mmas

from datetime import datetime, timedelta
import pandas as pd


source = pd.read_csv('data.csv', index_col='uuid', parse_dates=['date'])

date_1 = datetime.utcnow()
date_0 = date_1 - timedelta(days=30)

data = source[(source['date'] > date_0) & (source['date'] < date_1)]

mmas

def get_visits(groupby):
    ip_visits = data.groupby(groupby)['ip']
    return pd.DataFrame(
        {'unique_visits': ip_visits.apply(lambda x: len(set(x))),
         'total_visits': ip_visits.apply(len)})

data['date_day'] = data['date'].apply(datetime.date)
visits_by_date = get_visits('date_day')
# Redefine with date index to avoid lack of dates.
visits_by_date = pd.DataFrame(visits_by_date,

mmas

#!/usr/bin/env python

import sys


for line in sys.stdin:
    if not line.strip() or line.startswith('Wban'):
        continue
    _, k, v = line[:17].split(',', 2)
    try:

mmas

#!/usr/bin/env python

import sys


last_k = None
max_v = 0

for line in sys.stdin:
    k, v = line.strip().split('\t')

mmas

#!/usr/bin/env python

import re
import sys


started = False

for line in sys.stdin:
    if started:

mmas

#!/usr/bin/env python

import sys


last_k = None
last_v = 0

for line in sys.stdin:
    k, v = line.strip().split('\t')

mmas

#!/usr/bin/env python

import sys

for line in sys.stdin:
    if line.startswith('"'):
        index = line.find('"', 1)
        fields = [line[1:index]]+line[index+2:].split(',')
    else:
        fields = line.split(',')