code: def ensembl_to_kegg(organism,kegg_db):
      
      print("KEGG API: http://rest.genome.jp/link/"+kegg_db+"/"+organism)
      sys.stdout.flush()
      kegg_ens=urlopen("http://rest.genome.jp/link/"+kegg_db+"/"+organism).read()
      kegg_ens=kegg_ens.split("\n")
      final=[]
      for i in kegg_ens:
          final.append(i.split("\t"))
      df=pd.DataFrame(final[0:len(final)-1])[[0,1]]
      ens_id=pd.DataFrame(df[1].str.split(":").tolist())[1]
      df=pd.concat([df,ens_id],axis=1)
      df.columns=['KEGGid','ensDB','ENSid']
      df=df[['KEGGid','ENSid']]
      return df
docs: Looks up KEGG mappings of KEGG ids to ensembl ids
  
      :param organism: an organisms as listed in organismsKEGG()
      :param kegg_db: a matching KEGG db as reported in databasesKEGG
  
      :returns: a Pandas dataframe of with 'KEGGid' and 'ENSid'.