Converting timezones from pandas Timestamps

Question

I have the following in a dataframe:

> df['timestamps'].loc[0]
Timestamp('2014-09-02 20:24:00')

I know the timezone (I think it is GMT) it uses and would like to convert the entire column to EST. How can I do that in Pandas?

For reference, I found these other threads:

• Changing a unix timestamp to a different timezone
• Pandas: Read Timestamp from CSV in GMT then resample

but they work with datetime timestamps. E.g.:

> datetime.datetime.fromtimestamp(df['timestamps'].loc[0], tz=None)
returns:

TypeError                                 Traceback (most recent call last)
----> 2 datetime.datetime.fromtimestamp(ts, tz=None)

TypeError: an integer is required (got type Timestamp)

Answer 1

Just use tz_convert method.

Lets say you have a Timestamp object:

   stamp = Timestamp('1/1/2014 16:20', tz='America/Sao_Paulo')
   new_stamp = stamp.tz_convert('US/Eastern')

If you are interested in converting date ranges:

   range = date_range('1/1/2014', '1/1/2015', freq='S', tz='America/Sao_Paulo')
   new_range = range.tz_convert('US/Eastern')

For large time series:

   import numpy as np
   ts = Series(np.random.randn(len(range)), range)
   new_ts = ts.tz_convert('US/Eastern')

As stated in another answer, if your data does not have a timezone set, you'll need to tz_localize it:

   data.tz_localize('utc')