[FIXED] CSV Grouping w/o Pandas

Issue

Id like to group data in a .csv file. My data is like the following:

code,balance
CN,999.99
CN,1.01
LS,177.77
LS,69.42
LA,200.43
WO,100

I would like to group the items by code and sum up the balances of the like codes. Desired output would be:

code,blance
CN,1001
LS,247.19
...

I was originaly using Pandas for this task but will not have a package available to put that library on a server.

mydata = pd.read_csv('./tmp/temp.csv')
out = mydata.groupby('code').sum()

Solutions would preferably be compatible with Python 2.6. I apologize if this is a duplicate, the other posts seem to be grouping differently.

I would also like to avoid doing this in a -

if code = x
    add balance to x_total

-kind of way

MY SOLUTION:

def groupit():
    groups = defaultdict(list)
    with open('tmp.csv') as fd:
        reader = csv.DictReader(fd)
        for row in reader:
            groups[row['code']].append(float(row['balance.']))
    total={key:sum(groups[key]) for key in groups}
    total=str(total)
    total=total.replace(' ','')
    total=total.replace('{','')
    total=total.replace('}','')
    total=total.replace("'",'')
    total=total.replace(',','\n')
    total=total.replace(':',',')

    outfile = open('out.csv','w+')
    outfile.write('code,balance\n')
    outfile.write(total)

Solution

Python > 2.6:

from collections import defaultdict
import csv

groups = defaultdict(list)
with open('text.txt') as fd:
    reader = csv.DictReader(fd)
    for row in reader:
        groups[row['code']].append(float(row['balance']))

totals = {key: sum(groups[key]) for key in groups}
print(totals)

This outputs:

{'CN': 1001.0, 'LS': 247.19, 'LA': 200.43, 'WO': 100.0}

Python = 2.6:

from collections import defaultdict
import csv

groups = defaultdict(list)
with open('text.txt') as fd:
    reader = csv.DictReader(fd)
    for row in reader:
        groups[row['code']].append(float(row['balance']))

totals = dict((key, sum(groups[key])) for key in groups)
print(totals)

Answered By - Perplexabot