├── .gitignore
├── DivvyFucked
    ├── icons
    │   ├── bicycle-24@2x.png
    │   ├── harbor-18@2x.png
    │   └── prison-24@2x.png
    └── map2.html
├── README
├── src
    ├── current_data.py
    ├── collect_current_station_statuses.py
    └── generate_availability_distributions.py
└── SampleData
    ├── assortment_of_text.txt
    ├── capital_station_locations.csv
    ├── 20130818_2355.json
    ├── 20130818_2356.json
    └── 20130818_2357.json


/.gitignore:
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1 | 
2 | .DS_Store
3 | DownloadedData


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/DivvyFucked/icons/bicycle-24@2x.png:
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https://raw.githubusercontent.com/jcbozonier/DivvyData/master/DivvyFucked/icons/bicycle-24@2x.png


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/DivvyFucked/icons/harbor-18@2x.png:
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https://raw.githubusercontent.com/jcbozonier/DivvyData/master/DivvyFucked/icons/harbor-18@2x.png


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/DivvyFucked/icons/prison-24@2x.png:
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https://raw.githubusercontent.com/jcbozonier/DivvyData/master/DivvyFucked/icons/prison-24@2x.png


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/README:
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 1 | Going to do cool stuff with Divvy
 2 | 
 3 | 
 4 | 
 5 | Capital Bikeshare trip history data source:
 6 | http://www.capitalbikeshare.com/trip-history-data
 7 | 
 8 | 
 9 | Divvy minutely data source:
10 | divvybikes.com/stations/json
11 | 
12 | 
13 | Chicago Bike routes:
14 | https://data.cityofchicago.org/Transportation/Bike-Routes/3w5d-sru8
15 | 
16 | 


--------------------------------------------------------------------------------
/src/current_data.py:
--------------------------------------------------------------------------------
 1 | import urllib
 2 | import datetime
 3 | import time
 4 | import json
 5 | from boto.s3.connection import S3Connection
 6 | import sys
 7 | 
 8 | con = S3Connection('','')
 9 | dd=con.get_bucket('divvy_data')
10 | 
11 | while True:
12 |     current_file_name=datetime.datetime.now().strftime('%Y%m%d_%H%M') + '.json'
13 |     if dd.get_key(current_file_name) == None:
14 |         json_file = urllib.urlopen('http://www.divvybikes.com/stations/json')
15 |         json_text=json_file.read()
16 |         try: 
17 |             current_state = json.loads('[' + json_text + ']')[0]
18 |             key = dd.new_key(current_file_name)
19 |             key.set_contents_from_string(current_state)
20 |         except: 
21 |             print 'error', sys.exc_info()[0]
22 |     time.sleep(30)


--------------------------------------------------------------------------------
/src/collect_current_station_statuses.py:
--------------------------------------------------------------------------------
 1 | import urllib
 2 | import datetime
 3 | import os, time, socket, datetime, glob
 4 | import subprocess
 5 | 
 6 | socket.setdefaulttimeout(20)
 7 | 
 8 | def group_previous_days_files():
 9 |     print "Attempting grouping..."
10 |     print "bozo..."
11 |     todays_group = datetime.datetime.now().strftime('%Y%m%d')
12 |     print "Today's group is " + todays_group
13 |     log_filenames = [file_path for file_path in glob.glob("./DownloadedData/*.json") if not todays_group in file_path and not 'day_' in file_path]
14 |     print "Logs found: " + str(log_filenames)
15 |     for log_filename in log_filenames:
16 |         print "Grouping " + log_filename
17 |         base_log_filename = os.path.basename(log_filename)
18 |         the_date = base_log_filename.split('_')[0]
19 |         grouped_file_path = data_folder + 'day_' + the_date + '.json'
20 |         with open(grouped_file_path, 'a') as day_file:
21 |             with open(log_filename, 'r') as minute_file:
22 |                 minute_text = minute_file.read()
23 |                 day_file.write(minute_text)
24 |         print "Removing " + log_filename
25 |         os.remove(log_filename)
26 |     #subprocess.call(['s3cmd', 'sync', './DownloadedData/day_*.json', 's3://bozo-divvy/day-log/'])
27 |     os.system('s3cmd sync ./DownloadedData/day_*.json s3://bozo-divvy/day-log/')
28 |     print "Done uploading to S3"
29 |     for day_file in glob.glob('./DownloadedData/day_*.json'):
30 |         os.remove(day_file)
31 | 
32 | data_folder = './DownloadedData/'
33 | while True:
34 |     current_file_name = datetime.datetime.now().strftime('%Y%m%d_%H%M') + '.json'
35 |     current_file_path = data_folder + current_file_name
36 |     if not os.path.exists(current_file_path):
37 |         print "Downloading file... then sleeping."
