issue_comments: 400901163

Thanks yep my goal is to provide a simple online notebook that can be used to process/qa/qc Argo float data. I'd like to create system that works intuitively with the the current file structure and not build a database of values on the top of them.

here's a first go with some code

``` def processfloat(floatpath,zarrpath): root = zarr.open(zarrpath, mode='a') filenames = glob.glob(floatpath)

for file in filenames:
    ds = xr.open_dataset(file)
    platform = ds.PLATFORM_NUMBER.values[0].strip()
    float =root.get(platform)
    if float==None:
        float = root.create_group(platform)
    cycles = float.get('cycles')
    if cycles == None:
        cycles = float.zeros('cycles', shape=1, chunks=10, dtype=object, object_codec=numcodecs.Pickle())
    while len(cycles)<ds.CYCLE_NUMBER.values[0]:
        cycles.append([0])
    cycles[int(ds.CYCLE_NUMBER.values[0])-1]=ds
summary =float.zeros('summary', shape=1, chunks=10, dtype=object, object_codec=numcodecs.Pickle())
summary[0] = pd.DataFrame(list(map(lambda x: {'latitude':x.LATITUDE.values[0],
                                        'longitude':x.LONGITUDE.values[0],
                                        'time':x.JULD.values[0],'platform':platform,'cycle':x.CYCLE_NUMBER.values[0]}, cycles)))

```