When choosing chart types in a data visualization GUI, follow these best practices:

1. Know your data: Understand the data type, distribution, and relationships to select the most suitable chart.

2. Define the message: Determine the key insight or message you want to convey.

3. Consider user goals: Choose charts that support the user's goals and tasks.

4. Keep it simple: Select simple and familiar chart types, avoiding unnecessary complexity.

5. Avoid 3D charts: Unless necessary, use 2D charts for clarity and ease of understanding.

6. Use bar charts for categorical data: Bar charts effectively compare categorical data.

7. Use line charts for time series data: Line charts show trends and patterns in time series data.

8. Use scatter plots for relationships: Scatter plots illustrate relationships between two continuous variables.

9. Use pie charts sparingly: Pie charts are suitable for showing proportional data, but can be misleading if not used carefully.

10. Consider interactive elements: Incorporate interactive features like hover effects, tooltips, and filtering.

11. Be consistent: Establish a consistent design language throughout the GUI.

12. Test and refine: Validate chart choices through user testing and refine as needed.

Additionally, consider the following:

- Use color effectively to differentiate data series

- Label axes and provide clear titles

- Avoid clutter and ensure sufficient whitespace

- Use chart legends and filters judiciously

- Ensure accessibility and responsiveness

By following these best practices, you can choose the most effective chart types for your data visualization GUI, enabling users to gain valuable insights and make informed decisions.