write Pandas DatetimeIndex to netCDF variable

Question

I am trying to write out a time series of dates to a netCDF variable. My dates are stored as a Pandas DatetimeIndex called date_array. The code I'm trying use is as follows:

Times = w_nc_fid.createVariable('Times','S1',('time',))
Times[:] = str(date_array)

The result is a [72,1] array all with just the string D. What I'm actually trying to write out are the strings of dates (72 consecutive dates):

'2015-07-19 10:00:00'
'2015-07-19 11:00:00'
'2015-07-19 12:00:00'

Can anyone help me with this?

Is there a reason you want to write the dates as strings and not as floats? Typically, time in netCDFs is stored as a array of times since a reference time (e.g. "says since 1970-01-01"). — jhamman
– jhamman, Commented Aug 9, 2015 at 3:30

N1B4 · Accepted Answer · 2015-08-09 23:35:41Z

3

Using netCDF4, it can be accomplished using the following:

import numpy as np
import netCDF4

times = np.array(['2015-07-19 10:00:00', '2015-07-19 11:00:00', '2015-07-19 12:00:00'], dtype=object)

fileout = netCDF4.Dataset('./string_out.nc', 'w')
fileout.createDimension('time', len(times))
times_out = fileout.createVariable('times', str, 'time',)
times_out[:] = times
fileout.close()

Which you can confirm using ncks/ncdump:

>>> ncks string_out.nc | more
...
time[0] times[0]=2015-07-19 10:00:00 
time[1] times[1]=2015-07-19 11:00:00 
time[2] times[2]=2015-07-19 12:00:00

answered Aug 9, 2015 at 23:35

N1B4

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