How do you use animation and interactivity to enhance your charts and data stories?

1 Why animate charts?

Animation is the process of creating the illusion of movement by changing the appearance of an object over time. In data visualization, animation can help you show changes, trends, and patterns in your data, as well as highlight important points and comparisons. Animation can also make your charts more attractive and memorable, and draw attention to your message. However, animation should not be used for its own sake, but rather to support and enhance your data story.

2 How to animate charts?

When creating data visualizations, there are various ways to animate charts depending on the type and purpose of the data. Transition is when you alter the state or position of an element, like a bar, a line, or a point. This could be used to illustrate how a value changes over time or how rankings vary between categories. Morph is when you modify the shape or form of an element, such as a pie, a map, or a network. This could be used to demonstrate how a distribution shifts between segments or how a structure develops under different scenarios. Lastly, reveal is when you display or conceal an element, such as a label, legend, or detail. This can be employed to show extra information on demand or to emphasize a particular aspect of the data.

3 What tools to use?

Creating animated charts can be done with a variety of tools and platforms, depending on your level of skill and preference. For example, PowerPoint is a popular and user-friendly software that lets you add basic animation effects to your charts. Google Charts is a web-based service that offers interactive features and dynamic charts that respond to user input. If you need more advanced animation effects, D3.js is a JavaScript library that allows you to create custom and complex charts with animation capabilities. D3.js gives you control over the speed, duration, and easing of your animation.

4 How to design interactivity?

Interactivity is the process of enabling users to interact with your chart, such as by clicking, hovering, dragging, or zooming. In data visualization, interactivity can help you provide more options, details, and perspectives for your data, as well as engage and empower your users. Interactivity can also make your charts more adaptable and responsive, and allow users to explore and discover your data at their own pace. However, interactivity should not be used to confuse or overwhelm your users, but rather to guide and support your data story.

5 How to design interactivity?

Designing interactivity for data visualization can vary depending on the type and purpose. Filter is a popular method that allows users to select or deselect a subset of the data, such as a category, range, or condition. This enables them to compare different groups, regions, or periods. Drill-down allows users to access more detailed information about the data, such as a subcategory, breakdown, or case study. Highlight allows users to emphasize or focus on a specific element or aspect of the data, such as a value, trend, or relationship. This can help them identify outliers, anomalies, or correlations in the data.

6 Best practices for animation and interactivity

Animation and interactivity can enhance your charts and data stories, but they can also be used improperly and distract or mislead users. To ensure your charts are effective and meaningful, use animation and interactivity to support your data story, not to replace it. Use them sparingly and selectively, only when they add value or meaning to your data. Additionally, make sure animation and interactivity are consistent and intuitive for users, with familiar cues and conventions. Provide feedback and instructions for users as well to ensure the best experience.