# Mapping - map variables to the chart

#### Victor Perrier

#### 2024-09-09

## Introduction

There’s 3 ways with `billboarder` to pass data to construct a chart :

- Use a `data.frame` with only variable that need to be used, typically for a barchart, the first column is used for x-axis, the second for y-axis.
- Pass your data to `billboarder` and use function `bb_aes` in a “pipe” flow.
- Use function `bbaes` inside chart builder helper such as `bb_barchart`, `bb_linechart`, …

## Data

We’ll use data about the french electricity production between 2012 and 2016 :

    data("prod_par_filiere")
    str(prod_par_filiere)
    #> 'data.frame':    5 obs. of  11 variables:
    #>  $ annee             : chr  "2012" "2013" "2014" "2015" ...
    #>  $ prod_total        : num  542 550 540 547 531
    #>  $ prod_therm        : num  48.1 43.6 25.9 34.4 45.9
    #>  $ prod_hydraulique  : num  63.8 75.5 68.1 59.1 63.9
    #>  $ prod_bioenergies  : num  5.8 7.1 7.5 8 8.5
    #>  $ prod_eolien       : num  14.9 15.9 17.1 21.1 20.7
    #>  $ prod_therm_charbon: num  17.4 19.9 8.4 8.6 7.3
    #>  $ prod_solaire      : num  4.1 4.7 5.9 7.4 8.3
    #>  $ prod_therm_gaz    : num  24 19.9 14.3 21.9 35.3
    #>  $ prod_nucleaire    : num  405 404 416 417 384
    #>  $ prod_therm_fioul  : num  6.7 3.8 3.3 3.8 3.3

## First method : use a `data.frame`

For creating this simple barchart, we need to use two columns of our `data.frame`

    billboarder() %>%
      bb_barchart(data = prod_par_filiere[, c("annee", "prod_bioenergies")])

Variable `annee` is used on the x-axis, and `prod_bioenergies` as y values.

This is similar for line chart :

    billboarder() %>%
      bb_linechart(data = prod_par_filiere[, c("annee", "prod_bioenergies")])

## Second method : with mapping

We can pass our data to function `billboarder` and then call `bb_aes` to specify which variable to use :

    billboarder(data = prod_par_filiere) %>%
      bb_aes(x = annee, y = prod_bioenergies) %>%
      bb_barchart()

You don’t have to pass arguments to `bb_barchart`.

This is the same for line chart :

    billboarder(data = prod_par_filiere) %>%
      bb_aes(x = annee, y = prod_bioenergies) %>%
      bb_linechart()

## Third method : mapping inside function

Mapping can be specified inside the function which specify the type of chart :

    billboarder(data = prod_par_filiere) %>%
      bb_barchart(mapping = bbaes(x = annee, y = prod_bioenergies))

The function to map variables is `bbaes` without underscore.

For line chart :

    billboarder(data = prod_par_filiere) %>%
      bb_linechart(mapping = bbaes(x = annee, y = prod_bioenergies))

## Grouping variable

Construct a chart with groups differ between the first method and the others. For the first one, data need to be in ‘wide’ format, the other need data in ‘long’ format with a grouping variable.

With ‘wide’ data :

    billboarder() %>%
      bb_barchart(
        data = prod_par_filiere[, c("annee", "prod_bioenergies", "prod_eolien", "prod_solaire", "prod_hydraulique")]
      )

with ‘long’ data :

    # prepare data
    data("prod_filiere_long")
    prod_filiere_long <- prod_filiere_long[
      prod_filiere_long$branche %in% c("bioenergies", "eolien", "solaire", "hydraulique"),
    ]
    head(prod_filiere_long)
    #>    annee     branche prod
    #> 11  2012 hydraulique 63.8
    #> 12  2013 hydraulique 75.5
    #> 13  2014 hydraulique 68.1
    #> 14  2015 hydraulique 59.1
    #> 15  2016 hydraulique 63.9
    #> 16  2012 bioenergies  5.8

    billboarder(data = prod_filiere_long) %>%
      bb_barchart(mapping = bbaes(x = annee, y = prod, group = branche))

## Mapping with programming

In Shiny app or in function, you can use `bbaes_string` or `bb_aes_string`, these function accept character instead of unquoted variable names :

    billboarder(data = prod_filiere_long) %>%
      bb_barchart(mapping = bbaes_string(x = "annee", y = "prod", group = "branche"))