1. Know your data before you visualize it. Knowing your data allows you to identify errors or inconsistencies within your data.
2. Know your audience. This means not just knowing for whom you are creating a visualization but also why you are creating one.
3. Data visualization can be used to enhance data exploration and analysis rather than just being the final result of a project. Visualizing your data can be an accessible way to present your findings at the conclusion of a research project. However, preliminary visualizations can also help you better understand trends within the data and explore varying hypotheses.
4. Visualizations can lie or be misleading. Visualizations do not always tell the whole story.
We've all heard that a picture is worth a thousand words, but what if we don't understand what we're looking at? Good charts make us smarter--if we know how to read them. However, they can also lead us astray. Charts lie in a variety of ways--displaying incomplete or inaccurate data, suggesting misleading patterns, and concealing uncertainty--or are frequently misunderstood, such as the confusing cone of uncertainty maps shown on TV every hurricane season.
Addressing the prevalent issue of poorly designed quantitative information presentations, this accessible, practical, and comprehensive guide teaches how to properly create tables and graphs for effective and efficient communication.
W.E.B. Du Bois's Data Portraits is the first complete publication of W.E.B. Du Bois's groundbreaking charts, graphs, and maps presented at the 1900 Paris Exposition. Famed sociologist, writer, and Black rights activist W.E.B. Du Bois fundamentally changed the representation of Black Americans with his exhibition of data visualizations at the 1900 Paris Exposition. Beautiful in design and powerful in content, these data portraits make visible a wide spectrum of African American culture, from advances in education to the lingering effects of slavery. They convey a literal and figurative representation of what he famously referred to as "the color line," collected here in full color for the first time. A landmark collection for social history, graphic design, and data science.