Here, Kris Harbold explores the Bitly Real-Time Media Map, an interactive data visualization that illustrates media consumption across the United States. By using the tools of data science to analyze the source and format of media links being shared, this map attempts to pinpoint correlations between the political affiliation of readers and the news they consume.
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If you’re at all interested in economics, data science, or even just popular books, it’s a good bet that you’ve heard of the 2005 New York Times bestseller, Freakonomics: A Rogue Economist Explores the Hidden Side of Everything. Eight years might seem to be a long shelf life for a book about statistics, particularly one dealing with current events, but as one of the first books to push economics and data science into popular consciousness, we think it’s definitely worth taking a second look.
David McCandless, author of the popular Information is Beautiful blog, uses his 2010 TED Talk to describe how combining the language of the eye with the language of the mind enhances our understanding of complex data. He believes that the Web has turned us all into visualizers for whom processing graphic information is effortless.
“Big data” — we hear the term all of the time, but what does it really mean? Viktor Mayer-Schönberger and Kenneth Cukier’s 2013 bestseller, “Big Data: A Revolution That Will Transform How We Live, Work, and Think,” attempts to answer this question with a solid overview of the promises, advancements, issues and implications of the big data revolution.
From sifting through Twitter data to making your own Minecraft modifications, Python is one of the most versatile programming languages at a coder’s disposal. The open-source, object-oriented language is also quickly becoming one of the most-used languages in data science. According to the Association for Computing Machinery, Python is now the most popular introductory language at universities in the United States. To help readers practice the Python fundamentals, datascience@berkeley gathered six coding problems, including some from the W200: Introduction to Data Science Programming course. The questions below cover concepts ranging from basic data types to object-oriented programming using classes. Are […]