How to get the Dask scalar value as an ordinary number without using compute

[Damilola]

Hi,

I am trying to get the result of the below Dask sequence of operations as an ordinary number.

Unfortunately, in the Jupyter environment that I am using, the .compute() approach is not allowed for Dask.

Is there any other way by which this can be done or achieved?

import dask.dataframe as dd
import pandas as pd

df = pd.DataFrame({'values': [10, 20, 30, 40, 50]})

ddf = dd.from_pandas(df, npartitions=1)

result = (ddf['values'].sum() * 8) / 1e3

print(result)

I am getting the below result

<dask_expr.expr.Scalar: expr=df[‘values’].sum() * 8 / 1000.0, dtype=float64>

[guillaumeeb]

Hi @Damilola,

@Damilola

Unfortunately, in the Jupyter environment that I am using, the .compute() approach is not allowed for Dask.

Strange, can you explain why?

@Damilola

Is there any other way by which this can be done or achieved?

Well, no. This is the way Dask works: coding using Dask collection whill just build a tasks graph. You need to compute it in order to get final results. I’m not sure why you are using Dask and what you are trying to achieve with it.