title: Python - Not identifying Null values even though it is present in the Pandas Dataframe
body: <p>I am reading a csv file and creating a Pandas Dataframe out of it. It has many columns of different datatypes. </p>
  
  <p>The column "localHour" is assumed to contain only numeric values but unfortunately it contains "null" values as it can be seen in Microsoft Excel / Open Office application or even the unique() method in Pandas also reveals that it contains "null" values</p>
  
  <pre><code>df1['localHour'].unique()
  
  Out[78]: 
  array(['9', '12', '17', '16', '22', '19', '11', '15', '6', '18', '7', '21',
         '13', '20', '23', '10', '14', '8', '5', '3', '1', '0', '2', '4',
         'null', '-1'], dtype=object)
  </code></pre>
  
  <p><strong>But surprisingly isnull() method does not find any null values in the column. I am not able to understand what is wrong here</strong>.</p>
  
  <pre><code>df1['localHour'].isnull().values.any()
  Out[80]: False
  
  df1['localHour'].isnull().unique()    
  Out[81]: array([False], dtype=bool)
  </code></pre>