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. ...

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