Muging of data

matches = {
  1: 'AUTOSERVICIO',
  2: 'CONSUMO/INST',
  3: 'DESPENSA',
  4: 'FARMACIA',
  5: 'GRUPO ACONCAGUA',
  6: 'MAYORISTA',
  7: 'MINORISTA',
  8: 'SUPERMERCADO',
  9: 'DISTRIBUIDOR',
}


import pandas as pd
import re
df = pd.read_csv('/tmp/data.csv', sep='|', quotechar='"', encoding='utf-8')
ndata = []
for idx, data in df.iterrows():
    tmpl = dict(data)
    cliente = data.cliente_nombre.upper()
    if re.search('DESPENSA|BODEGA', cliente):
        tmpl['canal_aco'] = matches.get(3)
    if re.search('MAYORISTA', cliente):
        tmpl['canal_aco'] = matches.get(6)

    ndata.append(tmpl)

dfn = pd.DataFrame(ndata)
dfn.to_csv('/tmp/output.csv', sep='|', quotechar='"', encoding='utf-8')