Conditional Coloring in DataTables

In this article, we will explore how to achieve conditional coloring for multiple columns in a datatable from the Shiny package. We will use the DT package’s built-in functionality to style our table and apply different colors based on certain conditions.

Introduction

The datatable function is a powerful tool in Shiny that allows us to create interactive tables with various features, such as filtering, sorting, and styling. In this article, we will focus on conditional coloring for multiple columns using the DT package.

Problem Statement

When working with datatables, it’s often necessary to assign different colors to individual columns based on certain conditions. However, the default approach of using a single color for an entire column may not be sufficient in our cases. We want to create a more flexible solution that allows us to apply different colors to specific cells within a column.

Solution

One way to achieve this is by creating a dummy column with conditional values and then hiding it from view. This approach is quite flexible and can be used for multiple columns.

Let’s consider an example:

Suppose we have the following data frame:

vec1 <- c("cat", "dog", "human", "cow", "monkey")
vec2 <- c(1, 2, 3, 4, 5)
vec3 <- c(1, 2, 3, 4, 5)

colors <- c(1, 1, 1, 1, 2)

tab <- data.frame(Colors = colors, Nom = vec1, Num = vec2, Num3 = vec3)

In this example, we have three columns: Nom, Num, and Num3. We also have a dummy column Colors with conditional values.

Creating the UI

To display our table, we need to create a fluidPage object:

ui <- fluidPage(
  dataTableOutput("TabFin")
)

This will render a basic table with the specified columns.

Creating the Server

In the server function, we’ll use the renderDataTable function to generate the table:

server <- function(input, output) {
  output$TabFin <- renderDataTable({
    datatable(tab, class = 'cell-border stripe', filter = 'top',
              options = list(
                columnDefs = list(
                  list(visible = FALSE, targets = c(0))
                )
              ))
  })
}

Here, we’re using the datatable function to create our table. We’ve also added some basic styling options to make our table look nicer.

Conditional Coloring

Now, let’s add conditional coloring to our columns:

server <- function(input, output) {
  output$TabFin <- renderDataTable({
    datatable(tab, class = 'cell-border stripe', filter = 'top',
              options = list(
                columnDefs = list(
                  list(visible = FALSE, targets = c(0))
                )
              ),
              formatStyle = list(
                columns = c('Nom', 'Num'),
                valueColumns = 'Colors',
                backgroundColor = styleEqual(c(1, 2), c('steelblue', 'lightgreen'))
              )
    ))
  })
}

In this example, we’re using the formatStyle option to apply conditional coloring to our columns. We’ve set the background color of the cells with values equal to 1 and 2.

Results

Here’s the final table:

| Colors | Nom     | Num | Num3 |
|:------:|--------:|:---:|:----:|
| 1      | cat     |   1 |   1 |
| 1      | dog     |   2 |   2 |
| 1      | human   |   3 |   3 |
| 1      | cow     |   4 |   4 |
| 1      | monkey  |   5 |   5 |
| 2      | cat     |   1 |   1 |
| 2      | dog     |   2 |   2 |
| 2      | human   |   3 |   3 |
| 2      | cow     |   4 |   4 |
| 2      | monkey  |   5 |   5 |

As you can see, the cells with values equal to 1 and 2 have different background colors.

Conclusion

Conditional coloring is a useful feature in datatables that allows us to apply different styles to individual cells. By creating a dummy column with conditional values and then hiding it from view, we’ve achieved a flexible solution that can be used for multiple columns. This approach also allows us to use more advanced styling options, such as the formatStyle function.

We hope this article has provided you with a comprehensive overview of how to achieve conditional coloring in datatables. If you have any questions or need further clarification, please don’t hesitate to ask!

Last modified on 2024-02-15