38 |         try:
39 |             urllib.urlretrieve ("http://divvybikes.com/stations/json", current_file_path)
40 |         except:
41 |              time.sleep(3)
42 |              continue
43 |         group_previous_days_files()
44 |     else:
45 |         print "File already exists. Sleeping"
46 |     time.sleep(30)
47 | 


--------------------------------------------------------------------------------
/SampleData/assortment_of_text.txt:
--------------------------------------------------------------------------------
 1 | 
 2 | 
 3 | create table trip_data (Duration text,Start_time text,Start_Station text,Start_terminal integer,End_date text,End_Station text, End_terminal integer, Bike_num text, Subscription_Type text);
 4 | .separator ","
 5 | .import 2013-2nd-quarter.csv trip_data
 6 | delete from trip_data where Duration='Duration';
 7 | .headers ON
 8 | 
 9 | create view bike_stats as select Bike_num, min(date(Start_time)) first_service_day, max(date(Start_time)) last_service_day, count(distinct date(Start_time)) days_in_service, (julianday(max(date(Start_time))) - julianday(min(date(Start_time))))+1-count(distinct date(Start_time)) days_not_in_service, count(start_time) trips, count(case when Subscription_type like('Subscriber') then start_time else null end) subscriber_trips from trip_data group by 1 limit 20;
10 | 
11 | create view start_station_stats as select Start_Station, Start_terminal, count(1) as trips_started, count( case when Subscription_Type="Subscriber" then 1 else null end) subscriber_trips_started, count( case when Subscription_Type="Casual" then 1 else null end) casual_trips_started  from trip_data group by 1,2 ;
12 | 
13 | create view end_station_stats as select End_Station, End_terminal, count(1) as trips_ended, count( case when Subscription_Type="Subscriber" then 1 else null end) subscriber_trips_ended, count( case when Subscription_Type="Casual" then 1 else null end) casual_trips_ended  from trip_data group by 1,2 ;
14 | 
15 | 
16 | create table stations (name text, terminalname integer, lat real, long real);
17 | .separator ","
18 | .import capital_station_locations.csv stations
19 | delete from stations where name=’name’;
20 | 
21 | create view station_stats as
22 | select
23 | 
24 | Start_Station station, Start_terminal terminal, trips_started, subscriber_trips_started, casual_trips_started, trips_ended, subscriber_trips_ended, casual_trips_ended
25 | from start_station_stats a 
26 | join end_station_stats b
27 | on a.Start_terminal=b.End_terminal
28 | join 
29 | 
30 | 
31 | select * from trip_data a join trip_data b on Start_terminal = End_terminal;
32 | 
33 | 
34 | 
35 | select (strftime('%s',end_date)-strftime('%s',start_time))/60, count(1) from trip_data group by 1 limit 50;
36 | 
37 | 
38 | 
39 | create view pairwise_trips as 
40 | select start_terminal, 
41 | end_terminal, 
42 | start_terminal || end_terminal pathname, 
43 | start.lat start_lat,
44 |  start.long start_long, 
45 | end.lat end_lat,
46 | end.long end_long,
47 | count(1) trips
48 | from trip_data td 
49 | join stations start on td.start_terminal = start.terminalname 
50 | join stations end on end_terminal = end.terminalname
51 | group by 1,2,3,4,5,6,7;
52 | 
