title: Drop rows containing empty cells from a pandas DataFrame
body: <p>I have a <code>pd.DataFrame</code> that was created by parsing some excel spreadsheets. A column of which has empty cells. For example, below is the output for the frequency of that column, 32320 records have missing values for <em>Tenant</em>.</p>
  
  <pre><code>&gt;&gt;&gt; value_counts(Tenant, normalize=False)
                                32320
      Thunderhead                8170
      Big Data Others            5700
      Cloud Cruiser              5700
      Partnerpedia               5700
      Comcast                    5700
      SDP                        5700
      Agora                      5700
      dtype: int64
  </code></pre>
  
  <p>I am trying to drop rows where Tenant is missing, however <code>.isnull()</code> option does not recognize the missing values. </p>
  
  <pre><code>&gt;&gt;&gt; df['Tenant'].isnull().sum()
      0
  </code></pre>
  
  <p>The column has data type "Object". What is happening in this case? How can I drop records where <em>Tenant</em> is missing?</p>