "November", value = 7.9),
        list(month = "December", value = 4.8)
      )
    )
  ),
  xField = "month",
  yField = "value",
  crosshair = list(
    xField = list(visible = TRUE)
  )
)

# or use R API
vchart(meteo_paris) %>%
  v_line(aes(month, temperature_avg)) %>%
  v_specs(
    crosshair = list(
      xField = list(visible = TRUE)
    )
  )

# or
vchart(meteo_paris, aes(month, temperature_avg)) %>%
  v_line() %>%
  v_specs(
    crosshair = list(
      xField = list(visible = TRUE)
    )
  )

# or
vchart() %>%
  v_line(aes(month, temperature_avg), data = meteo_paris) %>%
  v_specs(
    crosshair = list(
      xField = list(visible = TRUE)
    )
  )

Shiny bindings for vchart

Description

Output and render functions for using vchart() within Shiny applications and interactive Rmd documents.

Usage

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

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

Arguments

Value

An output or render function that enables the use of the widget within Shiny applications.

Examples

library(shiny)
library(bslib)
library(vchartr)

ui <- page_fluid(
  tags$div(
    style = "max-width: 900px; margin: auto;",
    tags$h2("vchart in shiny"),
    radioButtons(
      inputId = "data",
      label = "Show:",
      choiceNames = c("electricity mix by country", "countries generation by sources"),
      choiceValues = c("mix", "sources"),
      inline = TRUE
    ),
    conditionalPanel(
      condition = "input.data == 'mix'",
      selectInput(
        inputId = "country",
        label = "Select country:",
        choices = unique(electricity_mix$country)
      )
    ),
    conditionalPanel(
      condition = "input.data == 'sources'",
      selectInput(
        inputId = "source",
        label = "Select source:",
        choices = unique(electricity_mix$source)
      )
    ),
    vchartOutput(outputId = "mychart", height = "500px"),
    radioButtons(
      inputId = "type",
      label = "Represent as:",
      choices = c("bar", "pie", "treemap", "circlepacking"),
      inline = TRUE
    ),
    checkboxInput(
      inputId = "show_label",
      label = "Show label ?"
    )
  )
)

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

  output$mychart <- renderVchart({

    if (input$data == "mix") {
      elec_data <- subset(electricity_mix, country == input$country)
      mapping <- aes(source, generation, fill = source)
    } else {
      elec_data <- subset(electricity_mix, source == input$source)
      mapping <- aes(country, generation, fill = country)
    }

    vc <- vchart(elec_data, mapping = mapping)
    if (input$type == "bar") {
      vc <- vc %>% 
        v_bar(serie_id = "bar_serie") %>%
        v_specs_legend(visible = FALSE) %>%
        v_specs(
          xField = "x",
          label = list(visible = input$show_label),
          serie_id = "bar_serie"
        )
    } else if (input$type == "pie") {
      vc <- vc %>% 
        v_pie(label = list(visible = input$show_label))
    } else if (input$type == "treemap") {
      vc <- vc %>% 
        v_treemap(label = list(visible = input$show_label))
    } else if (input$type == "circlepacking") {
      vc <- vc %>% 
        v_circlepacking(label = list(style = list(visible = input$show_label)))
    }
    vc %>%
      v_scale_color_manual(c(
        "oil" = "#80549f",
        "coal" = "#a68832",
        "solar" = "#d66b0d",
        "gas" = "#f20809",
        "wind" = "#72cbb7",
        "hydro" = "#2672b0",
        "nuclear" = "#e4a701"
      ))
  })

}

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

Create a Map

Description

Create a Map

Usage

vmap(
  data,
  mapping = NULL,
  ...,
  projection = NULL,
  width = NULL,
  height = NULL,
  elementId = NULL
)

Arguments

Value

A vmap() htmlwidget object.

Examples

if (rlang::is_installed(c("sf", "geojsonio"))) {
  
  library(vchartr)
  library(sf)
  
  # Create map from sf object
  vmap(co2_world)
  
  # Draw data on the map
  vmap(co2_world, aes(name = name, fill = co2_per_capita))
  
  # Change projection and colors
  vmap(
    co2_world,
    aes(name = name, fill = co2_per_capita), 
    projection = "equalEarth"
  ) %>% 
    v_specs_colors(
      range = c(
        "#FFFFE5", "#FFF7BC", "#FEE391", 
        "#FEC44F", "#FE9929", "#EC7014", 
        "#CC4C02", "#993404", "#662506"
      )
    ) %>% 
    v_specs_legend(
      orient = "bottom",
      type = "color",
      field = "fill"
    )
  
  # Map discrete data
  vmap(
    co2_world[!is.na(co2_world$co2_per_capita), ], 
    aes(
      name = name,
      fill = ifelse(co2_per_capita >= 2.3, "Above", "Under")
    )
  ) %>% 
    v_specs(
      area = list(
        style = list(
          stroke = "#FFFFFF"
        )
      )
    )
  
}

World low carbon & fossil electricity generation 2014 - 2023

Description

This dataset represents world's electricity generation from low-carbon sources and fossil fuels over the period 2014 - 2023.

Usage

world_electricity

Format

A data frame with 70 observations and 4 variables:

• year : Year

• source : Either :

  • ⁠Low carbon⁠ : Electricity generation from low-carbon sources - Low-carbon sources correspond to renewables and nuclear power, that produce significantly less greenhouse-gas emissions than fossil fuels.

  • Renewables : Electricity generation from renewables

  • Nuclear : Electricity generation from nuclear

  • Fossil : Electricity generation from fossil fuels (oil + gas + coal)

  • Oil : Electricity generation from fossil fuels

  • Gas : Electricity generation from fossil fuels

  • Coal : Electricity generation from fossil fuels

• generation : Electricity generation in terawatt-hours.

• type : Type of source : total or detail.

Source

Our World In Data