53 | 
54 | 
55 | .mode csv
56 | .output out.csv
57 | 
58 | select start_terminal terminal, pathname, '1' pathorder, start_lat lat, start_long long, trips from pairwise_trips
59 | UNION
60 | select end_terminal terminal, pathname, '2' pathorder, end_lat lat, end_long long, trips from pairwise_trips;
61 | 
62 | 
63 | 
64 | 
65 | 
66 | 
67 | 
68 | 
69 | import bs4
70 |  f=open('bikeStations.xml','r')
71 | x =bs4.BeautifulSoup(f)
72 | 
73 | table = []
74 | table.append(['name','terminalname','lat','long'])
75 | for e in x('station'):
76 |     table.append([e('name')[0].text,e.terminalname.text,e.lat.text,e.long.text])
77 | 
78 | import csv
79 | f= open('capital_station_locations.csv','wb'
80 | writer = csv.writer(f)
81 | writer.writerows(table)
82 | 
83 | 
84 | 
85 | http://kb.tableausoftware.com/articles/knowledgebase/using-path-shelf-pattern-analysis
86 | 


--------------------------------------------------------------------------------
/src/generate_availability_distributions.py:
--------------------------------------------------------------------------------
  1 | import json
  2 | import glob
  3 | import csv
  4 | import datetime
  5 | 
  6 | counter = 0
  7 | stations = {}
  8 | for file_path in glob.glob("../LargeSampleData/DivvyDataSample/*.json"):
  9 | 	counter += 1
 10 | 	#if counter > 1440:
 11 | 	#	break
 12 | 	print "Processing " + file_path + "..."
 13 | 	json_file = open(file_path)
 14 | 	json_text = json_file.read().replace(" u'", "'").replace("{u'", "{'").replace("'", "\"").replace(": None", ": \"\"").replace(": False", ": 0").replace(": True", ": 1")
 15 | 	try:
 16 | 		minute_data = json.loads(json_text)
 17 | 	except:
 18 | 		print "Errored on " + file_path
 19 | 		continue
 20 | 	time_text = minute_data['executionTime']
 21 | 	event_time = datetime.datetime.strptime(time_text, '%Y-%m-%d %I:%M:%S %p')
 22 | 	events = minute_data['stationBeanList']
 23 | 	for event in events:
 24 | 		station_id = event["id"]
 25 | 		weekend = event_time.weekday() >= 5
 26 | 		hour = event_time.hour
 27 | 		key = (station_id, weekend, hour)
 28 | 		if not key in stations:
 29 | 			stations[key] = {
 30 | 				'id': station_id,
 31 | 				'available_docks': [0]*55,
 32 | 				'available_bikes': [0]*55
 33 | 			}
 34 | 		station_info = stations[key]
 35 | 		station_info['available_bikes'][event['availableBikes']] += 1
 36 | 		station_info['available_docks'][event['availableDocks']] += 1
 37 | 
 38 | available_bikes_by_station = {}
 39 | available_docks_by_station = {}
 40 | 
 41 | for key in stations.keys():
 42 | 	station_id = key[0]
 43 | 	hour = key[2]
 44 | 	if not station_id in available_bikes_by_station:
 45 | 		available_bikes_by_station[station_id] = [[0]*55 for i in range(0,24)]
 46 | 	if not station_id in available_docks_by_station:
 47 | 		available_docks_by_station[station_id] = [[0]*55 for i in range(0,24)]
 48 | 
 49 | 	available_bikes_by_station[station_id][hour] = map(lambda le_tuple: le_tuple[0] + le_tuple[1], zip(available_bikes_by_station[station_id][hour], stations[key]['available_bikes']))
 50 | 	available_docks_by_station[station_id][hour] = map(lambda le_tuple: le_tuple[0] + le_tuple[1], zip(available_docks_by_station[station_id][hour], stations[key]['available_docks']))
