[pydata-outreach-staff] Pandas-specific invite text (round 2)

[Asheesh Laroia]

Suggested text:

<text>

Subject: Learn how to do science with Python, and make the tools better, 
Sun 12/17

On Sunday, Dec 17, newcomers and experienced programmers will be working 
together to teach, learn, and improve data processing tools in Python. 
We'll learn about pandas, a library for loading and processing large 
numerical data sets into Python -- and then we'll get to work improving 
it, mentored by Chang She, a Pandas maintainer.

This special event is intended to be welcoming to anyone with some Python 
programming experience, ranging from no experience with the above tools 
all the way up to core contributors. It's free of cost, and you're 
invited! Here's how it works:

Morning:

* Meet and greet, and tutorial on PyData and Pandas

Afternoon:

* Lunch, sponsored by the Python Software Foundation

* Group work contributing code to Pandas via Github, mentored by a core 
Pandas contributor, Chang She

* Self-paced contribution sprint, where you can help any PyData project by 
improving documentation, code, performance, test cases, or examples, with 
mentorship continously available.

It runs from 10 AM to 5:15 PM in Manhattan. Sign up here: 
http://pydata-workshop-sprint.eventbrite.com/ (Space donated by Pivotal 
Labs; thanks!)

More info here: 
https://github.com/svaksha/PyData-Workshop-Sprint/wiki/2012-NYC

If you want to get in touch with the organizers, email: 
pydata-outreach-staff at lists.openhatch.org

</text>

New notes on the above text:

* I kept the subject line the same; I figure vague and intriguing is OK, 
since many prospective attendees may not know what pandas is, but do 
know what science is.

* I narrowed the first paragraph down to be very Pandas-y. I hope I'm 
accurately capturing and conveying what Pandas is. My sense is "yes," 
after spending some time reading their docs.

* I mentioned "performance" in the "Self-paced" part because that's a part 
I personally will find exciting, so presumably other people like me will 
find it exciting.

* This fixes the bug where we said it was OK to work on non-pandas pydata 
stuff. (-:

* It's a little longer than 2 paragraphs, once you add in all the bullets.

* It still could be a little clearer on the knowledge prerequisites. Part 
of why it's somewhat vague is I don't know the details of Chang's lecture. 
I invited Chang to this list, so if he joins, great; if not, then we're 
flying blind on this part, which troubles me.

* I added a "Thank you" to Pivotal for the space.

Comments welcome! Again, I haven't sent this out anywhere but our private 
list.

-- Asheesh.