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Brunch so hard

Non-Mathematical Feature Engineering Techniques for Data Science
This article is worth Pocketing for the straightforward, plain-English explanation of feature engineering alone. (And the best practices for pre-processing data ain’t bad either.) - Sachin Joglekar

Is it brunch time?
One man’s quest to discover “the exact time of day in which brunch maximally occurs” using Twitter data. Bonus for you Python users out there: this analysis includes some beautiful charts made with pandas and matplotlib. - The Startup

Why we didn’t use a cartogram in the Brexit map
After Brexit, tons of publications released maps of how the U.K. voted. Graphics editor Gregor Aisch shares why The New York Times opted for a simple map—and the challenges of using cartograms in the news. - Gregor Aisch

Visualising Data: A Handbook for Data Driven Design
Data viz thought leader Andy Kirk recently released his first book. He put together a companion site full of resources and references that are useful whether you buy the book or not. - Visualising Data

If Correlation Doesn’t Imply Causation, Then What Does?
This tweet from @DannyPage sums up our feelings on this article exactly: “Love that it gives a framework for thinking about correlations that isn’t just ¯\_(ツ)_/¯”
- Adam Kelleher

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The more you surround yourself with the work of others, the more you learn. Data viz practitioners: here are 11 experts to follow for constant inspiration.