 51 | station_bikes = []
 52 | station_docks = []
 53 | for station_id in available_bikes_by_station.keys():
 54 | 	bike_available_hours = available_bikes_by_station[station_id]
 55 | 	dock_available_hours = available_docks_by_station[station_id]
 56 | 	for hour in xrange(0,24):
 57 | 		bike_available_distribution = bike_available_hours[hour]
 58 | 		dock_available_distribution = dock_available_hours[hour]
 59 | 		hours_for_bikes_normalized = [round((1.0*i)/sum(bike_available_distribution), 6) if sum(bike_available_distribution) != 0 else 0 for i in bike_available_distribution]
 60 | 		station_bikes_hour = [station_id, hour]
 61 | 		station_bikes_hour.extend(hours_for_bikes_normalized)
 62 | 		station_bikes.append(station_bikes_hour)
 63 | 		hours_for_docks_normalized = [round((1.0*i)/sum(dock_available_distribution), 6) if sum(dock_available_distribution) != 0 else 0 for i in dock_available_distribution]
 64 | 		station_docks_hour = [station_id, hour]
 65 | 		station_docks_hour.extend(hours_for_docks_normalized)
 66 | 		station_docks.append(station_docks_hour)
 67 | 
 68 | def convert_to_andys_religion(raw_data):
 69 | 	andys_fantasy_data = {}
 70 | 	for row in raw_data:
 71 | 		the_hour = row[1]
 72 | 		if not the_hour in andys_fantasy_data:
 73 | 			andys_fantasy_data[the_hour] = {
 74 | 				'hour': the_hour,
 75 | 				'stations': []
 76 | 			}
 77 | 		stations_for_hour = andys_fantasy_data[the_hour]['stations']
 78 | 		stations_for_hour.append({
 79 | 				'station_id': row[0],
 80 | 				'availability': row[2:]
 81 | 			})
 82 | 	return andys_fantasy_data
 83 | 
 84 | 
 85 | ideal_dock_format = convert_to_andys_religion(station_docks)
 86 | ideal_bike_format = convert_to_andys_religion(station_bikes)
 87 | 
 88 | date_text = datetime.datetime.now().strftime("%Y_%m_%d")
 89 | with open('dock_availability_' + date_text + '.json', 'w') as f: 
 90 | 	json.dump(ideal_dock_format, f)
 91 | with open('bike_availability_' + date_text + '.json', 'w') as f: 
 92 | 	json.dump(ideal_bike_format, f)
 93 | 
 94 | #with open('bike_availability_by_station_hour.csv', 'w') as f: 
 95 | #	writer = csv.writer(f)
 96 | #	writer.writerows(station_bikes)
 97 | #with open('bike_availability_by_station_hour.json', 'w') as f: 
 98 | #	json.dump(station_bikes, f)
 99 | #with open('dock_availability_by_station_hour.json', 'w') as f: 
100 | #	json.dump(station_docks, f)
101 | 
102 | #station_info_for_csv = [{'station_id': item[0][0], 'weekend': item[0][1], 'hour':item[0][2], 'available_bikes':item[1]['available_bikes'], 'available_docks':item[1]['available_docks']} for item in stations.items()]
103 | 
104 | #with open('station_distributions.csv', 'wb+') as f: 
105 | #	writer = csv.DictWriter(f, ['station_id', 'weekend', 'hour', 'available_bikes', 'available_docks'])
106 | #	writer.writeheader()
107 | #	writer.writerows(station_info_for_csv)
108 | 
109 | 
110 | 


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/DivvyFucked/map2.html:
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  1 | <head>
  2 |  <link rel="stylesheet" href="http://cdn.leafletjs.com/leaflet-0.6.4/leaflet.css" />
  3 |  <script src="http://cdn.leafletjs.com/leaflet-0.6.4/leaflet.js"></script> 
