title: rolling mean values to fill NaN
body: <p>I got this function for fill <code>main_df</code>'s NaN cells. After had calculate the progressive rolling mean from every row, I'd then pick the value from the mean stream at each level of NaNs in order to substitute with those NaNs in the <code>main_df</code> cells.</p>
  <p>Here is my trial:</p>
  <pre class="lang-py prettyprint-override"><code>main_df = pd.DataFrame({'a':[1,1,2,3,4,56,6],'b':[2,3,2,np.nan,4,3,6],'c':[1,1,2,3,4,56,np.nan]})
  
  for i in range(len(main_df)):
      main_df.iloc[i] = main_df.iloc[i].fillna(value=main_df.iloc[i].ewm(span=1).mean())
  </code></pre>
  <p>Any suggestions to let it works ?</p>