import re
?re

txt= 'The cat sat on the mat 11 times.'
pattern=re.compile(r'^The (\w*)')
pattern.findall(txt)

txt= 'The cat sat on the mat 11 times.'
pattern=re.compile(r'\s(.at)')
pattern.findall(txt)

pattern2=re.compile(r'^The (\w*) sat (.*) (\d*) times\.$')
grouper=pattern2.match(txt)
grouper.groups()

grouper.group(2)

pattern2.match(txt).group(1)

whatwhere=re.compile(r'^The (?P<what>\w*) sat (?P<where>.*) (\d*) times\.$')
whatwhere.match(txt).group('where')

whatwhere.match(txt).group(0)

whatwhere.match(txt).group(3)

whatwhere.match(txt).groups()

re.sub(r'The (\w*) (.*) ([^\s]*) ([\d]{1,}.*)\.',r'The \3 \2 \1? Was it really \4?',txt)

from datetime import datetime

#Time and datetimes can be represented as special datetime objects
now=datetime.now()
now

#We can index in using .microsecond, .second, .minute, .hour, .day, .month, .year
now.microsecond

#We can format a date in a variety of ways..

#Reference: https://docs.python.org/2/library/datetime.html#strftime-and-strptime-behavior

now.strftime("%d/%m/%Y")

now_sentence=now.strftime("%A, %B %d, %Y (week %W)")
now_sentence

#Shortcuts
now_str=now.strftime("%F")
now_str

#Parse the date back
datetime.strptime(now_str,"%Y-%m-%d")

datetime.strptime(now_sentence,"%A, %B %d, %Y (week %W)")

from dateutil.parser import parse
?parse

parse('11/2/13',dayfirst=True)

parse('11-10-09',dayfirst=None,yearfirst=None)

parse('January 22nd, 1983')

parse('January 22nd, 1983, 10:23am')

import pandas as pd
https://docs.google.com/spreadsheets/d/<KEY>/export?gid=SHEETNUMBER&format=csv
url='https://docs.google.com/a/okfn.org/spreadsheets/d/1M14S4hqG4F5P8H78VdOMMeoITOPBpVZEGoiCvXEFBQg/export?gid=0&format=csv'
cceats=pd.read_csv(url)

cceats

import requests
import json

#http://api.ratings.food.gov.uk/help
#http://docs.python-requests.org/en/latest/user/quickstart/

params={'name':"McDonald's",'address':'SW12 9AU'}
r=requests.get('http://api.ratings.food.gov.uk/Establishments',
               headers={"x-api-version":2},
               params=params)
j=json.loads(r.content)
j

def getFoodRatingData(name,address):
    params={'name':name,'address':address}
    r=requests.get('http://api.ratings.food.gov.uk/Establishments',
                   headers={"x-api-version":2},
                   params=params)
    return r

def parseFoodRatingData(jdata):
    df=pd.DataFrame()
    for establishment in jdata['establishments']:
        info={}
        for item in ['BusinessName','FHRSID','PostCode','RatingValue','RatingDate']:
            info[item]= establishment[item] 
        for item in establishment['geocode']:
            info[item]= establishment['geocode'][item] 
        for item in establishment['scores']:
            info[item]= establishment['scores'][item] 
        df=df.append(info,ignore_index=True)
    return df

def getAndParseFoodRatingData(name,address):
    r=getFoodRatingData(name,address)
    jdata=json.loads(r.content)
    df=parseFoodRatingData(jdata)
    return df

parseFoodRatingData(j)

getAndParseFoodRatingData('Sacro Cuore','NW10 3NB')

adf=pd.DataFrame()
for place in cceats.iterrows():
    adf=adf.append(getAndParseFoodRatingData(place[1]['Name'],place[1]['Postcode']))
adf[['FHRSID','BusinessName','PostCode','RatingDate','RatingValue','latitude','longitude',
               'Structural','Hygiene','ConfidenceInManagement']]

#!pip install folium
import folium

from IPython.display import HTML
import folium

def inline_map(map):
    """
    Embeds the HTML source of the map directly into the IPython notebook.
    
    This method will not work if the map depends on any files (json data). Also this uses
    the HTML5 srcdoc attribute, which may not be supported in all browsers.
    """
    map._build_map()
    return HTML('<iframe srcdoc="{srcdoc}" style="width: 100%; height: 510px; border: none"></iframe>'.format(srcdoc=map.HTML.replace('"', '&quot;')))

def embed_map(map, path="map.html"):
    """
    Embeds a linked iframe to the map into the IPython notebook.
    
    Note: this method will not capture the source of the map into the notebook.
    This method should work for all maps (as long as they use relative urls).
    """
    map.create_map(path=path)
    return HTML('<iframe src="files/{path}" style="width: 100%; height: 510px; border: none"></iframe>'.format(path=path))

ccd=pd.read_csv('/Users/ajh59/Downloads/Code-Club-s-Fave-Restaurants-Sheet1-csv.csv')
ccd

fmap=folium.Map(location=[51.5, 0], zoom_start=9)

for row in ccd.iterrows():
    latlon = [ row[1]['latitude'], row[1]['longitude'] ]
    fmap.simple_marker( latlon )
inline_map(fmap)

fmap=folium.Map(location=[51.5, 0], zoom_start=9)

for row in adf.iterrows():
    latlon = [ row[1]['latitude'], row[1]['longitude'] ]
    fmap.simple_marker( latlon, clustered_marker=True,
                       popup='Name: {name}<br/>Score: {score}'.format(name=row[1]['BusinessName'],
                                                                      score=row[1]['RatingValue']) )
inline_map(fmap)