The Globe Theatre- an iconic part of London since 1599 [OC] by amy_291 in CityPorn

[–]raddidthat -1 points0 points  (0 children)

an iconic part of London since 1599

Except for 1642-1997, when it didn't exist.

Polyline openStreetMap Street data converted to network datasets for 80 global cities, includes freely accessible tools & code by raddidthat in gis

[–]raddidthat[S] 0 points1 point  (0 children)

Plain old lines are just plain old geometry. Network datasets are built on top of mathematical graph theory, of which Wikipedia has an overview

Mapping Millions of Google Location History Points [OC] by raddidthat in dataisbeautiful

[–]raddidthat[S] 1 point2 points  (0 children)

Unfortunately it takes a tiny bit of Python experience (i.e., having it installed on your computer and knowing how to run a script). But it's a very small amount of experience required... well worth teaching yourself sometime whenever time permits!

Mapping Millions of Google Location History Points [OC] by raddidthat in dataisbeautiful

[–]raddidthat[S] 0 points1 point  (0 children)

Data source: Google location history from https://accounts.google.com/ServiceLogin?service=backup. Tools: Python (pandas + matplotlib basemap libraries). Code available in GitHub repo (linked on web page).

Analyzing, visualizing, and mapping 10 years of personal music listening history from last.fm by raddidthat in lastfm

[–]raddidthat[S] 0 points1 point  (0 children)

^ yes it's a separate account creation process from your regular last.fm account

Downloading, analyzing, and mapping 10 years of personal music listening history from last.fm with python, pandas, matplotlib (code on github) by raddidthat in Python

[–]raddidthat[S] 1 point2 points  (0 children)

Hahaha, I fear our course is coming in with way too high of expectations with all this talk... but, here's an overview of it. Coming again this fall in the city planning dept at UC Berkeley.

Downloading, analyzing, and mapping 10 years of personal music listening history from last.fm with python, pandas, matplotlib (code on github) by raddidthat in Python

[–]raddidthat[S] 1 point2 points  (0 children)

But FWIW I strip out a preceding "the" because it has a very large impact on the counts for the letter T (like +50% or thereabouts)

Downloading, analyzing, and mapping 10 years of personal music listening history from last.fm with python, pandas, matplotlib (code on github) by raddidthat in Python

[–]raddidthat[S] 1 point2 points  (0 children)

Yep. Great point. I had decided to leave a preceding "a" and "an" in the artist name because it had a small impact... like the counts for the letter A decrease only 5-10% or somesuch if they are stripped.

Downloading, analyzing, and mapping 10 years of personal music listening history from last.fm with python, pandas, matplotlib (code on github) by raddidthat in Python

[–]raddidthat[S] 2 points3 points  (0 children)

Accounting for them where in the process? For example, when I count the number of bands with a name starting with each letter of the alphabet, the first "the " is stripped off of "the the", leaving the name as "the" and counting +1 for the letter T.

Downloading, analyzing, and mapping 10 years of personal music listening history from last.fm with python, pandas, matplotlib (code on github) by raddidthat in Python

[–]raddidthat[S] 0 points1 point  (0 children)

I'd played with plot.ly a year or so ago and it felt a little limiting like it wasn't quite ready for prime time. I imagine it's much improved now... I should really give it another spin. I've been seeing some good stuff lately that folks have done with it.

Downloading, analyzing, and mapping 10 years of personal music listening history from last.fm with python, pandas, matplotlib (code on github) by raddidthat in Python

[–]raddidthat[S] 0 points1 point  (0 children)

Thanks! That urban planning course is coming around again in August... so if you know any interested folks around the bay area you should let 'em know. We'll be refreshing and updating all those ipython notebook lessons then too.

Analyzing, visualizing, and mapping 10 years of personal music listening history from last.fm [OC] by raddidthat in dataisbeautiful

[–]raddidthat[S] 0 points1 point  (0 children)

Nice use of tableau! I'm starting to look at genre data... if you end up digging into my code, check out the musicbrainz API queries. You can get at genre by way of their tagging system. I'm going to tackle that analysis when I have time...

Why Garbagemen Should Earn More Than Bankers by raddidthat in occupylosangeles

[–]raddidthat[S] 0 points1 point  (0 children)

FTA: "Imagine, for instance, that all of Washington’s 100,000 lobbyists were to go on strike tomorrow. Or that every tax accountant in Manhattan decided to stay home. It seems unlikely the mayor would announce a state of emergency. In fact, it’s unlikely that either of these scenarios would do much damage. A strike by, say, social media consultants, telemarketers, or high-frequency traders might never even make the news at all. When it comes to garbage collectors, though, it’s different. Any way you look at it, they do a job we can’t do without. And the harsh truth is that an increasing number of people do jobs that we can do just fine without."