April 2015
Beginner to intermediate
504 pages
8h 36m
English
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Normalizing timestamps using time zones
Time zone management can be one of the most complicated issues to deal with when working with time-series data. Data is often collected in different systems across the globe using local time, and at some point, it will require coordination with data collected in other time zones.
Fortunately, pandas provides rich support for working with timestamps in different time zones. Under the covers, pandas utilizes the pytz and dateutil libraries to manage the time zone operations. The dateutil support is new as of pandas 0.14.1 and currently only supported for fixed offset and tzfile zones. The default library used by pandas is pytz, with support for dateutil provided for compatibility with other applications.
pandas ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.