title: Add additional column in merged csv file
body: <p>My code merges csv files and removes duplicates with pandas. 
  Is it possible to add an additional header with values to the single merged file?</p>
  
  <p>The additional header should be called <code>Host Alias</code> and should correspond to <code>Host Name</code></p>
  
  <p>E.g. <code>Host Name</code> is <code>dpc01n1</code> and the corresponding <code>Host Alias</code> should be <code>dev_dom1</code>
       <code>Host Name</code> is <code>dpc02n1</code> and the corresponding <code>Host Alias</code> should be <code>dev_dom2</code>
  etc.</p>
  
  <p>Here is my code</p>
  
  <pre><code>from glob import glob
  import pandas as pd
  
  class bcolors:
      HEADER = '\033[95m'
      OKBLUE = '\033[94m'
      OKGREEN = '\033[92m'
      WARNING = '\033[93m'
      FAIL = '\033[91m'
      ENDC = '\033[0m'
      BOLD = '\033[1m'
      UNDERLINE = '\033[4m'
  
  input_path = r'C:\Users\urale\Desktop\logs'
  output_path = r'C:\Users\urale\Desktop\logs' + '\\'
  output_name = 'output.csv'
  
  stock_files = sorted(glob(input_path + '\pc_dblatmonstat_*_*.log'))
  print(bcolors.OKBLUE + 'Getting .log files from', input_path)
  
  final_headers = [
          'Start Time', 
          'epoch', 
          'Host Name', 
          'Db Alias', 
          'Database', 
          'Db Host', 
          'Db Host IP',
          'IP Port',
          'Latency (us)'
  ]
  
  #read in files via list comprehension
  content = [pd.read_csv(f,usecols = final_headers, sep='[;]',engine='python') 
             for f in stock_files]
  print(bcolors.OKBLUE + 'Reading files')
  
  
  #combine files into one dataframe
  combo = pd.concat(content,ignore_index = True)
  print(bcolors.OKBLUE + 'Combining files')
  
  #drop duplicates
  combo = combo.drop_duplicates()
  #combo = combo.drop_duplicates(final_headers, keep=False)
  print(bcolors.OKBLUE + 'Dropping duplicates')
  
  #write to csv:
  combo.to_csv(output_path + output_name, index = False)
  print(bcolors.OKGREEN + 'Merged file output to', output_path, 'as', output_name)
  </code></pre>