title: Reshape a dask array (obtained from a dask dataframe column)
body: <p>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!</p>
  
  <p>Example:</p>
  
  <pre><code>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])
  </code></pre>