Displayr allows many different options to customize your visualizations, including customizing the colors shown. You can update the colors of items in the visualization, ranging from your font colors to the colors of the bars, lines, columns, etc.
This article outlines the different options you have when customizing the colors used in your visualizations.
- Visualization Templates
- Default Colors for Tables and Visualizations
- R-based Visualization Templates
- Set the Color for a Single Category/Brand
- Assign Different Colors in a Small Multiples Funnel Visualization
- Apply a Gradient Palette
- Apply Conditional Formatting
Requirements
- A data source in a Displayr document
- Additional requirements, if present, are detailed in their respective section below.
Visualization Templates
Displayr makes it easy to set up templates for your visualizations. These templates can then be applied to visualizations across your report so that you can set up everything to match your desired look and feel, including brand colors, font colors, labels, etc. This is especially helpful when you have many pages with the same layout and chart type, and want them to all be formatted the same, or if you need to make changes to the Chart tab settings across many of the same visualization types. See How to Create and Apply a Visualization Template for more details and instructions.
Default Colors for Tables and Visualizations
If you want to set the default colors for your table styles and visualizations across your project, follow the steps in How to Set the Default Colors for Tables and Visualizations. Note that this method doesn't allow customization beyond the colors used in visualizations. If you need to customize colors, as well as font style, data labels, axis formatting, etc., use the method described in the Visualization Templates section.
R-based Visualization Templates
When you want to create a template for fonts, including number fonts, and colors, you should use an R Visualization Template. You can specify appearance settings (such as color palettes and font settings), and apply these settings to any visualization you hook up to the template. This can be useful if you want to assign specific colors to specific brands in your visualizations. For example, any data points for Coca-Cola in the visualization would be colored red. Note that this method requires you to use an R-based visualization, i.e., visualizations that do not have "with Tests" in the name or aren't number visualizations.
Set the Color for a Single Category/Brand
If you have a bar, column, or funnel (pyramid) visualization, you can set a specific color for a single category or brand. See How to Customize the Color of a Single Category in a Bar, Column, or Funnel Visualization. Note, this setting is static, so if your visualization is filtered or dynamically sorted, the assigned color will always remain in the same spot, regardless of brand/category. For example, if you set the third category as red and the data updates, the third category, regardless of whether it is the same as the original category, will be assigned in red. If you need to assign colors to a dynamic visualization, use the named colors option described in How to Create an R Visualization Template.
Assign Different Colors in a Small Multiples Funnel Visualization
When creating a brand funnel visualization, you might want to assign different colors to each funnel so that your brand is one color and your competitor brands are a different color. See How to Make Each Funnel in a Small Multiple Funnel Visualization One Color.
Apply a Gradient Palette
If you have a bar, column, or funnel (pyramid) visualization, you can apply a gradient palette. Note that this customization is only available for non-legacy (without "with Tests" in the name) bar, column, and funnel visualizations. See How to Apply a Gradient Palette to a Bar, Column, or Funnel Visualization for details.
Apply Conditional Formatting
You can apply conditional formatting to visualizations using custom R code, which allows you to specify the colors and conditions. For example, you might want to apply one color to all series with values greater than 50%, and another color to series with values of less than 25%. Since this utilizes R code, you can customize things as much or as little as you'd like. See How to Set Conditional Formatting for Visualizations for the requirements and an example of the custom code.
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Frequently Asked Questions About Creating and Modifying Visualizations