rouli

def readfile(filename):
    with open(filename) as f:
        df = pd.read_html(f)[0]
        df.columns = ['date', 'views']
        df['date'] = df['date'].apply(lambda x:dateutil.parser.parse(x))
        df = df.set_index('date')
        df['day_of_week'] = df.index.map(lambda t:t.dayofweek)
        df['max_weekly_value'] = df.views-pd.rolling_max(df.views, 7)==0
        return df
weekdays = ['Mondays', 'Tuesdays', 'Wednesdays', 'Thursdays', 'Fridays', 'Saturdays', 'Sundays']

rouli

#observed data
popsize = 10000.0 
infected_data = np.array([  7, 10, 11, 11, 13, 14, 14, 13, 14, 16, 18, 18, 20, 21, 22, 23, 23, 24, 25, 23])
T = len(infected_data)

I0 = 7
R0 = 5
 

# priors

rouli

import csv

titanic  = open('titanic.txt', "rb")
reader = csv.reader(titanic)


prefix_list = ["Mr ", "Mrs", "Mis"]     # used to determine if passanger's name includes a prefix. Using 3 chars because of Mr. 


# There are several demographic details we can count passengers and survivors by, this is a dictionary to map them out along with col number in the file.

rouli

#!/usr/bin/env python

import binascii, sys, json
import version, tnetstring, flow
from datetime import datetime


def create_har(flows):
    return {
        "log":{