issue_comments

@fmaussion Thank you, I'm trying this now. I actually just came back to this thread to edit my original reply - xarray 0.8 won't cut it for me because I need to use features from 0.10

That conda update --all really took me a few steps backwards! Hopefully the new environment will work better.

Edit: Solved, thank you

@max-sixty @jhamman thanks for your replies, I uninstalled both versions of xarray that I had, tried (unsuccessfully # All requested packages already installed.) to update Python, then reinstalled xarray via conda install -c anaconda xarray, to which the import worked but gave: python /nerc/n02/n02/amethyst/.conda/envs/my_root/lib/python3.4/importlib/_bootstrap.py:321: FutureWarning: The pandas.tslib module is deprecated and will be removed in a future version. return f(*args, **kwds) The version of xarray installed is 0.8.2, which just won't seem to update to a newer version. Could be something to do with the fact I'm using Miniconda? Anyway, as long as it works for now. Is this likely to cause problems for me along the line?

@spencerkclark yeah I was using a different platform, updated my xarray version and this works now, thanks!

@spencerkclark ```python Traceback (most recent call last): File "/var/spool/torque/mom_priv/jobs/63347.rdf-xcat.SC", line 22, in <module> a = ml50_shear[0].where(ml50_shear[0] >= 11, other = 0)

NotImplementedError: The optional argument 'other' has not yet been implemented ```

@spencerkclark Oh you're right, I didn't think about that - it returns 4

Gonna try with just the first of the four

@spencerkclark ah sorry I missed line 5 - I'm not looking to get the mean, I want to make sure the unusual values are still represented. That might be why mine went wrong, it generally only works when there's just one time. Anyway, here's what I tried: ```python import xarray as xr from function_codes import sfcwinds, complete_shear, winds import os pathway = #my pathway os.chdir(pathway)

sfc_winds = sfcwinds("sfc") ml50_winds = winds("ml50") ml50_shear = complete_shear(sfc_winds, ml50_winds)

a = ml50_shear.where(ml50_shear >= 11, other = 0) b = a.where(a == 0, other = 1) pa = (b.sum('time') / b.sizes['time']) * 100 print(pa) ```

@spencerkclark following your method: python AttributeError: 'tuple' object has no attribute 'where'

@spencerkclark Thanks a lot, I'll give it a try 👍

@spencerkclark python a = da.loc[date[0]] #the initial time, obviously this part doesn't work but this is the methodology b = a.where(a >= threshold, other = 0) #keeps values that satisfy the threshold, sets the rest to 0 c = b.where(b == 0, other = 1) #sets all values that satisfy the threshold to 1 new_array = zero_array + c #zero_array is just an array of the same shape without time, set to 0 runs = runs + 1 Loops through this whole thing for every time (changing the loc to date[1], date[2], etc.), then: python percentage = (new_array / runs) * 100

This is not my complete code but you should get the idea, as I said it works fine with only 1 time per day

@spencerkclark I'm creating a 2D array of the percentage of time each lon/lat coordinate exceeds a defined threshold. I did this fine before, but I was only using 1 time from each day

@spencerkclark thanks for this, using '1979-01-01T00' works which is a relief. I am trying to use the method of date[number] because I have in excess of 4,000 times to go through. Is there a way to get it to work? I figured adding the %H would work, but obviously not!

Otherwise, at least I know I can revise my code to state the datetime explicitly.

@fmaussion thank you! Think I got a bit confused