title: Get the missing columns from one dataframe and append it to another dataframe
body: <p>I have a Dataframe <code>df1</code> with the columns. I need to compare the headers of columns in <code>df1</code> with a list of headers from <code>df2</code> </p>
  
  <pre><code>df1 =['a','b','c','d','f']
  df2 =['a','b','c','d','e','f'] 
  </code></pre>
  
  <p>I need to compare the <code>df1</code> with <code>df2</code> and if any missing columns, I need to add them to <code>df1</code> with blank values. </p>
  
  <p>I tried <code>concat</code> and also <code>append</code> and both didn't work. with <code>concat</code>, I'm not able to add the column <code>e</code> and with <code>append</code>, it is appending all the columns from <code>df1</code> and <code>df2</code>. How would I get only missing column added to <code>df1</code> in the same order?</p>
  
  <pre><code>df1_cols = df1.columns
  df2_cols = df2._combine_match_columns
  
  if (df1_cols == df2_cols).all():
          df1.to_csv(path + file_name, sep='|')
  else:
      print("something is missing, continuing")
      #pd.concat([my_df,flat_data_frame], ignore_index=False, sort=False)
      all_list = my_df.append(flat_data_frame, ignore_index=False, sort=False)
  </code></pre>
  
  <p>I wanted to see the results as </p>
  
  <pre><code>a|b|c|d|e|f - &gt; headers
  1|2|3|4||5 -&gt; values
  </code></pre>