In [18]:

    

import pandas as pd
import numpy as np
import plotly
import plotly.plotly as py
from plotly.graph_objs import *


    

In [22]:

    

plotly.tools.set_credentials_file(username='lis590dv', api_key='6uwmYW8YbwRrWizyrqCS')
mapbox_access_token = 'pk.eyJ1IjoieGlhb2xpYW5namlhbmciLCJhIjoiY2l6OWJhZTZqMDFoMDJ3cG82Znhja3dodCJ9.88BUSeqz4H2xm8bemGd4VQ'


    

In [32]:

    

df = pd.read_csv('stops.txt',encoding='iso-8859-1')
df.head()


    

    
Out[32]:






  

    

      

      
stop_id
      
stop_code
      
stop_name
      
stop_desc
      
stop_lat
      
stop_lon
      
zone_id
      
stop_url
      
location_type
      
parent_station
    
  
  

    

      
0
      
KBYWSFLD:3
      
MTD4346
      
Kirby & Westfield (South Side)
      
NaN
      
40.098248
      
-88.290173
      
1
      
http://www.cumtd.com/maps-and-schedules/bus-st...
      
0
      
NaN
    
    

      
1
      
PHILOMI:4
      
MTD1026
      
Philo & Michigan (NW Corner)
      
NaN
      
40.101792
      
-88.190865
      
1
      
http://www.cumtd.com/maps-and-schedules/bus-st...
      
0
      
NaN
    
    

      
2
      
DNCNCLKRD:2
      
MTD3333
      
Duncan & Clark (SE Corner)
      
NaN
      
40.117390
      
-88.295470
      
1
      
http://www.cumtd.com/maps-and-schedules/bus-st...
      
0
      
NaN
    
    

      
3
      
TRLSPHILO:1
      
MTD6424
      
Trails & Philo (NE Corner)
      
NaN
      
40.077915
      
-88.190315
      
1
      
http://www.cumtd.com/maps-and-schedules/bus-st...
      
0
      
NaN
    
    

      
4
      
RMNERKA:4
      
MTD4040
      
Romine & Eureka (NW Corner)
      
NaN
      
40.125585
      
-88.227525
      
1
      
http://www.cumtd.com/maps-and-schedules/bus-st...
      
0
      
NaN
    
  

In [43]:

    

#latitude=[]
#longitude=[]
#color=["#ffe6cc","#ffeecc","#fff7cc","#ffffcc","#f7ffcc","#eeffcc","#e6ffcc","#ddffcc","#d5ffcc"]
#color1=[]
#for i in range(9):
#    latitude1=df['stop_lat']
#    longitude1=df['stop_lon']
#    longitude.append(longitude1)
#    latitude.append(latitude1)
#    for j in range(len(df['stop_lat'])):
#        color1.append(color[i])


    

In [31]:

    

data = Data([
    Scattermapbox(
        lat=df['stop_lat'],
        lon=df['stop_lon'],
        mode='markers',
        marker=Marker(
            size=9
        ),
        text=df['stop_name'],
    )
])
layout = Layout(
    autosize=True,
    hovermode='closest',
    mapbox=dict(
        accesstoken=mapbox_access_token,
        bearing=0,
        center=dict(
            lat=40.11,
            lon=-88.23
        ),
        pitch=0,
        zoom=10
    ),
)

fig = dict(data=data, layout=layout)
py.iplot(fig, filename='Multiple Mapbox')


    

    
Out[31]:

In [ ]: