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a guest Jul 23rd, 2019 66 Never
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  1. SoftwareVersion,2.1.0.46
  2. SystemType,Gen3
  3. CodeClass,Name,Accession,Count
  4. Endogenous,CCNO,NM_021147.4,18
  5. Endogenous,MYC,NM_002467.3,1114
  6. Endogenous,CD79A,NM_001783.3,178
  7. Endogenous,FSTL3,NM_005860.2,529
  8.      
  9. ScannerID,1609P0139
  10. StagePosition,1
  11. BindingDensity,0.19
  12. CodeClass,Name,Accession,Count
  13. Endogenous,CCNO,NM_021147.4,196
  14. Endogenous,MYC,NM_002467.3,962
  15. Endogenous,CD79A,NM_001783.3,390
  16. Endogenous,FSTL3,NM_005860.2,67
  17.      
  18. CodeClass,Name,Accession,small_example1,small_example2
  19. CCNO,NM_021147.4,Endogenous,18,196
  20. MYC,NM_002467.3,Endogenous,1114,962
  21. CD79A,NM_001783.3,Endogenous,178,390
  22. FSTL3,NM_005860.2,Endogenous,529,67
  23.      
  24. import pandas as pd
  25. filenames = ['small_example1.csv', 'small_example2.csv']
  26. path = '/home/Joy'
  27. def convert(filenames):
  28.     for file in filenames:
  29.         df1 = pd.read_csv(file, sep=',')
  30.         df = df1.merge(df2, on=['CodeClass', 'Name', 'Accession'])
  31.         df.to_csv('result.csv')
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