title: Python pandas dataframe interpolate missing data
body: <p>I have a data set like the following. We only have data for the last day of a month I am trying to interpolate rest of it, is it the right way of doing it? </p>
  
  <pre><code>Date  Australia China
  2011-01-01  NaN   NaN
  2011-01-02  NaN   NaN
  -           -     -
  -           -     -
  2011-01-31  4.75  5.81
  2011-02-01  NaN   NaN
  2011-02-02  NaN   NaN
  -           -     -
  -           -     -
  2011-02-28  4.75  5.81
  2011-03-01  NaN   NaN
  2011-03-02  NaN   NaN
  -           -     -
  -           -     -
  2011-03-31  4.75  6.06
  2011-04-01  NaN   NaN
  2011-04-02  NaN   NaN
  -           -     -
  -           -     -
  2011-04-30  4.75  6.06
  </code></pre>
  
  <p>For interpolate this dataframe to find missing NaN values I am using the following code </p>
  
  <pre><code>import pandas as pd
  df = pd.read_csv("data.csv", index_col="Date")
  df.index = pd.DatetimeIndex(df.index)
  df.interpolate(method='linear', axis=0).ffill().bfill()
  </code></pre>
  
  <p>But I am getting an error "TypeError: Cannot interpolate with all NaNs."</p>
  
  <p>What might be wrong here, how I can fix this?</p>
  
  <p>Thanks.</p>