BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//pretalx//cfp.scipy.org//2023//speaker//CFCJHA
BEGIN:VTIMEZONE
TZID:America/Chicago
BEGIN:DAYLIGHT
DTSTART:20220713T000000
TZNAME:CDT
TZOFFSETFROM:-0500
TZOFFSETTO:-0500
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:20221106T020000
RDATE:20231105T020000
TZNAME:CST
TZOFFSETFROM:-0500
TZOFFSETTO:-0600
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20230312T030000
RDATE:20240310T030000
TZNAME:CDT
TZOFFSETFROM:-0600
TZOFFSETTO:-0500
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
SUMMARY:Tidy Geospatial Cubes - Deepak Cherian\, Emma Marshall\, Scott Hen
 derson
DTSTART;TZID=America/Chicago:20230713T155000
DTEND;TZID=America/Chicago:20230713T162000
DTSTAMP:20261007T034635Z
UID:pretalx-2023-LCWBBP@cfp.scipy.org
DESCRIPTION:The open-source project\, Xarray\, combines labeled data struc
 tures inspired by Pandas with NumPy-like multi-dimensional arrays to provi
 de an intuitive and scalable interface for scientific analysis. Xarray has
  strong user bases in the physical sciences and geospatial community. Howe
 ver\, new users commonly struggle to fit their dataset into the Xarray mod
 el and with conceptualizing and constructing an Xarray object that makes s
 ubsequent analysis steps easy (“dataset wrangling”). We take inspirati
 on from the “tidy data” concept for dataframes — “datasets structu
 red to facilitate analysis” (Wickham\, 2014) — and attempt a definitio
 n of tidy data for labeled array objects provided by Xarray.
LOCATION:Grand Salon C
URL:https://cfp.scipy.org/2023/talk/LCWBBP/
END:VEVENT
END:VCALENDAR