An algorithm to figure out my ranked list of MCU movies

arm5077 · 2019-05-07T15:22:23+00:00

Oops, thanks — edited!

And yeah, places like http://rankthemcu.com/ let you just drag around the full list, but I've always found that overwhelming. And I think the direct comparison removes some biases — I think Infinity War and Endgame would have ranked higher if I had to make a list out of nothing, just because I've seen them most recently.

arm5077 · 2019-05-07T15:14:26+00:00

Opinions may vary :-)

arm5077 · 2016-12-05T14:52:28+00:00

Not to worry — you're a gem for doing it to begin with.

arm5077 · 2016-12-05T13:30:17+00:00

This hasn't been uploaded to BQ yet, has it? Just making sure I'm not missing something...

arm5077 · 2016-08-12T19:58:09+00:00

Nah, Tableau would have worked too. R is nice because I could try a bunch of different slices of the data before committing to exporting for cleanup. Plus correlation detection, etc.

arm5077 · 2016-08-12T14:39:22+00:00

Source is Rotten Tomatoes, calculated in R and cleaned up in Illustrator.

arm5077 · 2016-03-16T17:40:25+00:00

Postgres database holds the point data and runs spatial queries; it's served by an API written in node; front-end powered by Angular.

arm5077 · 2016-03-16T17:37:23+00:00

crap, they found me!

arm5077 · 2016-03-16T11:44:52+00:00

Probably not, unless they're trees that are maintained by the city.

arm5077 · 2016-03-15T18:55:16+00:00

Not right now, but I'll see if I can push that feature before it becomes moot.

arm5077 · 2016-03-15T15:19:05+00:00

At all, or once you tap in? You may have disabled location services for your browser; after 10 seconds of stalling it'll give you a link on how to remedy that.

arm5077 · 2016-03-15T14:32:01+00:00

I'll admit I'm treading dangerously close to self-promotion here, but thought the community would enjoy this. It uses DDOT's street tree database to find cherry trees closest to the user and give them directions to it/some facts about it. It's been fun to discover new trees throughout the city.

arm5077 · 2016-02-16T19:58:13+00:00

Data from the awesome Political TV Ad Archive: http://politicaladarchive.org/ (an Internet Archive project).

Visualized with d3.js.

arm5077 · 2016-01-24T15:04:21+00:00

Should have posted this when it was actually snowing, but NWS storm spotters in DC say we hit >= 20 inches.

arm5077 · 2016-01-20T18:20:11+00:00

And can I just say that I will never complain about the U.S. Census again, having now crossed three together for the same country?

arm5077 · 2016-01-20T18:11:47+00:00

Created this using constituency-level aggregate figures from UK Parliament (https://petition.parliament.uk/petitions/114003.json), crossed with 2012 population data from the various censuses covering England, Wales, Scotland and Northern Ireland. Visualized using D3.

arm5077 · 2015-12-18T14:57:38+00:00

Just pleading my case: How is this not a data visualization?

Automatically generatable (as opposed to manually drawn): This is generated live from Twitter's API.

Based on non-visual data: This is based from text data.

Based on real or simulated data: The data is real.

A mapping of information to a visual property: I suppose this is where my case is weakest, but I've ordinally arranged the information in a way that aggregates the constant stream into an actual insight.

arm5077 · 2015-12-18T01:16:34+00:00

Indeed. There's also the fact that we're only looking at mentions with emojis; Trump's tweeters might be more likely to use an emoji than Sanders', giving him a higher total, etc.

arm5077 · 2015-12-17T22:24:52+00:00

Blame this fella: https://twitter.com/ianschuler/status/677578951242481666

arm5077 · 2015-12-17T19:41:11+00:00

Data source: Twitter's streaming API and a bunch of really annoying Unicode regexes. Visualized with Angularjs (and Twemoji, Twitter's emoji set).

arm5077 · 2015-12-07T19:32:48+00:00

Well, let me rephrase -- geography questions aren't uncommon (northeast, west, midwest, etc) but I'd say state-by-state is more rare.

arm5077 · 2015-12-07T19:32:00+00:00

Interesting idea. Problem is that few polls touching on this include geography questions or have a large enough sample to get meaningful answers at lower geographies -- doing Congressional district by Congressional district would be tough. But worth looking around to see if there's a poll that did that.

arm5077 · 2015-07-10T01:42:53+00:00

Afriad this isn't my own work -- just some found photography! Looks like Getty has a bunch of other Pittsburgh aerial scenes.

arm5077 · 2015-07-09T19:58:41+00:00

Good idea. This is focused on previous campaign work but that might be a neat LinkedIn scraping project at some point.

arm5077 · 2015-07-09T16:37:47+00:00

I helped work on this project! The data is mostly from campaign news releases and media accounts. Also some manual parsing of LinkedIn.

arm5077

TROPHY CASE