Re:Agate: A Data Analysis Library for Journalists
by staringmonkey on Wednesday October 28, 2015 @10:27AM
(#10464618)
Hello! Author of the library here. Just want to point out that I am a journalist and very active in the data journalism community. (6+ years) Both the sites you name-check have journalists who do production online graphics that don't go through the traditional Illustrator workflow and news organizations are increasingly discarding that antiquated pattern. (I've made a hundred graphics for NPR and I don't even have a copy of Illustrator installed.)
To your second point, that's fine. The most common feedback I've gotten is "I don't see what purpose this serves that X doesn't already fulfill!" Well okay then, you don't gotta use it. But given the fact I've done this job for years, working with the very folks who it's targeted at, I think it's probably safe to assume I've got some reasons. (Which you will find enumerated in the blog post and documentation.)
Re:Agate: A Data Analysis Library for Journalists
by JPKab on Wednesday October 28, 2015 @11:26AM
(#10464949)
hey man, good work on agate. I like it.
I actually used to live right near the NPR offices in Crystal City.
You might know a pythonista I know who used to work there and is now doing a machine learning start-up. (his name is Greg)
Re:Agate: A Data Analysis Library for Journalists
by plafl on Wednesday October 28, 2015 @11:34AM
(#10464991)
I like pandas but I find it confusing to use. I wouldn't mind sacrificing some speed for ease of use. In particular it would be great to find a library with something similar to pandas' MultiIndex, but a more intuitive behavior. However, from skimming over Agate's docs, it doesn't seem to have something similar. Anyway, it's great that alternatives are attempted.
Sites like FiveThirtyEight and The Economist usually have separate graphics departments who use nonstatistical tools like Illustrator to annotate and apply custom theming. Good visualization is an huge part of a persuasive argument, and so being able to do both is important (and languages like R have good native plotting as well)
Additionally, looking at the agate code Jupyter notebook, it appears that the processing syntax is very, very similar to pandas (despite the warning against it) aside from the print_bars method, so I'm confused about the specific utility of the module.
From the post comments, after someone else noted the similarities too:
> You're right, most of my problems with pandas are not in its interfaces. My problems there are with the overhead of the numpy dependency, its confusing handling of text, nulls, etc. (inherited from numpy) and its documentation aimed at advanced users rather than beginners.