from IPython.display import HTML
import urllib2

goog = urllib2.urlopen("https://www.google.com/?q=parametres+GET")
HTML(goog.read().decode('iso-8859-1'))

import pandas as pd

bikes = urllib2.urlopen('https://github.com/defeo/in202/raw/gh-pages/assets/bike-dataset.csv')
b = pd.read_csv(bikes)

import json

data = json.load(urllib2.urlopen('http://eu.battle.net/api/sc2/ladder/grandmaster?locale=fr_FR'))

type(data)

data.keys()

type(data['ladderMembers'])

data['ladderMembers'][0]

sc2 = pd.DataFrame(data['ladderMembers'])

sc2

sc2['percent'] = sc2.wins / (sc2.wins + sc2.losses)
sc2.groupby('favoriteRaceP1').mean()

import datetime
import dateutil

date = datetime.datetime(2015, 3, 2)
date

date.ctime()

dateutil.parser.parse('2015-3-2')

dateutil.parser.parse('2/3/2015')

dateutil.parser.parse('20/3/2015')

delta = datetime.datetime.now() - datetime.datetime(2015, 3, 4)
delta

delta.total_seconds()

b.head()

type(b['dteday'][0])

b.dtypes

b.dteday - b.dteday

bikes = urllib2.urlopen('https://github.com/defeo/in202/raw/gh-pages/assets/bike-dataset.csv')
bb = pd.read_csv(bikes, parse_dates=["dteday"])

bb.dtypes

type(bb['dteday'][0])

bb.dteday - bb.dteday

from geopy.geocoders import Nominatim
coder = Nominatim()

l = coder.geocode("45 avenue des États Unis, Versailles")
l

l2 = coder.reverse((46.0,4.0))
l2.address

l.latitude, l.longitude

from geopy.distance import distance

distance(l.point, l2.point)

distance(l.point, (49.0, 3.4))