Mapping Happiness and Isoline Functions

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Most of the time I get emails they’re either work-related or spam-related.  Sometimes the spam turns out to be interesting.  About once a month I’ll get a digest of articles from Teleport .  This month there was an article from Forbes about mapping global happiness using news headlines.  I’m assuming the author used natural language processing of some sort, as he mentions evaluating the context in which each location is written about ( sentiment analysis).

Not entirely sure how accurate the methodology is (and the final product is somewhat hard to draw conclusions from), but it’s a super cool concept nonetheless.  Unfortunately, the author did not leave us with a GitHub repo to pore through, but did mention making use of Google’s BigQuery platform and Carto’s mapping system.

Being the fantastic procrastinator that I am, I took a look at Carto’s services.  Turns out they have a pretty cool feature (with an API) that creates time and distance isolines.  Might try using something like that in an upcoming project.  Stay tuned!  Or check out my GitHub for a sneak peek.

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R Weekly

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During my Monday morning ritual of avoiding work,  I found this publication that is written in R, for people who use R – R Weekly.  The authors do a pretty awesome job of aggregating useful, entertaining, and informative content about what’s happening surrounding our favorite programming language.  Check it out, give the authors some love on GitHub, and leave a like if you find something useful there.

Have a good week,

Kiefer Smith

What is the real unemployment rate? Or, how cherry-picking data is dishonest.

This video by the vlogbrothers does a great job at breaking down what the unemployment rate in America really means, but also exemplifies how reporting data improperly can cause issues.  There are six main ways(probably more) to measure unemployment!  Mixing measurement types or presenting one out of context can distort what is happening in reality.

Keep those critical thinking skills sharp, folks.  We’re gonna need them.

– Kiefer

Initial Node

Stories are an integral part of the human experience.  They don’t have to be true, but there is something that about seeing “based on a true story” that grabs our attention.  Fiction is entertaining and can be instructive, but a true story we can really connect with.  A true story takes place in our universe – a place where we know the rules.

Finding truth has become increasingly difficult, a problem that became well-known during the 2016 election season.  My goal with this blog (and in life) is to tell interesting stories that are based in fact, based on data.  While no science is infallible, I feel that a story based on numbers is as close to “based on a true story” as we can get.

I mainly use R for data processing and analysis, but I’m slowly learning Python.  These will be my tools for telling stories.  If you have a burning question or find some interesting data, I’d be happy to dig into it.  As this blog progresses I hope to improve my data science skills and hopefully get better at writing blog posts.

– Kiefer