重塑dask数组（从dask dataframe列获得） [英] Reshape a dask array (obtained from a dask dataframe column)

问题描述

我对dask并不陌生，正在尝试弄清楚如何重整我从dask数据帧的单个列中获得的dask数组，并且遇到了错误。想知道是否有人可能知道此修复程序（而不必强制执行计算）？谢谢！

I am new to dask and am trying to figure out how to reshape a dask array that I've obtained from a single column of a dask dataframe and am running into errors. Wondering if anyone might know of the fix (without having to force a compute)? Thanks!

示例：

import pandas as pd
import numpy as np
from dask import dataframe as dd, array as da
df = pd.DataFrame({'x': [1, 2, 3], 'y': [4, 5, 6]})
ddf = dd.from_pandas(df, npartitions=2)

# This does not work - error ValueError: cannot convert float NaN to integer
ddf['x'].values.reshape([-1,1])

# this works, but requires a compute
ddf['x'].values.compute().reshape([-1,1])

# this works, if the dask array is created directly from a np array
ar = np.array([1, 2, 3])
dar = da.from_array(ar, chunks=2)
dar.reshape([-1,1])

推荐答案

也：

ddf['x'].to_dask_array(lengths=True).reshape([-1,1])

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