Pivoting a dask dataframe using multiple columns as index

I have a Dask DataFrame of following format:

date	   hour	device	param	  value
20190701	21	dev_01	att_1	0.000000
20190718	22	dev_01	att_2	20.000000
20190718	22	dev_01	att_3	18.611111
20190701	21	dev_01	att_4	18.706083
20190718	22	dev_01	att_5	23.333333

I am trying to pivot the dataframe using Dask.DataFrames.pivot_table() API. However, I want to use 'date', 'hour' and 'device' as the index (i.e, in the pivoted table each row would be uniquely identified by the date, hour and device identifier):

ddf.pivot_table(index = ['date', 'hour', 'device'], columns='param', values='value')

However, it's failing with the following error:

'index' must be the name of an existing column

As I understand from the API documentation (here), the parameter 'index' accepts name of a single column (and not a list) and hence this error.

Is there any other alternative of pivoting a dask dataframe using multiple columns as index?

As mentioned in the docstring the column on which you pivot must be a single column, and it must be of categorical dtype. So to accomplish what you want you would have to convert your three columns into a single categorical column.

This is doable using normal Pandas syntax, but will likely require a full pass through the data to get the categories.