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How Charts Lie - Ch.2

Chapter 2 is my favorite chapter of all chapters from Pro. Cairo’s books I have ever read. It constantly reminds me of what I keep telling myself as I grow up, “This world is complicated. There is no absolutely good nor absolutely bad.” Don’t make your judgment simply by following one rule as what you see may not be the whole story.


In data-driven stories, what makes a story diverse is the data. Data themselves have many features, or as described in the book, nature: the sum, the mean, the median, the distribution, the difference, so on and so forth. Each of them can reveal a unique side of a story. Not to mention thousands of possibilities of their combination and the inner relationships with each other. Also, the same feature of different data can carry different information.


In chapter 2, the author discusses in detail how designers use different encoding methods to achieve different goals in data viz while covering a variety of situations. The prerequisite of doing that is to develop a full understanding of the story that you are about to tell first. Only in this way, can you make sure that your story is not hiding any important details that tell the opposite, neither intentionally or not. “How do you know that you have found the bottom of the truth of a story?” I wrote this question down as I was reading page 56. Luckily, I found the answer soon in the next few pages - conducting thorough research, specifically in terms of data viz, is finding all relevant data. After all, correlation does not equal causation.


So how to choose the most suitable encoding method? The chapter points out that a suitable encoding method must first be reasonable, based on the nature of the data, as well as the goal of the story. As much as the representation of the data may vary, there remains only one truth. And we should not break this one rule.

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