data_ess_clean_up_step_4.py

import pandas as pd
import datetime
import csv
from collections import defaultdict

source_file = "tech_grand_est_00.csv"
dest_file   = "tech_grand_est_01.csv"

df = pd.read_csv(source_file,
    sep=',' ,
    error_bad_lines=False,
    encoding='iso-8859-1',
    quoting=csv.QUOTE_NONE
)

print "Begining =============================================================="

df.columns = df.columns.str.replace('\"','')
df.columns = df.columns.str.replace("\r",'')

# Verification
print df.columns
print df[:10]
print len(df)

# Selection des departements qui intéressent
# type des departements pas clair.
df = df.loc[df['DEPET'].isin([
    88, 54, 55, 57, 67, 68, 70, 52, 10, 51, 8, 90,
    '88', '54', '55', '57', '67', '68', '70', '52', '10', '51', '8', '08', '90'
])]

df.to_csv(dest_file, sep=',', encoding='utf-8', index=False)

print "Ended ================================================================"