title: How to find out difference of two dataframes in terms of column name using Python
body: <p>I want to find out the difference between two data frame in terms of column names.</p>
  
  <p>This is sample table1</p>
  
  <pre><code>d1 = {'row_num': [1, 2, 3, 4, 5], 'name': ['john', 'tom', 'bob', 'rock', 'jimy'], 'DoB': ['01/02/2010', '01/02/2012', '11/22/2014', '11/22/2014', '09/25/2016'], 'Address': ['NY', 'NJ', 'PA', 'NY', 'CA']}
  df1 = pd.DataFrame(data = d)
  df1['month'] = pd.DatetimeIndex(df['DoB']).month
  df1['year'] = pd.DatetimeIndex(df['DoB']).year
  </code></pre>
  
  <p>This is sample table2</p>
  
  <pre><code>d2 = {'row_num': [1, 2, 3, 4, 5], 'name': ['john', 'tom', 'bob', 'rock', 'jimy'], 'DoB': ['01/02/2010', '01/02/2012', '11/22/2014', '11/22/2014', '09/25/2016'], 'Address': ['NY', 'NJ', 'PA', 'NY', 'CA']}
  df2 = pd.DataFrame(data = d)
  </code></pre>
  
  <p>table 2 or df2 does not have the month and year column like df1. I want to find out which columns of df1 are missing in df2.</p>
  
  <p>I know there's 'EXCEPT' in sql but how to do it using pandas/python , Any suggestions ?</p>