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Also: here's how the poverty rate varies across states. Louisiana and Mississippi have poverty rates (20%), and New Hampshire has the lowest poverty rate (6%).pic.twitter.com/4OhrUhY4Gi
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I never really had a quantitative sense of income inequality, so I downloaded some data from the Census Bureau and visualized it. Overall, it seems like “the rich get richer, and the poor g̶e̶t̶ ̶p̶o̶o̶r̶e̶r̶ stay about the same.” More details: https://srcole.github.io/2020/01/26/income-inequality-census/ …pic.twitter.com/qRw4QfDAfP
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Scott Cole proslijedio/la je Tweet
It was a great pleasure to finally get
@thomaschattwill on the podcast:https://samharris.org/podcasts/182-unlearning-race/ …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Joe Rogan is none of those things, as anyone who listens to his interviews would know.https://twitter.com/MoveOn/status/1221125549051011073 …
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Scott Cole proslijedio/la je Tweet
At some point you're going to have to learn that listening to people, even people who are wrong, is a good thing.
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a detailed perspective of how the data science job market is getting oversaturated. Slightly worrying that it was written 1 year ago
https://twitter.com/marcaruel/status/1219270887687573509 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Delete your account.https://twitter.com/mbeisen/status/1219010077203427328 …
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Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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The most common (but unusual) words in the tweets I've liked aren't terribly surprisingly.pic.twitter.com/ndwaGiPH1w
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Was curious whose tweets I've liked most.
@nickwan is apparently my fav. Also@neuromusic and@_rdgao. And surprisingly few non-neuroscientists (*). (~3500 total likes) (personal data from@Twitter, Account>Your Twitter Data, and then merged with their API)pic.twitter.com/YxUEOd5EuX
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Scott Cole proslijedio/la je Tweet
Looks like MATLAB has acknowledged Python as a competitor in the scientific analysis ecosystem. https://www.mathworks.com/products/matlab/matlab-vs-python.html …
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I mean. Yeah. I can use 'hls'. But I've been using A LOT of hls.
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ouch. I felt
@michaelwaskom and the rest of the data viz community judging me. I just wanted a variety of colors for my lines...pic.twitter.com/sbhJ8PZNQd
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Scott Cole proslijedio/la je Tweet
NEW VIDEO: Tiny Bombs in your Blood - The Complement Systemhttps://youtu.be/BSypUV6QUNw
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Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Also cool to see how the truth ratings varied by state. Each red/blue dot here is a politician who had at least 5 facts checked. While the grey dot/bar represents the average for that state. Congratulations to Oregon!pic.twitter.com/wLrJQVM8cq
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Fun to look at how the statements break up by each truth score.
@HillaryClinton had, on average, the most accurate statements across politicians with at least 100 fact checks. And@BernieSanders didn't appear to have any that were "Pants on Fire"pic.twitter.com/9IVx7Y8B5s
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Here we see the top 10 and bottom 10 politicians, ranked by truthfulness.
@BetoORourke is the only primary candidate I've heard of to break the top 10, while@realDonaldTrump is unsurprisingly close to the bottom.pic.twitter.com/UdcwA60okR
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While the accuracy of statements by Republicans appear to have decreased over the past decade, those by Democrats have stayed relatively stable.pic.twitter.com/Dg843eS5kT
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I scraped >16,000 fact checks from
@PolitiFact to see some trends in the truthfulness of political statements over the past decade. Post: https://srcole.github.io/2019/07/20/politifact/ … Code: https://github.com/srcole/politifact-analysis … Here we see there was a large relative increase in "Pants on Fire" statements in 2017.pic.twitter.com/ZOcjuKe3hN
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