data

US births by day data is available here: https://github.com/fivethirtyeight/data/tree/master/births For the period 2000-2014 the number of births by month, divided by the number of days in a month, is: 1 31 5 072 588 163 631.87 2 28 4 725 693 168 774.75 3 31 5 172 961 166 869.71 4 30 4 960 750 165 358.33 5 31 5 195 445 167 595.00 6 30 5 163 360 172 112.00 7 31 5 450 418 175 819.94 8 31 5 540 170 178 715.16 9 30 5 399 592 179 986.40 10 31 5 302 865 171 060.16 11 30 5 008 750 166 958.33 12 31 5 194 432 167 562.32 365 62 187 024 170 375.41 The difference isn't huge but it's significant. There were on average 180k birth in Sept. vs 165k in April and 170k in December. Edit: also,

If we're going off of rarity, December 25 has 6,574 average yearly births and September 9 has almost double at 12,301 average yearly births. Taking a look at Feb 29th, it has 10467 average yearly births (for years that have a Feb 29th). So what is the level of rarity that makes a day not worth calculating? https://github.com/fivethirtyeight/data/blob/master/births/U...

GitLab's UI is in every way a travesty compared to GitHub's. GitLab feels like using GitHub's UI from about 3 years ago. Here's a list of things missing, just to name a few: > consolidated reviews > multiple assigned people > reasonable diffs when merging complicated changes, ability to review code since it was last reviewed > easy to create merge requests, and plenty of context sensitive stuff > can generate comparisons of code online without creating a merge request There's so many small UI/UX pain points Take https://gitlab.com/coldnight/ci-test (which was the trending repo when I visited....): > The navigation is spread across: > The very top > The left hand side > An inline breadcrumbs below that > A bar in the middle of the screen > A bar below that > History button duplicat

A couple of demos: https://fivethirtyeight.datasettes.com/ contains SQLite versions of every CSV published by the FiveThirtyEight crew to https://github.com/fivethirtyeight/data I built a separate tool on top of pandas which can mass-convert CSVs to SQLite - https://github.com/simonw/csvs-to-sqlite - so building the database for https://fivethirtyeight.datasettes.com/ is now a one-liner: csvs-to-sqlite ~/fivethirtyeight/data fivethirtyeight.db https://parlgov.datasettes.com/ uses the SQLite database from http://www.parlgov.org/ - this is a more interesting demo as it includes things like SQL views - e.g. https://parlgov.datasettes.com/parlgov/view_election Both of these demos are served through Cloudflare - since the URL to each database incorporates a sha256 hash of the database contents, I can send a far-future cache expiry header

PSA: FiveThirtyEight are running the problem again [1], and this time have released the data from the previous battle so you can see the soldier distributions that everyone took last time [2]. Submissions are due this Friday. [1]: http://fivethirtyeight.com/features/the-battle-for-riddler-n... [2]: https://github.com/fivethirtyeight/data/tree/master/riddler-...

I've worked as a journalist in which my (and many other data journalists') modus operandi was to publish the data. Often because the data was public record anyway. I now work in academia and the mentality is significantly different. Some of it is logistics -- I would say most traditional news organizations do not have the internal incentive or habit to figure out a way to publish data. Whereas with newer organizations, such as 538 [0] and Buzzfeed News [1], the data teams have editors to whom open-source and digital publishing is more the natural way of things. But in academia, there are also set rules and precautions governing every study. I haven't proposed any research yet but my understanding is that if your study requires collecting data from participants, the Institutional Review Board requires you to be very clear to participants a

The code is on GH [1] and the data is on BigQuery [2]. [1] https://github.com/fivethirtyeight/data/tree/master/subreddi... [2] https://bigquery.cloud.google.com/table/fh-bigquery:reddit_c...

Sadly doesn't seem to be at https://github.com/fivethirtyeight/data

I picked a project at random -- the Tarantino one, which lists every death or curse word in every Tarantino movie -- and browsed through the data: https://github.com/fivethirtyeight/data/blob/master/tarantin... I found it interesting that the author was willing to catalog each curse word by writing it in its entirety -- except one, the n-word (which, by the way, appears 179 times in Tarantino's movies, with the bulk in "Django Unchained" and "Jackie Brown"). The article for which this data set was compiled similarly censors none but the n-word: http://fivethirtyeight.com/features/complete-catalog-curses-... I happen to think that no one of any ethnic group should use the n-word, and I do not use it myself, but I think in the context of cataloging curse words, where you're writing at a sort of meta level (i.e. writing about words, rather

https://github.com/fivethirtyeight/data You're welcome to use their data and come up with your own analyses or just not read what they write. It's not like they're particularly influential, even if they are highly regarded. I'm also semi-interested to know what agenda you're talking about. I read every political article they publish, and I'm actually irritated by how neutral they are.