title: pandas df after fillna() is still NaN
body: <p>A 40000 rows 1 column data saved as excel. There are hundred  null values in it. Such as row 361... 
  When I carried out <code>df.fillna(method='bfill')</code>, the NaN values is still NaN.
   If sliced a df fragment contained Null values, it processed expectently.
  I tried but still could not fill NaN cells.
  So what's wrong with it?
  The df file is here:</p>
  
  <p><a href="https://www.jianguoyun.com/p/DfOdIGsQkL6WBhjYlTE" rel="nofollow noreferrer">excel file click here</a></p>
  
  <pre><code>df=pd.read_execel('npp.xlsx')
  df.fillna(method='bfill')
  print( df.iloc[360:370,] )
  Out[122]: 
            0
  t360     NaN
  t361     NaN
  t362     NaN
  t363     NaN
  t364  220.50
  t365  228.59
  t366     NaN
  t367     NaN
  t368     NaN
  t369     NaN
  </code></pre>
  
  <p>When apply <code>fillna()</code> on sliced df, the NaN values could be replaced:</p>
  
  <pre><code>print( df.iloc[360:370,].fillna(method='bfill') )
         0
  t360  220.50
  t361  220.50
  t362  220.50
  t363  220.50
  t364  220.50
  t365  228.59
  t366     NaN
  t367     NaN
  t368     NaN
  t369     NaN
  </code></pre>