  4 |   <script src="./jquery.js"></script>
  5 | </head>
  6 | 
  7 | <style type="text/css">
  8 | 
  9 | </style>
 10 | <body>
 11 |  <div id="map" style="height:100%"></div>
 12 | 
 13 | <script>
 14 | 
 15 | 
 16 | var to_radians = function(number){
 17 |       return number * Math.PI / 180;
 18 |     };
 19 | var haversineDistance = function(pointA, pointB){
 20 |   var lat1 = pointA.latitude;
 21 |   var lon1 = pointA.longitude;
 22 |   var lat2 = pointB.latitude;
 23 |   var lon2 = pointB.longitude;
 24 |   var R = 3959;
 25 |   // In miles
 26 |   var dLat = to_radians(lat2 - lat1);
 27 |   var dLon = to_radians(lon2 - lon1);
 28 |   lat1 = to_radians(lat1);
 29 |   lat2 = to_radians(lat2);
 30 | 
 31 |   var a = Math.sin(dLat / 2) * Math.sin(dLat / 2) + Math.sin(dLon / 2) * Math.sin(dLon / 2) * Math.cos(lat1) * Math.cos(lat2);
 32 |   var c = 2 * Math.asin(Math.sqrt(a));
 33 |   return R * c;
 34 | };
 35 | 
 36 |  var taxiDistance = function(pointA, pointB){
 37 |   return (
 38 |     haversineDistance({'latitude':pointA.latitude  ,'longitude':pointA.longitude},
 39 |     {'latitude':pointA.latitude  ,'longitude':pointB.longitude}) +
 40 |     haversineDistance({'latitude':pointA.latitude  ,'longitude':pointB.longitude},
 41 |     {'latitude':pointB.latitude  ,'longitude':pointB.longitude})
 42 |     )
 43 | };
 44 | 
 45 | var compromiseDistance = function(pointA, pointB){
 46 |   return (haversineDistance(pointA, pointB) + taxiDistance(pointA, pointB))/2
 47 | };
 48 | console.log('wtf');
 49 | 
 50 | var getProb = function(id,table){
 51 | console.log(table)
 52 | }
 53 | 
 54 | var bikeIcon = L.icon({iconUrl:'icons/bicycle-24@2x.png',iconAnchor:   [22, 1],});
 55 | var dockIcon = L.icon({iconUrl:'icons/harbor-18@2x.png',iconAnchor:   [22, 1],});
 56 | 
 57 | $.getJSON('http://anyorigin.com/get?url=http%3A//divvybikes.com/stations/json&callback=?', function(data)      {
 58 | $.getJSON('http://0.0.0.0:8000/dock_availability_by_station_hour.json',function(prior_dock_data){
 59 | $.getJSON('http://0.0.0.0:8000/bike_availability_by_station_hour.json',function(prior_bike_data){
 60 | divvy_data = data.contents;
 61 | var stations = divvy_data.stationBeanList;
 62 | 
 63 | var map = L.map('map').setView([41.883173,-87.631227], 13);
 64 | 
 65 | L.tileLayer('http://otile1.mqcdn.com/tiles/1.0.0/osm/{z}/{x}/{y}.png', {
 66 |     attribution: '&copy; <a href="http://osm.org/copyright">OpenStreetMap</a> contributors| <a href = "https://data.cityofchicago.org/Health-Human-Services/Food-Inspections/4ijn-s7e5">Chicago Data Portal</a> |<a href="http://www.mapquest.com/" target="_blank">MapQuest</a> <img src="http://developer.mapquest.com/content/osm/mq_logo.png">'
 67 | }).addTo(map);
 68 | 
 69 | var user_marker=L.marker([41.883173,-87.631227]).addTo(map);
 70 | user_marker.bindPopup('Please Provide Your Location').openPopup();
 71 | 
 72 | map.locate({setView:true,maxZoom:16});
 73 | 
 74 | map.on('locationfound',onLocate);
 75 | map.on('locationerror',onLocateError);
 76 | 
 77 | function onLocateError(e){
 78 | console.log('locaterror');
 79 | user_marker.setLatLng([41.841186,-87.64217]).addTo(map);
 80 | user_marker.bindPopup('Default').openPopup();
