Mask dataframe column based on datetime index

Question

Very similar to this question except I need to consider both date and time; indexer_between_time does not appear to support any datetime formats I can find.

I have a dask dataframe that looks like this:

                     logger_volt        lat     lon
time                                               
2017-01-01 00:01:20      12.0112  37.150902 -98.362
2017-01-01 00:01:40      12.0113  37.150902 -98.362
2017-01-01 00:02:00      12.0057  37.150902 -98.362
2017-01-01 00:02:20      12.0113  37.150902 -98.362
2017-01-01 00:02:40      12.0058  37.150902 -98.362
2017-01-01 00:03:00      12.0113  37.150902 -98.362

And a list of columns to mask at specific time ranges (the data in these ranges are considered "bad" and should return None there instead) in the form or a list of python tuples:

[   # var       start of mask           end of mask
    ('lat', '2017-01-01 00:01:40', '2017-01-01 00:02:00'),
    ('lon', '2017-01-01 00:02:40', '2017-01-01 00:03:00'),
]

Desired Result:

                     logger_volt        lat     lon
time                                               
2017-01-01 00:01:20      12.0112  37.150902 -98.362
2017-01-01 00:01:40      12.0113       None -98.362
2017-01-01 00:02:00      12.0057       None -98.362
2017-01-01 00:02:20      12.0113  37.150902 -98.362
2017-01-01 00:02:40      12.0058  37.150902    None
2017-01-01 00:03:00      12.0113  37.150902    None

Non-working code:

dqrs = [   # var       start of mask           end of mask
    ('lat', '2017-01-01 00:01:40', '2017-01-01 00:02:00'),
    ('lon', '2017-01-01 00:02:40', '2017-01-01 00:03:00'),
]
df = xarray.open_dataset('filename.cdf').to_dask_dataframe()

dqr_mask = (df == df) | df.isnull()  # create a dummy mask that's all True
for var, start, end in dqrs:
    dqr_mask |= ((df.columns == var) & (df.index >= start) & (df.index >= end))

df = df.mask(dqr_mask).compute()

Problems with other approaches:

• Dask dataframes don't yet implement slice assignment so something like df[start:end] = None won't work for this

Answer 1

You need to select only the column var of dqr_mask in the loop for that you want to modify. here is one way:

dqr_mask = df != df # you want a mask set to False where there is a value
for var, start, end in dqrs:
    #set to True the column var when index is between start and end
    dqr_mask[var] |= (df.index >= start) & (df.index <= end) 
# where dqr_mask False it keeps df otherwise it set the value to None
df = df.mask(dqr_mask,other=None)

print (df)
                    logger_volt      lat     lon
time                                            
2017-01-01 00:01:20     12.0112  37.1509 -98.362
2017-01-01 00:01:40     12.0113     None -98.362
2017-01-01 00:02:00     12.0057     None -98.362
2017-01-01 00:02:20     12.0113  37.1509 -98.362
2017-01-01 00:02:40     12.0058  37.1509    None
2017-01-01 00:03:00     12.0113  37.1509    None