title: Pandas df.fillna(method = 'pad') not working on 28000 row df
body: <p>Have been trying to just replace the NaN values in my DataFrame with the last valued item however this does not seem to do the job. Just wondering if anyone else has this same issue or what could be causing this problem.</p>
  
  <pre><code>In [16]: ABCW.info()
  Out[16]:&lt;class 'pandas.core.frame.DataFrame'&gt;
           DatetimeIndex: 692 entries, 2014-10-22 10:30:00 to 2015-05-21   16:00:00
           Data columns (total 6 columns):
           Price              692 non-null float64
           Volume             692 non-null float64
           Symbol_Num         692 non-null object
           Actual Price       577 non-null float64
           Market Cap Rank    577 non-null float64
           Market Cap         577 non-null float64
           dtypes: float64(5), object(1)
           memory usage: 37.8+ KB
  
  
  In [18]: ABCW.fillna(method = 'pad')
  
  In [19]: ABCW.info()
  Out [19]: &lt;class 'pandas.core.frame.DataFrame'&gt;
           DatetimeIndex: 692 entries, 2014-10-22 10:30:00 to 2015-05-21 16:00:00
           Data columns (total 6 columns):
           Price              692 non-null float64
           Volume             692 non-null float64
           Symbol_Num         692 non-null object
           Actual Price       577 non-null float64
           Market Cap Rank    577 non-null float64
           Market Cap         577 non-null float64
           dtypes: float64(5), object(1)
           memory usage: 37.8+ KB
  </code></pre>
  
  <p>There is no change in the number of non-null values and there is still all the preexisting NaN values that were previously in the data frame</p>