nanosecond-resolution data. Also provides easy time zone conversions. • Enhanced support for time zones. Add tz_convert and tz_lcoalize methods to TimeSeries and DataFrame. All timestamps are stored as if their UTC timestamps match. Operations between time zone-aware time series with different time zones will result in a UTC-indexed time series. • Time series string indexing conveniences / shortcuts: Handling Using pytz, pandas provides rich support for working with timestamps in different time zones. By default, pandas objects are time zone unaware: In [154]: rng = date_range(’3/6/2012 00:00’, periods=15

nanosecond-resolution data. Also provides easy time zone conversions. • Enhanced support for time zones. Add tz_convert and tz_lcoalize methods to TimeSeries and DataFrame. All timestamps are stored as if their UTC timestamps match. Operations between time zone-aware time series with different time zones will result in a UTC-indexed time series. • Time series string indexing conveniences / shortcuts: timestamps in different time zones using pytz and dateutil li- braries. dateutil support is new [in 0.14.1] and currently only supported for fixed offset and tzfile zones. The default library is pytz.

nanosecond-resolution data. Also provides easy time zone conversions. • Enhanced support for time zones. Add tz_convert and tz_lcoalize methods to TimeSeries and DataFrame. All timestamps are stored as if their UTC timestamps match. Operations between time zone-aware time series with different time zones will result in a UTC-indexed time series. • Time series string indexing conveniences / shortcuts: timestamps in different time zones using pytz and dateutil li- braries. dateutil support is new [in 0.14.1] and currently only supported for fixed offset and tzfile zones. The default library is pytz.

nanosecond-resolution data. Also provides easy time zone conversions. • Enhanced support for time zones. Add tz_convert and tz_lcoalize methods to TimeSeries and DataFrame. All timestamps are stored as if their UTC timestamps match. Operations between time zone-aware time series with different time zones will result in a UTC-indexed time series. • Time series string indexing conveniences / shortcuts: with timestamps in different time zones using pytz and dateutil li- braries. dateutil support is new in 0.14.1 and currently only supported for fixed offset and tzfile zones. The default library is pytz. Support

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 771 20.13.1 Working with Time Zones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 771 20.13.2 Ambiguous Times nanosecond-resolution data. Also provides easy time zone conversions. • Enhanced support for time zones. Add tz_convert and tz_lcoalize methods to TimeSeries and DataFrame. All timestamps are stored as if their UTC timestamps match. Operations between time zone-aware time series with different time zones will result in a UTC-indexed time series. • Time series string indexing conveniences / shortcuts:

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 773 20.13.1 Working with Time Zones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 773 20.13.2 Ambiguous Times nanosecond-resolution data. Also provides easy time zone conversions. • Enhanced support for time zones. Add tz_convert and tz_lcoalize methods to TimeSeries and DataFrame. All timestamps are stored as if their UTC timestamps match. Operations between time zone-aware time series with different time zones will result in a UTC-indexed time series. • Time series string indexing conveniences / shortcuts:

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 859 19.14.1 Working with Time Zones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 860 19.14.2 Ambiguous Times nanosecond-resolution data. Also provides easy time zone conversions. • Enhanced support for time zones. Add tz_convert and tz_lcoalize methods to TimeSeries and DataFrame. All timestamps are stored as if their UTC timestamps match. Operations between time zone-aware time series with different time zones will result in a UTC-indexed time series. • Time series string indexing conveniences / shortcuts:

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 856 19.14.1 Working with Time Zones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 856 xvi 19.14.2 Ambiguous nanosecond-resolution data. Also provides easy time zone conversions. • Enhanced support for time zones. Add tz_convert and tz_lcoalize methods to TimeSeries and DataFrame. All timestamps are stored as if their UTC timestamps match. Operations between time zone-aware time series with different time zones will result in a UTC-indexed time series. • Time series string indexing conveniences / shortcuts:

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 892 19.14.1 Working with Time Zones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 892 19.14.2 Ambiguous Times nanosecond-resolution data. Also provides easy time zone conversions. • Enhanced support for time zones. Add tz_convert and tz_lcoalize methods to TimeSeries and DataFrame. All timestamps are stored as if their UTC timestamps match. Operations between time zone-aware time series with different time zones will result in a UTC-indexed time series. • Time series string indexing conveniences / shortcuts:

nanosecond-resolution data. Also provides easy time zone conversions. • Enhanced support for time zones. Add tz_convert and tz_lcoalize methods to TimeSeries and DataFrame. All timestamps are stored as if their UTC timestamps match. Operations between time zone-aware time series with different time zones will result in a UTC-indexed time series. • Time series string indexing conveniences / shortcuts: Handling Using pytz, pandas provides rich support for working with timestamps in different time zones. By default, pandas objects are time zone unaware: In [156]: rng = date_range(’3/6/2012 00:00’, periods=15