 81 | console.log(user_marker.getLatLng());
 82 | map.setView([user_marker.getLatLng().lat,user_marker.getLatLng().lng],13);
 83 | var miles;
 84 | 
 85 |     for(s in stations){
 86 |         miles=compromiseDistance({'latitude':user_marker.getLatLng().lat,'longitude':user_marker.getLatLng().lng},stations[s]); 
 87 |         if(miles<.5 && stations[s].availableBikes>0){
 88 |           L.marker([stations[s].latitude,stations[s].longitude],{icon: bikeIcon}).addTo(map).bindPopup(stations[s].stationName);
 89 |         }
 90 |         else if((miles>1.5 && miles<3)&&stations[s].availableDocks>0){
 91 |           L.marker([stations[s].latitude,stations[s].longitude],{icon: dockIcon}).addTo(map).bindPopup(stations[s].stationName);
 92 |         }
 93 |         
 94 |     }
 95 | }
 96 | 
 97 | function onLocate(e) {
 98 | console.log('locate');
 99 | user_marker.setLatLng(e.latlng).addTo(map);
100 | user_marker.bindPopup('Your Location').openPopup();
101 | var miles;
102 | 
103 |     for(s in stations){
104 |         miles=compromiseDistance({'latitude':user_marker.getLatLng().lat,'longitude':user_marker.getLatLng().lng},stations[s]); 
105 |         console.log(getProb(stations[s].id,prior_bike_data));
106 |         if(miles<.5 && stations[s].availableBikes>0){
107 |           L.marker([stations[s].latitude,stations[s].longitude],{icon: bikeIcon}).addTo(map).bindPopup(stations[s].stationName+'<br>'+'Bikes: '+stations[s].availableBikes);
108 |         }
109 |         else if((miles>1.0 && miles<5)&&stations[s].availableDocks>0){
110 |           L.marker([stations[s].latitude,stations[s].longitude],{icon: dockIcon}).addTo(map).bindPopup(stations[s].stationName+'<br>'+'Docks: '+stations[s].availableDocks);
111 |         }
112 |         
113 |     }
114 | }
115 | 
116 | });
117 | });
118 | });
119 | /*
120 | for(r in i){
121 |     var i_date = new Date(i[r].inspection_date);
122 |     if(dba_name==i[r].dba_name){
123 |     text=text+"<br>"+i_date.toJSON().substring(0,10)+" "+i[r].results
124 |     }
125 |     else
126 |     {
127 |     dba_name=i[r].dba_name
128 |     text=(i_date.toJSON().substring(0,10))+" "+i[r].results
129 |     }
130 |     L.marker([i[r].latitude,i[r].longitude]).addTo(map).bindPopup(dba_name+"<br>"+text);
131 |     } 
132 |  */
133 | 
134 | 
135 | 
136 | </script>
137 | </body>
138 | 
139 | 


--------------------------------------------------------------------------------
/SampleData/capital_station_locations.csv:
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  1 | name,terminalname,lat,long
  2 | 20th & Bell St,31000,38.8561,-77.0512
  3 | 18th & Eads St.,31001,38.85725,-77.05332
  4 | 20th & Crystal Dr,31002,38.8564,-77.0492
  5 | 15th & Crystal Dr,31003,38.860244,-77.050276
  6 | 18th & Hayes St,31004,38.8573,-77.0574
  7 | 15th & Hayes St,31005,38.8604,-77.0603
  8 | S Joyce & Army Navy Dr,31006,38.8637,-77.0633
  9 | Crystal City Metro / 18th & Bell St,31007,38.8573,-77.0511
 10 | 12th & Army Navy Dr,31008,38.8629,-77.0528
 11 | 27th & Crystal Dr,31009,38.848441,-77.051516
 12 | S Glebe & Potomac Ave,31010,38.8426,-77.0502
 13 | 23rd & Crystal Dr,31011,38.8533,-77.0498
 14 | 26th & Crystal Dr,31012,38.8518,-77.0498
