7.1. Data Visualization Best Practices

In previous lessons, we've explored the importance of data aggregation, numerical analysis, and the categorization of data. We've covered techniques to process, clean, and reshape data into various groupings, such as channel groups, and have employed regular expressions to refine text. So far, our results have been presented in tables, but we haven't yet delved into the world of data visualization.

This week, we will shift our focus to visualizing data. Our goal is to effectively communicate insights and tell stories with data, empowering people to find answers in the information we've prepared for them.

This lesson will be divided into two parts: the first focusing on best practices, and the second on "styling like a pro."

In this first part, we will explore the principles of data visualization, while in the second part, we will learn how to apply these principles in practice.

Today's lesson will cover:

1. Storytelling: Harnessing the power of data visualization to convey meaningful stories.
2. Chart Selection: Choosing the right chart type to communicate your message effectively.
3. Contextualization: Enhancing your charts with reference lines and other contextual elements.
4. Conditional Formatting: Communicating data status by applying visual cues based on specific conditions.
5. Color Consistency: Using colors purposefully and consistently to improve comprehension.
6. Distraction Avoidance: Removing unnecessary clutter to increase the value and impact of your visualizations.

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