title: Dask: Drop NAs on columns?
body: <p>I have tried to apply a filter to remove columns with too many NAs to my dask dataframe:</p>
  
  <pre><code>df.dropna(axis=1, how='all', thresh=round(len(df) * .8))
  </code></pre>
  
  <p>Unfortunately it seems that the dask <code>dropna</code> API is slightly different from that of pandas and does not accept either an <code>axis</code> nor a <code>threshold</code>.
  One partial way around it is to iterate column by column and remove those that are constant (regardless of whether they are filled with NAs or not, as I do not mind getting rid of constants):</p>
  
  <pre><code>    for col in df.columns:
          if len(df[col].unique()) == 1:
              new_df = df.drop(col, axis = 1)
  </code></pre>
  
  <p>But this does not let me apply a threshold. I could compute the threshold manually by adding:</p>
  
  <pre><code>elif sum(df[col].isnull().compute()) / len(df[col]) &gt; 0.8:
      new_df = df.drop(col, axis = 1)
  </code></pre>
  
  <p>But I'm not sure calling <code>compute</code> and <code>len</code> at this point would be optimal and I would be curious to know if there are any better ways to go about this ?</p>