
Show HN: Data Driven Tech Radar - mrmrcoleman
http://datadriventechradar.com/
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robbiemitchell
I was about to say that I would love to see this for NYC, and now I see the
"coming soon" button. Boston would also be interesting.

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mrmrcoleman
Hey, one of the creators here. NYC is definitely on the list, keep an eye on
Twitter. Hadn't considered Boston, but we will now.

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garysieling
Philadelphia would be nice too!

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mrmrcoleman
Added it to the list!

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div3rs3
Great work! Mashing up data based on tweets, HN posts and real-world projects
(i.e. from GitHub) would be an interesting dimension.

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frisovv
Yeah, I have some ideas about including different data sources. You have to
start somewhere, though, and Meetup.com has a nice real-life aspect to it. My
best guess would be that Github and HN would add most interesting data from a
technology / community popularity and natural language perspective
respectively.

Question is: how do you connect a Github repo or a HN post to a specific
community? Content based? User based? Topic based? The community detection in
the real life Meetup.com network is at the very basis of this and for good
reasons, so you'd have to find a way to tie other data to that idea.

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fzsix
Very nice! Despite the super bootstrapped layout, the data itself is really
great. And as a result of your work, I'm now seriously considering Amsterdam,
haha.

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frisovv
Horrible shameless plug from the creator here:
[http://www.godatadriven.com/careers](http://www.godatadriven.com/careers)

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mrmrcoleman
Horrible indeed! :-)

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lguminski
nice graphs. What tools did you use to generate them? I'm curious.

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kgreene2
The graphs looks like they were all created with C3

[http://c3js.org/](http://c3js.org/)

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frisovv
The line and bar charts are c3js indeed, which wraps d3. The mind map graph is
done using cytoscape.js.

Data gathering, preparation, initial exploratory analysis and pretty much
everything else is done with a combination of Jupyter notebooks, some Python
scripting, and a set of Jinja2 templates for the HTML and the city specific
JS. The JSON which is loaded to populate the charts is also generated from the
same Python scripts. The code base is not necessarily something to be proud
of, but it works. We focused on analysis (hence, the default bootstrap theme
and nothing fancy).

We're likely to do a making of talk at one or two meetups here in Amsterdam.
Hopefully those will be recorded. There's some additional interesting aspects
to the collected data not immediately visible in this presentation.

Disclaimer: I did most of the data wrangling and coding on this; also I'm CTO
for GoDataDriven, one of the two companies mentioned as producer.

