Parsing csv using python

[Larz60+]

I added some more code to show how to access the sorted list:

import operator
import csv


# li = [["user1", 100], ["user2", 234], ["user3", 131]]
li = []
with open('sampleCSV.csv') as f:
    csvdata = csv.reader(f, delimiter=',')
    for row in csvdata:
        li.append(row)
# li sorted ascending on date (second column)
li_ascending = sorted(li, key=operator.itemgetter(1))
li_descending = sorted(li, key=operator.itemgetter(1), reverse=True)
print('Ascending: {}\nDescending: {}\n'.format(li_ascending, li_descending))

# get all ascending grouped by date:
last_date = 0
for inner in li_ascending:
    if len(inner) != 3:
        break
    if last_date == 0:
        last_date == inner[1]

    if inner[1] != last_date:
        print('\n')
        last_date = inner[1]
    print('Value: {}, Date: {}, Time: {}'.format(inner[0], inner[1], inner[2]))

output:

Output:
Ascending: [['24.99', '2015-06-01', '00:00:12'], ['0', '2015-06-01', '00:03:15'], ['24.99', '2015-06-01', '00:08:01'], ['0', '2015-06-01', '00:08:23'], ['46.73', '2015-06-01', '00:08:51'], ['0', '2015-06-01', '00:08:58'], ['164.45', '2015-06-01 00:04:05'], ['47.73', '2015-06-02', '00:00:25'], ['101.74', '2015-06-02', '00:04:11'], ['119.99', '2015-06-02', '00:04:35'], ['38.59', '2015-06-02', '00:05:26'], ['73.47', '2015-06-02', '00:06:50'], ['34.24', '2015-06-02', '00:07:36'], ['27.24', '2015-06-03', '00:01:40'], ['82.2', '2015-06-03', '00:12:21'], ['23.48', '2015-06-03', '00:12:35']]
Descending: [['27.24', '2015-06-03', '00:01:40'], ['82.2', '2015-06-03', '00:12:21'], ['23.48', '2015-06-03', '00:12:35'], ['47.73', '2015-06-02', '00:00:25'], ['101.74', '2015-06-02', '00:04:11'], ['119.99', '2015-06-02', '00:04:35'], ['38.59', '2015-06-02', '00:05:26'], ['73.47', '2015-06-02', '00:06:50'], ['34.24', '2015-06-02', '00:07:36'], ['164.45', '2015-06-01 00:04:05'], ['24.99', '2015-06-01', '00:00:12'], ['0', '2015-06-01', '00:03:15'], ['24.99', '2015-06-01', '00:08:01'], ['0', '2015-06-01', '00:08:23'], ['46.73', '2015-06-01', '00:08:51'], ['0', '2015-06-01', '00:08:58']]



Value: 24.99, Date: 2015-06-01, Time: 00:00:12
Value: 0, Date: 2015-06-01, Time: 00:03:15
Value: 24.99, Date: 2015-06-01, Time: 00:08:01
Value: 0, Date: 2015-06-01, Time: 00:08:23
Value: 46.73, Date: 2015-06-01, Time: 00:08:51
Value: 0, Date: 2015-06-01, Time: 00:08:58