What are the best practices for creating interactive data visualisations?

Some best practices for creating interactive data visualizations include:

1. Define the purpose: Clearly understand the objective of the visualization and what insights you want to convey to the audience.

2. Know your audience: Consider the knowledge level and preferences of your target audience to design a visualization that effectively communicates the data.

3. Keep it simple: Avoid clutter and unnecessary complexity. Use clear and concise labels, titles, and legends to make the visualization easy to understand.

4. Choose the right chart type: Select a chart type that best represents the data and supports the message you want to convey. Consider factors like data type, relationships, and comparisons.

5. Use appropriate colors: Choose a color palette that enhances readability and avoids confusion. Use contrasting colors for different categories or data points to make them easily distinguishable.

6. Provide interactivity: Incorporate interactive elements like tooltips, filters, and drill-down options to allow users to explore the data and gain deeper insights.

7. Ensure responsiveness: Design the visualization to be responsive across different devices and screen sizes, ensuring a seamless user experience.

8. Test and iterate: Continuously test the visualization with different users and gather feedback to identify areas for improvement. Iterate and refine the design based on user insights.

9. Provide context: Include relevant context, such as titles, captions, and annotations, to help users understand the data and its significance.

10. Tell a story: Structure the visualization in a logical flow to guide users through the data and tell a compelling story. Use annotations or animations to highlight key insights or trends.

Remember, these best practices may vary depending on the specific data, audience, and platform you are working with.