In [2]:

    

from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
import pandas as pd
import gmaps
import json
import os
%matplotlib inline


    

In [3]:

    

with open('secrets.json') as secrets_file:    
    secrets = json.load(secrets_file)
    
len(secrets)


    

    
Out[3]:





2

In [4]:

    

gmaps.configure(api_key=secrets['GMAPS_API_KEY'])


    

In [53]:

    

plt.rcParams['figure.figsize'] = (5,5)


    

In [9]:

    

stations = pd.read_csv('data/stations_combined.csv', index_col=0)
stations.head(5)


    

    
Out[9]:







  

    

      

      
location
      
name
      
address
      
latitude
      
longitude
      
phone
    
    

      
station_id
      

      

      

      

      

      

    
  
  

    

      
4030
      
Cupertino
      
Valero
      
10002 N De Anza Blvd, Cupertino, CA 95014, USA
      
37.323388
      
-122.031775
      
408-996-1222
    
    

      
10588
      
Cupertino
      
Chevron
      
10023 S De Anza Blvd, Cupertino, CA 95014, USA
      
37.322547
      
-122.032735
      
408-996-9906
    
    

      
24622
      
Los Altos
      
Shell
      
929 Fremont Ave, Los Altos Hills, CA 94024, USA
      
37.354072
      
-122.088676
      
650-949-3746
    
    

      
21026
      
Menlo Park
      
Quik Stop
      
3401 Middlefield Rd, Menlo Park, CA 94025, USA
      
37.470637
      
-122.201853
      
650-365-5783
    
    

      
2550
      
Mountain View
      
ARCO
      
790 W Middlefield Rd, Mountain View, CA 94043,...
      
37.402403
      
-122.074635
      
(650) 934-2630
    
  

In [10]:

    

stations.describe()


    

    
Out[10]:







  

    

      

      
latitude
      
longitude
    
  
  

    

      
count
      
336.000000
      
336.000000
    
    

      
mean
      
37.430980
      
-122.143135
    
    

      
std
      
0.171924
      
0.242650
    
    

      
min
      
36.984397
      
-122.515774
    
    

      
25%
      
37.337983
      
-122.334396
    
    

      
50%
      
37.429867
      
-122.158949
    
    

      
75%
      
37.566795
      
-121.995910
    
    

      
max
      
37.811295
      
-121.551986
    
  

In [11]:

    

fig = plt.figure(figsize=(18,16))
plt.scatter(stations['latitude'], stations['longitude'])
plt.show()


    

In [58]:

    

# m = Basemap(projection='ortho', lat_0=37.430980, lon_0=-122.143135)
# lower left = (37.166, -122.843)
# upper right = (37.859, -121.598)

fig=plt.figure(figsize=(18, 16))

m = Basemap(llcrnrlon=-122.843, llcrnrlat=37.166, urcrnrlon=-121.598, urcrnrlat=37.859,
            projection='lcc',lat_0=37.430980,lon_0=-122.143135,
            resolution ='h')
m.fillcontinents(color='tan')

plt.show()


    

In [16]:

    

stations_coords = list(zip(stations['latitude'], stations['longitude']))


    

In [20]:

    

bay_area_coordinates = (37.430980, -122.143135)
# fig = gmaps.figure(center=bay_area_coordinates, zoom_level=10)
fig = gmaps.figure()
markers = gmaps.marker_layer(stations_coords)
fig.add_layer(markers)
fig


    

In [28]:

    

m = gmaps.Map(width="1000px", height="1000px")
markers = gmaps.marker_layer(stations_coords)
m.add_layer(markers)
m


    

In [ ]: