PyData DC 2016
Hosted by Capital One
PyData is a gathering of users and developers of data analysis tools in Python. The goals are to provide Python enthusiasts a place to share ideas and learn from each other about how best to apply our language and tools to ever-evolving challenges in the vast realm of data management, processing, analytics, and visualization.
Costs listed below reflect pricing after Early Bird specials have expired.
- Individual (Oct. 7-9): $325.00
- Startup (Oct. 7-9): $375.00
- Corporate (Oct. 7-9): $425.00
- Academic (Oct. 7-9): $200.00
2-Day Passes (Excludes tutorials on Oct. 7)
- Individual (Oct. 8-9): $275.00
- Startup (Oct. 8-9): $325.00
- Corporate (Oct. 8-9): $375.00
- Academic (Oct. 8-9): $150.00
Tutorial Pass (ONLY valid Friday, Oct. 7)
- Tutorial (Oct. 7): $150.00
-Please Note: If you wish to attend both tutorials on Friday, Oct. 7 and the main sessions on Saturday and Sunday (Oct 8-9), you need to purchase an Individual, Startup, Corporate, or Academic 3-Day Pass.
CFP is now open!
If you are interested in presenting a talk or tutorial, we encourage your submission(s). To see the type of topics presented at previous PyData events, please look at our past conference sites at pydata.org or check out the videos on https://www.youtube.com/user/PyDataTV.
Submission Information - http://pydata.org/dc2016/cfp/
For comprehensive information about PyData DC 2016,
please visit the conference website:
Interested in Sponsoring? Contact us at: firstname.lastname@example.org
What is the refund policy?
100% --- before 28 days
90% --- before 21 days
80% --- before 14 days
70% --- before 7 days
50% --- before the event
0% --- after the event has started
Are there ID requirements or an age limit to enter the event?
While an ID isn't required, we ask that you have one available in case of any questions with your registration.
Attendees under age 14 must be accompanied by an adult.
What can/can't I bring to the event?
We recommend all attendees bring laptops.
Where can I contact the organizer with any questions?
You can contact us by email: email@example.com or phone: 512-222-5449
Is my registration/ticket transferrable?
Please let us know if someone else will be using your ticket to avoid delays at conference registration.
PyData is organized by: NumFOCUS