by defaulttime series in pandas are time zone naive consider the following time seriesrng pd date_range( : 'periods= freq=' 'ts series(np random randn(len(rng))index=rngthe index' tz field is nonein [ ]print(ts index tznone date ranges can be generated with time zone setin [ ]pd date_range( : 'periods= freq=' 'tz='utc'out[ ] : : : : length freqdtimezoneutc conversion from naive to localized is handled by the tz_localize methodin [ ]ts_utc ts tz_localize('utc'in [ ]ts_utc out[ ] : : + : : : + : : : + : : : + : : : + : : : + : freqd - in [ ]ts_utc index out[ ] : : : : length freqdtimezoneutc once time series has been localized to particular time zoneit can be converted to another time zone using tz_convertin [ ]ts_utc tz_convert('us/eastern'out[ ] : : - : : : - : : : - : : : - : - : : - : : : - : freqd in the case of the above time serieswhich straddles dst transition in the us/eastern time zonewe could localize to est and convert tosayutc or berlin timein [ ]ts_eastern ts tz_localize('us/eastern' time series www it-ebooks info