In [1]:

    

import pandas as pd
import re
import requests

from IPython.display import IFrame

import folium


    

In [2]:

    

df = pd.read_excel('../data/one_dollar_oysters.xlsx')


    

In [3]:

    

df.tail(n=2)


    

    
Out[3]:






  

    

      

      
Name
      
Address
      
Phone
      
Hours
      
Notes
      
Verified
    
  
  

    

      
67
      
Woodhouse Fish Company
      
1914 Fillmore St.
      
415-437-2722
      
Tues 11:30 - 10:00
      
NaN
      
NaN
    
    

      
68
      
Woodhouse Fish Company
      
2073 Market St.
      
415-437-2722
      
Tues 11:30 - 9:30
      
NaN
      
NaN
    
  

In [4]:

    

df.shape


    

    
Out[4]:





(69, 6)

In [5]:

    

# Split df.Hours into days of week, start time, and end time (not done yet, obvs)
re.compile('')
df['days'] = df.Hours


    

In [6]:

    

f = open('/Users/tesskornfield/google_api_key.txt', 'r')
GOOGLE_API_KEY = f.readline().rstrip()


    

In [7]:

    

lats = []
lngs = []

for address in df.Address.tolist()[:69]:
    
    try: 
        response = requests.get('https://maps.googleapis.com/maps/api/geocode/json?address=%s+San+Francisco' %address)
        responsejson = response.json()

        lat = responsejson['results'][0]['geometry']['location']['lat']
        lng = responsejson['results'][0]['geometry']['location']['lng']
        
    except:
        lat = 'na'
        lng = 'na'
        
    lats.append(lat)
    lngs.append(lng)


    

In [8]:

    

df['lats'] = lats
df['lngs'] = lngs


    

In [21]:

    

tileset = r'http://tile.stamen.com/terrain/{z}/{x}/{y}.png'
attribution = 'Map data by OpenStreetMap, under ODbL.'
zip_map = folium.Map(location=[37.769230, -122.433810], zoom_start=12, tiles=tileset, attr=attribution)

for row_index, row in df.iterrows():
    
    zip_map.simple_marker([row['lats'],row['lngs']],popup='%s, %s, %s' %(row['Name'],row['Address'],row['Hours']))

mappath = 'orsters.html'
zip_map.create_map(path=mappath)

IFrame(mappath,1200,550)


    

    
Out[21]:





        
        

In [ ]: