These are chat archives for data-8/datascience

3rd
Jan 2016
Sam Lau
@SamLau95
Jan 03 2016 11:29
@cboettig @henryem to get column values from a table without brackets, you can use
table.values(‘my_column’)
henryem
@henryem
Jan 03 2016 15:29
Cool, thanks
Chris Holdgraf
@choldgraf
Jan 03 2016 15:45
hey folks - how up-to-date will the pip version of this class be?
in previous pip builds there have been some nasty bugs that had already been fixed on the dev branch, but pip wasn't updated
I'm trying to figure out which I should tell an instructor to use...git clone or pip. They're not super familiar with the shell/git/etc so I'd prefer pip, but not if it's going to lag considerably behind the dev branch
@SamLau95 maybe you have thoughts?
Sam Lau
@SamLau95
Jan 03 2016 19:07
@choldgraf last semester we were actively developing the package and were releasing new versions every week because oftentimes students needed the fixes to complete labs. i think using the pip version for class should be fine if for no other reason than parity between instructor / student code output
right now releasing a new version has a lot of friction (depends on both john to update the Pypi version and ryan to update + push the dockerfile) which is why it’s been delayed so long. i’m actually waiting on john to push a bunch of changes the pypi at the moment
Chris Holdgraf
@choldgraf
Jan 03 2016 20:49
ok cool - so you think the pip version is stable enough to use primarily...I'll pass that along to instructors
Sam Lau
@SamLau95
Jan 03 2016 22:11
yup, thanks for that :)
is there a place where this conversation is happening? i’d be willing to listen in and answer questions directly if needed
i think i’d like to push out a written, consolidated, collaborative guide of how an instructor can be productive in creating material using juypter and datascience
but i’m not sure if something like is useful / already being worked on / done
Chris Holdgraf
@choldgraf
Jan 03 2016 22:19
there's no consolidated place for discussion, more just little conversations here and there
I think a guide will be useful, especially for some instructors who have no background at all in computing
E.g., I've been writing up a short post on how to do scientific computing in windows
because somebody was confused about people saying "bring up a terminal and type XXX" which didn't work in windows
but it sounds like having some materials for instructors will be almost just as important (at least early on) as material for students...at least if we want to attract instructors who don't already do scientific computing in python
Sam Lau
@SamLau95
Jan 03 2016 22:22
gotcha. personally i lean towards helping instructors without background in scientific computing since i think long-term that’ll result in more diversity in terms of courses and students addressed
maybe i’ll just throw up a github page on the dsten org with some info
what are some things that are absolutely necessary for a page like that?
Chris Holdgraf
@choldgraf
Jan 03 2016 22:24
that's a good question, I think after the previous and this iteration it'll be clearer what the main pain points are
but it might be worth a brainstorm
either way, we should be documenting what people have questions about
Sam Lau
@SamLau95
Jan 03 2016 22:25
agreed
are there some particular topics that would be the best bang for the buck for instructors right now?
Chris Holdgraf
@choldgraf
Jan 03 2016 22:27
well, one would be coding in a windows environment :)
the Table tutorial is going to be a useful one
I think that there should also be a page for "so you want to learn about scientific computing in general, check out these tutorials:"
because there's already a lot of great content out there for people wanting to learn python, the shell, numpy/scipy/pandas/etc
and if we can just point people to the right place that would alleviate some of the burden
Sam Lau
@SamLau95
Jan 03 2016 22:28
yup