title: Python: Pandas cause invalid type of comparison
body: <p>I have two types of error data that need to corrected. One is with null and one is with Nan.</p>
  
  <pre><code> &gt;&gt;&gt; df_new
            Volume Price   
  Date
  2017-01-01 500  760
  2017-01-02 null 760
  2017-01-03 50   770
  2017-01-04 null 780
  </code></pre>
  
  <p>Another type is with NaN</p>
  
  <pre><code> &gt;&gt;&gt; df_new
            Volume Price   
  Date
  2017-01-01 500  760
  2017-01-02 NaN 760
  2017-01-03 50  770
  2017-01-04 NaN 780
  </code></pre>
  
  <p>How to replace both null and NaN data with 0?
  My code working if either null or NaN but I can't work for both</p>
  
  <pre><code>volume = df_new['Volume'] == 'null' or df_new['Volume'].isnull()
  df_new.loc[volume,'Volume'] = 0
  df_new.replace('null',np.NaN,inplace=True)
  df_new.iloc[0].fillna(df_new.iloc[1].Open,inplace=True)
  </code></pre>
  
  <p>it return error</p>
  
  <blockquote>
    <p>Traceback (most recent call last):  File "", line 1, in
      File
    "/home/.local/lib/python2.7/site-packages/pandas/core/ops.py", line
    763, in wrapper    res = na_op(values, other)  File
    "/home/.local/lib/python2.7/site-packages/pandas/core/ops.py", line
    718, in na_op    raise TypeError("invalid type comparison")TypeError:
    invalid type comparison</p>
  </blockquote>
  
  <p>The code will work if <code>volume = df_new['Volume'] == 'null'</code> but this will not correct the data is it is NaN, and repalce with 0</p>