Data Visualization: Principles and Practices

This lecture covers the basic techniques and practical skills required for data analysis, emphasizing the importance of data visualization in finding relationships, discovering structure, and quantifying values. It explores static and interactive visualization, chart selection, histograms, box plots, scatter plots, line plots, and stacked plots. The instructor discusses the significance of perception of magnitudes, dimensionality reduction, and the use of color, axes, and data ink wisely. Various use cases for data visualization are presented, including data wrangling, multimodal data, and handling weird data. The lecture also highlights the importance of maintaining a theory of data appearance and showcases examples from journalism and interactive storytelling.