Is there a function in pandas to convert timestamps with CST as the time zone?
Question:
I have a data frame which has the time_zone and the date in different columns. I want to get the local time corresponding to the time_zone.
I have the data frame as below:
df = pd.DataFrame({'CREATED_DT':['2017-01-01 20:24:21','2017-01-01 21:10:54','2017-01-02 11:48:12','2017-01-02 19:30:53','2017-01-02 21:06:55'],
'Time_Zone':['EST','EST','CET','EST','CST']})
df['CREATED_DT'] = pd.to_datetime(df['CREATED_DT']).dt.tz_localize('UTC')
I have converted the created date to UTC and the time_zone is in a different column. I want to get the local time corresponding to the timezone. So the code for it is :
df['Local_Time'] = df.apply(lambda x: x['CREATED_DT'].tz_convert(x['timezone']), axis = 1)
Which works fine in case the time_zone is EST,CET but gives an error for CST which says:
UnknownTimeZoneError: ('CST', u'occurred at index 4')
I am not sure if there is a way to handle this other than hard coding … please suggest if there is any other library or function that could be used?
Answers:
The reason why CST as a timezone throws an error is because it can refer to 3 different timezones: Central Standard Time, which is North America’s Central Time Zone (UTC -0600), China Standard Time (UTC +0800) and Cuba Standard Time (UTC -0400). I’m assuming you want to use Central Standard Time.
An easy way to converge time, is the use the pytz library, which has a constantly updated database of most timezones.
In your case, the line that converts the date to the timezone could be changed to this line:
import pytz
df['Local_Time'] = df.apply(lambda x: pytz.timezone("US/Central" if x['Time_Zone'] == 'CST' else x['Time_Zone']).normalize(x['CREATED_DT']), axis = 1)
(sidenote: in pytz, Central Standard Time is 'US/Central', China Standard Time is 'Asia/Shanghai' and Cuba Standard Time is 'Cuba'. For any other times, you can check this stackoverflow question or this wikipedia page)
It might also make your code a bit more readable if you made it a function instead of a lambda at this point though.
The following worked for me:
df['Local_Time'] = pd.to_datetime(df,unit='s', utc=True)
.map(lambda x: x.tz_convert('America/Chicago'))
There is no timezone named CST, CDT, or EST. This is the list of the name of timezones in pytz.
Hope this helps someone!
I have a data frame which has the time_zone and the date in different columns. I want to get the local time corresponding to the time_zone.
I have the data frame as below:
df = pd.DataFrame({'CREATED_DT':['2017-01-01 20:24:21','2017-01-01 21:10:54','2017-01-02 11:48:12','2017-01-02 19:30:53','2017-01-02 21:06:55'],
'Time_Zone':['EST','EST','CET','EST','CST']})
df['CREATED_DT'] = pd.to_datetime(df['CREATED_DT']).dt.tz_localize('UTC')
I have converted the created date to UTC and the time_zone is in a different column. I want to get the local time corresponding to the timezone. So the code for it is :
df['Local_Time'] = df.apply(lambda x: x['CREATED_DT'].tz_convert(x['timezone']), axis = 1)
Which works fine in case the time_zone is EST,CET but gives an error for CST which says:
UnknownTimeZoneError: ('CST', u'occurred at index 4')
I am not sure if there is a way to handle this other than hard coding … please suggest if there is any other library or function that could be used?
The reason why CST as a timezone throws an error is because it can refer to 3 different timezones: Central Standard Time, which is North America’s Central Time Zone (UTC -0600), China Standard Time (UTC +0800) and Cuba Standard Time (UTC -0400). I’m assuming you want to use Central Standard Time.
An easy way to converge time, is the use the pytz library, which has a constantly updated database of most timezones.
In your case, the line that converts the date to the timezone could be changed to this line:
import pytz
df['Local_Time'] = df.apply(lambda x: pytz.timezone("US/Central" if x['Time_Zone'] == 'CST' else x['Time_Zone']).normalize(x['CREATED_DT']), axis = 1)
(sidenote: in pytz, Central Standard Time is 'US/Central', China Standard Time is 'Asia/Shanghai' and Cuba Standard Time is 'Cuba'. For any other times, you can check this stackoverflow question or this wikipedia page)
It might also make your code a bit more readable if you made it a function instead of a lambda at this point though.
The following worked for me:
df['Local_Time'] = pd.to_datetime(df,unit='s', utc=True)
.map(lambda x: x.tz_convert('America/Chicago'))
There is no timezone named CST, CDT, or EST. This is the list of the name of timezones in pytz.
Hope this helps someone!