Python Csv Copy Column

I have a file containing following first_name,last_name,uid,email,dep_code,dep_name john,smith,jsmith,jsmith@gmail.com,finance,21230 john,king,jking,jjing@gmail.com,human resource

Solution 1:

If you call next() on the reader you get one row at at a time; use that to copy over the headers. Copying the email column is easy enough:

import csv

infilename = r'c:\Python27\scripts\colnewfile.csv'
outfilename = r'c:\Python27\scripts\final.csv'

with open(infilename, 'rb') as fp_in, open(outfilename, 'wb') as fp_out:
    reader = csv.reader(fp_in, delimiter=",")
    headers = next(reader)  # read first row

    writer = csv.writer(fp_out, delimiter=",")
    writer.writerow(headers + ['email2'])

    for row in reader:
        if len(row) > 3:
            # make sure there are at least 4 columns
            email = row[3].split('@', 1)[0] + '@hotmail.com'
        writer.writerow(row + [email])

This code splits the email address on the first @ sign, takes the first part of the split and adds @hotmail.com after it:

>>> 'example@gmail.com'.split('@', 1)[0]
'example'
>>> 'example@gmail.com'.split('@', 1)[0] + '@hotmail.com'
'example@hotmail.com'

The above produces:

first_name,last_name,uid,email,dep_code,dep_name,email2
john,smith,jsmith,jsmith@gmail.com,finance,21230,jsmith@hotmail.com
john,king,jking,jjing@gmail.com,human resource,31230,jjing@hotmail.com

for your sample input.

Solution 2:

This can be done very cleanly using pandas . Here it goes:

In [1]: import pandas as pd

In [3]: df = pd.read_csv('your_csv_file.csv')

In [4]: def rename_email(row):
   ...:     return row.email.replace('gmail.com', 'hotmail.com')
   ...:

In [5]: df['email2'] = df.apply(rename_email, axis=1)

In [6]: """axis = 1 or ‘columns’: apply function to each row"""

In [7]: df
Out[7]:
  first_name last_name     uid             email        dep_code  dep_name              email2
0       john     smith  jsmith  jsmith@gmail.com         finance     21230  jsmith@hotmail.com
1       john      king   jking   jjing@gmail.com  human resource     31230   jjing@hotmail.com

In [8]: df.to_csv('new_update_email_file.csv')