new_contents: import pandas as pd
  df = pd.read_excel('mhc.xlsx')
  
  print "Initial size", len(df)
  
  alleles = df['MHC Allele']
  
  # drop missing allele names
  mask = ~alleles.isnull()
  # only count human HLA types 
  mask &= alleles.str.startswith("HLA-")
  # drop 2-digit partial HLA types like HLA-A2 and HLA-DR
  mask &= alleles.str.len() > 7
  
  binding_scores = df['Quantitative Result']
  
  # must have a binding score
  mask &= ~binding_scores.isnull()
  
  epitope_type = df['Epitope Type']
  mask &=  epitope_type == 'Linear peptide'
  
  assay_units = df['Assay Units']
  mask &= assay_units == 'IC50 nM'
  
  assay_method = df['Assay Method']
  mask &= assay_method.str.startswith("Purified MHC")
  
  df_subset = df[mask]
  
  df_clean = pd.DataFrame({
  	'MHC Allele' : df_subset['MHC Allele'], 
  	'Epitope' : df_subset['Epitope'], 
  	'IC50': df_subset['Quantitative Result']
  })
  
  type1_mask = df_clean['MHC Allele'].str.contains("HLA-(A|B|C)")
  
  df_type1 = df_clean[type1_mask]
  print "# Type 1", len(df_type1)
  df_type1.to_csv("mhc1.csv")
  
  type2_mask = df_clean['MHC Allele'].str.startswith("HLA-D")
  df_type2 = df_subset[type2_mask]
  print "# Type 2", len(df_type2)
  df_type2.to_csv("mhc2.csv")
  
  
subject: split data into type 1 and type 2