line

library(vchartr)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

Line Chart

co2_emissions %>% 
  filter(country %in% c("China", "United States", "India")) %>% 
  vchart() %>% 
  v_line(
    aes(year, co2, color = country),
    lineLabel = list(visible = TRUE)
  ) %>% 
  v_specs_legend(visible = FALSE) %>% 
  v_scale_y_continuous(
    name = "measured in million tonnes", 
    labels = ","
  ) %>% 
    v_scale_x_continuous(
    expand = list(max = 0.15)
  ) %>% 
  v_labs(
    title = "Annual CO₂ emissions",
    subtitle = "Source: Our World In Data"
  )

Line with data zoom

co2_emissions %>% 
  filter(country %in% c("China", "United States", "India")) %>% 
  vchart() %>% 
  v_line(
    aes(year, co2, color = country)
  ) %>% 
  v_specs_datazoom(
    start = "{label:.0f}",
    startValue = 2000, 
    end = "{label:.0f}"
  ) %>% 
  v_specs_legend(
    orient = "top",
    position = "start",
    layout = "vertical",
    layoutType = "absolute",
    left = 30,
    top = 20,
    item = list(
      shape = list(
        style = list(
          symbolType = "roundLine"
        )
      )
    )
  )

Line and area range

vchart(temperatures, aes(date)) %>% 
  v_area(
    aes(ymin = low, ymax = high),
    area = list(style = list(fill = "#848585", fillOpacity = 0.3)),
    name = "Low/high between 2019 and 2023"
  ) %>% 
  v_line(
    aes(y = `2024`), 
    line = list(style = list(stroke = "firebrick")),
  ) %>%
  v_scale_x_date(
    date_breaks = "2 months", 
    date_labels = "MMMM",
    date_labels_tooltip = "DD MMMM"
  ) %>% 
  v_scale_y_continuous(
    name = "Temperature in degree celsius",
    labels = format_num_d3(".0f", suffix = "°C"),
    labels_tooltip = format_num_d3(".3r", suffix = "°C")
  ) %>% 
  v_labs(
    title = "Temperatures in France in 2024 compared with previous years",
    subtitle = "Source: Enedis"
  ) %>% 
  v_specs_legend(
    visible = TRUE,
    orient = "top",
    position = "left"
  )

Area chart

vchart(eco2mix_long) %>% 
  v_area(
    aes(date, production, fill = source),
    stack = TRUE,
    area = list(
      style = list(
        fillOpacity = 0.6
      )
    )
  ) %>%
  v_scale_x_date(
    date_labels = "YYYY",
    date_labels_tooltip = "DD/MM/YYYY",
    date_breaks = "2 years"
  ) %>% 
  v_scale_y_continuous(
    min = -2000,
    labels = format_num_d3(",", locale = "fr-FR", suffix = " TWh")
  ) %>% 
  v_scale_color_manual(c(
    "oil" = "#80549f",
    "coal" = "#a68832",
    "solar" = "#d66b0d",
    "gas" = "#f20809",
    "wind" = "#72cbb7",
    "hydro" = "#2672b0",
    "nuclear" = "#e4a701",
    "pumping" = "#2f5673",
    "bioenergies" = "#156956"
  )) %>% 
  v_specs_legend(
    orient = "right",
    position = "middle",
    item = list(focus = TRUE),
    title = list(
      visible = TRUE,
      text = "Source"
    )
  ) %>% 
  v_specs_crosshair(
    xField = list(
      visible = TRUE,
      label = list(
        visible = TRUE, 
        formatMethod = label_format_date("DD/MM/YYYY"),
        style = list(
          fill = "#000"
        ),
        labelBackground = list(
          padding = 5,
          style = list(
            stroke = "#000",
            fill = "#19ff00"
          )
        )
      ),
      line = list(
        type = "line",
        width = 5,
        style = list(
          stroke = "#19ff00",
          lineDash = list(0)
        )
      )
    )
  )

Line with bar

vchart(meteo_paris) %>% 
  v_bar(
    aes(month, precipitation),
    serie_id = "precipitation",
    name = "Precipitation (mm)",
    bar = list(style = list(fill = "steelblue"))
  ) %>% 
  v_line(
    aes(month, temperature_avg),
    serie_id = "temperature", 
    point = list(
      visible = TRUE,
      style = list(fill = "firebrick")
    ),
    name = "Average temperature (°C)",
    line = list(style = list(stroke = "firebrick")),
    label = list(
      visible = TRUE,
      style = list(fill = "firebrick", strokeOpacity = 0)
    )
  ) %>% 
  v_scale_y_continuous(
    seriesId = "temperature",
    name = "Average temperature (°C)"
  ) %>% 
  v_scale_y_continuous(
    seriesId = "precipitation",
    name = "Precipitation (mm)",
    position = "right"
  ) %>% 
  v_labs(title = "Climate in Paris")

Left and right axis

data("economics", package = "ggplot2")
vchart(economics) %>% 
  v_line(
    aes(date, unemploy),
    serie_id = "unemploy",
    line = list(style = list(stroke = "#E69F00")),
  )%>% 
  v_line(
    aes(date, uempmed),
    serie_id = "uempmed",
    line = list(style = list(stroke = "#56B4E9")),
  ) %>% 
  v_scale_x_date(date_breaks = "10 years", date_labels = "YYYY", nice = FALSE) %>% 
  v_scale_y_continuous(
    seriesId = "unemploy",
    name = list(
      visible = TRUE,
      text = "number of unemployed, in thousands",
      position = "middle",
      shape = list(
        visible = TRUE,
        style = list(
          symbolType = "rect",
          fill = "#E69F00"
        )
      )
    )
  ) %>% 
  v_scale_y_continuous(
    seriesId = "uempmed",
    name = list(
      visible = TRUE,
      text = "median duration of unemployment, in weeks",
      position = "middle",
      shape = list(
        visible = TRUE,
        style = list(
          symbolType = "rect",
          fill = "#56B4E9"
        )
      )
    ),
    position = "right"
  ) %>% 
  v_labs(title = "US economic time series")