by sharpercoder on 3/3/2019, 10:07:06 AM
by altairiumblue on 3/3/2019, 9:26:56 AM
Jake is a great teacher - I would definitely recommend his book to people new to Python for data science, as well as any talk by him that you can find on youtube.
Also, it's kind of a shame that matplotlib is still so deeply ingrained in the Python data ecosystem.
by __blockcipher__ on 3/4/2019, 3:09:30 AM
Am I the only one who kind of hates the "notebook" format?
Don't get me wrong, the general concept is great. Shareable, interactive code snippets are awesome. But for a demo article like this I want a single python file that I can run and immediately see the results. I don't want to have to spin up a jupyter or pylab instance (I've never used pylab so not sure if it works the same EDIT: pylab is analogous to matplotlib, not jupyter. lesson learned). I just want to run the damn code.
On a bit of a tangent here but I also hate the way Jupyter makes git diffs absolutely unusable.
Now, the above being said, the fact that sites like Github have native Jupyter functionality is awesome. It'd be a lot less painful if they'd (the author) have linked to a repo that we (I) could run.
--
For example, first I copied the initial code snippet that defines the xkcdify function. Then I ran it with python3, and realized it needed python 2 due to the urllib2 dependency (this is not a big deal since the article is from 2012). Then I ran it again with python2, and realized I don't have numpy/scipy etc installed for python2, so I pip installed those. Then I copied in the following code snippet that generates the plot. I then ran it again, and it still didn't work. Finally after a brief google search, I realized I needed to put pylab.show() at the end since I didn't have the %pylab inline or whatever that command is since I'm running it with "pure python".
Honestly, it really wasn't _that_ much effort, but I vastly would prefer to have a demo like this given as a single python file, with the dependencies clearly specified in the blog post.
by jen729w on 3/3/2019, 8:13:19 PM
I’ve always had a problem designing diagrams in Visio. (I work in IT so think high level network diagrams, flowcharts describing state/processes, that sort of thing.)
Last year I found the template that makes everything look hand-drawn. It changed the way my brain saw the diagram, going from “this thing must be absolutely pixel perfect” to “this is something I literally sketched on the back of a napkin”.
This allowed my brain to create the thing, without worrying about whether everything was lined up just so. Then, at the end, I can choose to flip the theme back to straight edges, and line everything up if I choose.
Actually, many times I just left it as it was. Others seemed to like the hand-drawn look, which came as a surprise.
by emgee_1 on 3/3/2019, 9:15:29 AM
Interesting. Is something like this available in R?
In a same vain: when producing content using latex ( in the eighties ) I had a problem that papers under construction looked way to good ( lie as if was printed) ; in order to counter the good looks of the printed paper I choose to use a typewriter like blurred ink dropped font to ensure that what was printed was a draft and still under construction; producing graphs that show intent but not precision is very useful.
by wodenokoto on 3/3/2019, 9:37:56 AM
Is there a bootstrap or css theme to go along, so my PoC web-app can match the style of my proof of concept graphs?
by stared on 3/3/2019, 11:26:49 AM
(2012), infuential but archaic.
Now it is built-in matplotlib: https://matplotlib.org/api/_as_gen/matplotlib.pyplot.xkcd.ht...
by vntok on 3/3/2019, 12:21:48 PM
yUML.me is awesome for hand-drawn DB schemas or to show a website's graph of interlinked pages:
by loser777 on 3/3/2019, 9:47:25 AM
it would be cool if Randall stopped drawing plots by hand and just started using this ;)
by panda88888 on 3/4/2019, 8:39:17 PM
Follow up in 2013. XKCD officially merged in Matplotlib.
http://jakevdp.github.io/blog/2013/07/10/XKCD-plots-in-matpl...
by masukomi on 3/3/2019, 9:06:05 PM
it should be noted that the code to do this is actually part of matplotlib now. The author comments about it here http://jakevdp.github.io/blog/2013/07/10/XKCD-plots-in-matpl... and refers to the code in the post here as "my ugly little hack."
by pfd1986 on 3/3/2019, 8:12:14 AM
Needs 2013 tag. Still fun tho.
From a usability perspective, "sketchy" or "cartoony" charts actually serve a purpose. To me, they communicate "the trend is important here, not the precise numbers". This can more acurately convey communication intent as opposed to a precise rendered graph.