TLDR

This article contains my notes from Stanford's CS448B (Data Visualization) course, specifically focusing on the fourth lecture about exploratory data analysis. I'll discuss the importance of exploratory data analysis, the principles behind it, and explore various techniques for visualizing data, including the use of guides, expressiveness, effectiveness, support for comparison and pattern perception, grouping and sorting data, transforming data, reducing cognitive overhead, and consistency. I'll also cover various chart types, such as line charts, bar charts, stacked area charts, and others, providing examples and discussing their design considerations.

TLDR

This article contains my notes from Stanford's CS448B (Data Visualization) course, specifically focusing on the third lecture about visualization designs. I'll discuss the principles of effective data visualization, including the importance of guides, expressiveness, effectiveness, support for comparison and pattern perception, grouping and sorting data, transforming data, reducing cognitive overhead, and consistency. I'll also cover various chart types, such as line charts, bar charts, stacked area charts, and others, providing examples and discussing their design considerations.

TLDR

This article contains my notes from Stanford's CS448B (Data Visualization) course, specifically focusing on the second lecture about data. I'll discuss the different types of data models and how they can be categorized, as well as the distinction between dimensions and measures. I'll also cover data tables and transformations.

TLDR

This article contains my notes from Stanford's CS448B (Data Visualization) course, specifically focusing on the first lecture about the purpose of data visualization. I'll share several historical examples that demonstrate the power and importance of visualization in understanding data, including famous cases like Anscombe's quartet, John Snow's cholera map, and Minard's visualization of Napoleon's Russian campaign. These examples illustrate how visualization can reveal patterns, solve mysteries, and communicate complex information effectively.

TLDR

In this article, I will share my thoughts on the automatic generation of designer materials based on my experience working on a Design Platform project. I'll discuss how we implemented a semi-automated system for creating marketing visuals, the principles behind it, and explore the broader implications for design automation. This approach demonstrates how combining designer-provided frameworks with rule-based generation can create scalable design solutions while maintaining quality standards.