title: setting partitions for dask using read_csv
body: <p>Consider the following code:</p>
  <pre><code>import dask
  import dask.dataframe as dd
  import pandas as pd
  
  data_dict = {'data1':[1,2,3,4,5,6,7,8,9,10],
               'data2':[10,20,30,40,50,60,70,80,90,100]
               }
  
  df_pd = pd.DataFrame(data_dict)
  df_pd.to_csv('data.csv')
  
  # this works
  df_dask_from_pd = dd.from_pandas(df_pd,npartitions=2)
  df_dask_from_pd['data1x2'] = df_dask_from_pd['data1'].apply(lambda x:2*x,meta=('data1x2','int64')).compute()
  
  
  # this does not work
  df_dask_from_csv = dd.read_csv('data.csv')
  df_dask_from_csv['data1x2'] = df_dask_from_csv['data1'].apply(lambda x:2*x,meta=('data1x2','int64')).compute()
  </code></pre>
  <p>I'm trying to figure out why the block of code after <code>#this works</code> works, while the block of code after <code>#this does not work</code> does not work. I think it has to do with setting number of partitions. So I tried changing the second block to</p>
  <pre><code># this does not work
  df_dask_from_csv = dd.read_csv('data.csv')
  df_dask_from_csv = df_dask_from_csv.repartition(npartitions=2)
  df_dask_from_csv['data1x2'] = df_dask_from_csv['data1'].apply(lambda x:2*x,meta=('data1x2','int64')).compute()
  </code></pre>
  <p>The error I get is</p>
  <pre><code>ValueError: Not all divisions are known, can't align partitions. Please use `set_index` to set the index.
  </code></pre>
  <p>And I can't figure out what to do with <code>set_index</code>.</p>