I have a time series that I have pulled from a netCDF file and I\'m trying to convert them to a datetime format. The format of the time series is in \'days since 1990-01-01 00:0
The datetime
module's timedelta is probably what you're looking for.
For example:
from datetime import date, timedelta
days = 9465 # This may work for floats in general, but using integers
# is more precise (e.g. days = int(9465.0))
start = date(1990,1,1) # This is the "days since" part
delta = timedelta(days) # Create a time delta object from the number of days
offset = start + delta # Add the specified number of days to 1990
print(offset) # >>> 2015-12-01
print(type(offset)) # >>>
You can then use and/or manipulate the offset object, or convert it to a string representation however you see fit.
You can use the same format as for this date object as you do for your time_datetime
:
print(offset.strftime('%Y-%m-%d %H:%M:%S'))
Output:
2015-12-01 00:00:00
Instead of using a date
object, you could use a datetime
object instead if, for example, you were later going to add hours/minutes/seconds/timezone offsets to it.
The code would stay the same as above with the exception of two lines:
# Here, you're importing datetime instead of date
from datetime import datetime, timedelta
# Here, you're creating a datetime object instead of a date object
start = datetime(1990,1,1) # This is the "days since" part
Note: Although you don't state it, but the other answer suggests you might be looking for timezone aware datetimes. If that's the case, dateutil
is the way to go in Python 2 as the other answer suggests. In Python 3, you'd want to use the datetime
module's tzinfo.