Dask Array from DataFrame

Question

Is there a way to easily convert a DataFrame of numeric values into an Array? Similar to values with a pandas DataFrame. I can't seem to find any way to do this with the provided API, but I'd assume it's a common operation.

Answer 1

Edit: yes, now this is trivial

You can use the .values property

x = df.values

Older, now incorrect answer

At the moment there is no trivial way to do this. This is because dask.array needs to know the length of all of its chunks and dask.dataframe doesn't know this length. This can not be a completely lazy operation.

That being said, you can accomplish it using dask.delayed as follows:

import dask.array as da
from dask import compute

def to_dask_array(df):
    partitions = df.to_delayed()
    shapes = [part.values.shape for part in partitions]
    dtype = partitions[0].dtype

    results = compute(dtype, *shapes)  # trigger computation to find shape
    dtype, shapes = results[0], results[1:]

    chunks = [da.from_delayed(part.values, shape, dtype) 
              for part, shape in zip(partitions, shapes)]
    return da.concatenate(chunks, axis=0)