# Introduction - basic use

#### Victor Perrier

#### 2026-01-29

This package allow you to use billboard.js, a re-usable easy interface JavaScript chart library, based on D3 v4+.

Supported chart types:

- line
- bar
- pie / donut
- scatter

The main function is `billboarder`, all charts begin with. You can add layer to your charts with function `bb_*`, these functions correspond to a billboard option define in the API docs. There are helpers functions to quickly create a type of chart (`bb_barchart`, `bb_linechart`, `bb_piechart`, `bb_donutchart`, `bb_gauge`, `bb_scatterplot`), they have to be called after `billboarder`.

## Bar chart

You can create a simple bar chart by passing a `data.frame` to `bb_barchart`, the first column will be used as the x-axis, and the second one as the y-axis :

    library("billboarder")

    df <- as.data.frame(table(sample(letters[1:5], 50, TRUE)))
    df
    #>   Var1 Freq
    #> 1    a    9
    #> 2    b   15
    #> 3    c   10
    #> 4    d   11
    #> 5    e    5

    billboarder() %>%
      bb_barchart(data = df)

If you want to create a grouped bar chart, first option is to put your data in a “wide” format. Here we use `stats::reshape`, but I recommend to use `tidyr::spread` or `data.table::dcast`.

    df <- as.data.frame(table(
      sample(letters[1:5], 50, TRUE),
      sample(LETTERS[1:5], 50, TRUE)
    ))
    df.r <- reshape(data = df, idvar = "Var1", timevar = "Var2", direction = "wide")
    df.r
    #>   Var1 Freq.A Freq.B Freq.C Freq.D Freq.E
    #> 1    a      0      1      1      1      2
    #> 2    b      2      2      2      4      3
    #> 3    c      3      1      4      1      2
    #> 4    d      3      2      4      1      2
    #> 5    e      1      2      2      2      2

    billboarder() %>%
      bb_barchart(data = df.r)

Second option is to define a mapping of your variable with function `bbaes` (for more example of mapping, see vignette billboarder-mapping).

    billboarder() %>%
      bb_barchart(
        data = df,
        mapping = bbaes(x = Var1, y = Freq, group = Var2)
      )

## Line chart

You can pass to the function `bb_linechart` a vector, in that case x-axis will be the index of that vector :

    billboarder() %>%
      bb_linechart(data = sin(seq(-pi, pi, length.out = 10)))

You can change the type of line with argument `type`, for example an `area-step` :

    billboarder() %>%
      bb_linechart(data = sin(seq(-pi, pi, length.out = 10)), type = "area-step")

If want to specify a variable to map to the x-axis, you had to pass a `data.frame` to the function :

    df <- data.frame(
      var_x = seq(-pi, pi, length.out = 10),
      sin = sin(seq(-pi, pi, length.out = 10))
    )
    df
    #>         var_x           sin
    #> 1  -3.1415927 -1.224606e-16
    #> 2  -2.4434610 -6.427876e-01
    #> 3  -1.7453293 -9.848078e-01
    #> 4  -1.0471976 -8.660254e-01
    #> 5  -0.3490659 -3.420201e-01
    #> 6   0.3490659  3.420201e-01
    #> 7   1.0471976  8.660254e-01
    #> 8   1.7453293  9.848078e-01
    #> 9   2.4434610  6.427876e-01
    #> 10  3.1415927  1.224606e-16

    billboarder() %>%
      bb_linechart(data = df, x = "var_x")

If the first variable of the `data.frame` is a `Date` or a `POSIX`, it will be automatically mapped to the x-axis :

    df <- data.frame(
      date = seq.Date(from = as.Date("2017-06-12"), by = "day", length.out = 10),
      var = rnorm(10)
    )
    df
    #>          date        var
    #> 1  2017-06-12 -1.6579288
    #> 2  2017-06-13  0.9452694
    #> 3  2017-06-14 -0.1357516
    #> 4  2017-06-15 -1.0092445
    #> 5  2017-06-16  1.0758087
    #> 6  2017-06-17  0.7799234
    #> 7  2017-06-18 -0.6844396
    #> 8  2017-06-19  1.6639085
    #> 9  2017-06-20 -1.2049730
    #> 10 2017-06-21 -1.2449921

    billboarder() %>%
      bb_linechart(data = df)

## Scatter plot

For scatter plot, use a two column `data.frame` with function `bb_scatterplot`, or specify the x variable and the y variable (you can also specify a grouping variable) :

    billboarder() %>%
      bb_scatterplot(data = iris[, 1:2])

    billboarder() %>%
      bb_scatterplot(data = iris, x = "Petal.Length", y = "Petal.Width", group = "Species")

## Pie chart

For pie chart, use `bb_piechart` with a two column `data.frame` :

    df <- data.frame(
      var = c("A", "B"),
      count = c(457, 987)
    )

    billboarder() %>%
      bb_piechart(data = df)

## Donut chart

Donut charts works the same as pie charts :

    df <- data.frame(
      var = c("A", "B"),
      count = c(687, 246)
    )

    billboarder() %>%
      bb_donutchart(data = df)

Note : pie and donut are automatically sorted, you can change that with `bb_data(order = NULL)`.

## Gauge chart

Gauge only need one value :

    billboarder() %>%
      bb_gaugechart(value = 64)