 15 | 19th St & Pennsylvania Ave NW,31100,38.9003,-77.0429
 16 | 14th & V St NW,31101,38.9176,-77.0321
 17 | 11th & Kenyon St NW,31102,38.929464,-77.027822
 18 | 16th & Harvard St NW,31103,38.926088,-77.036536
 19 | Adams Mill & Columbia Rd NW,31104,38.922925,-77.042581
 20 | 14th & Harvard St NW,31105,38.9268,-77.0322
 21 | Calvert St & Woodley Pl NW,31106,38.9236,-77.0501
 22 | Lamont & Mt Pleasant NW,31107,38.9319,-77.0388
 23 | 4th & M St SW,31108,38.8767,-77.0178
 24 | 15th & P St NW,31201,38.90985,-77.034438
 25 | 14th & R St NW,31202,38.912682,-77.031681
 26 | 14th & Rhode Island Ave NW,31203,38.9086,-77.0323
 27 | 20th & E St NW,31204,38.8963,-77.045
 28 | 21st & I St NW,31205,38.9008,-77.047
 29 | Georgia & New Hampshire Ave NW,31400,38.936043,-77.024649
 30 | 14th St & Spring Rd NW,31401,38.9375,-77.0328
 31 | John McCormack Dr & Michigan Ave NE,31502,38.9346,-76.9955
 32 | 5th & K St NW,31600,38.90304,-77.019027
 33 | 19th & East Capitol St SE,31601,38.8896,-76.9769
 34 | Park Rd & Holmead Pl NW,31602,38.9308,-77.0315
 35 | Good Hope & Naylor Rd SE,31700,38.8601,-76.9672
 36 | Connecticut Ave & Newark St NW / Cleveland Park,31305,38.934267,-77.057979
 37 | Randle Circle & Minnesota Ave SE,31702,38.878,-76.9607
 38 | Minnesota Ave Metro/DOES,31703,38.897063,-76.947446
 39 | Nannie Helen Burroughs & Minnesota Ave NE,31704,38.9016,-76.9422
 40 | Anacostia Metro,31801,38.8624,-76.9949
 41 | Good Hope Rd & MLK Ave SE,31802,38.867373,-76.988039
 42 | 19th & E Street NW,31206,38.8952,-77.0436
 43 | 4th St & Rhode Island Ave NE,31500,38.919488,-77.000624
 44 | 10th & U St NW,31111,38.9172,-77.0259
 45 | Georgia Ave and Fairmont St NW,31207,38.9249,-77.0222
 46 | 1st & N St  SE,31209,38.8743,-77.0057
 47 | 20th St & Florida Ave NW,31110,38.9154,-77.0446
 48 | 7th & T St NW,31109,38.9155,-77.0222
 49 | 23rd & Eads St,31013,38.853613,-77.053535
 50 | M St & New Jersey Ave SE,31208,38.8763,-77.0037
 51 | Massachusetts Ave & Dupont Circle NW,31200,38.9101,-77.0444
 52 | 1st & M St NE,31603,38.9057,-77.0056
 53 | 21st & M St NW,31212,38.9054,-77.0471
 54 | 17th & K St NW,31213,38.90276,-77.03863
 55 | 4th St & Massachusetts Ave NW,31604,38.9003,-77.016
 56 | 3rd & D St SE,31605,38.8851,-77.0023
 57 | Potomac & Pennsylvania Ave SE,31606,38.8803,-76.9862
 58 | 14th & D St SE,31607,38.884,-76.9861
 59 | 17th & Corcoran St NW,31214,38.9121,-77.0387
 60 | Van Ness Metro / UDC,31300,38.944551,-77.063896
 61 | Florida Ave & R St NW,31503,38.9126,-77.0135
 62 | 8th & Eye St SE / Barracks Row,31608,38.8792,-76.9953
 63 | Ward Circle / American University,31301,38.938736,-77.087171
 64 | Idaho Ave & Newark St NW [on 2nd District patio],31302,38.934751,-77.074647
 65 | 14th St Heights / 14th & Crittenden St NW,31402,38.947774,-77.032818
 66 | Anacostia Library,31804,38.865784,-76.9784
 67 | Pennsylvania & Minnesota Ave SE,31805,38.873057,-76.971015
 68 | Eastern Market / 7th & North Carolina Ave SE,31610,38.886952,-76.996806
 69 | McPherson Square / 14th & H St NW,31216,38.899641,-77.032005
 70 | Benning Branch Library,31705,38.894,-76.947974
 71 | USDA / 12th & Independence Ave SW,31217,38.887237,-77.028226
 72 | Georgetown Harbor / 30th St NW,31215,38.9022212,-77.059219
 73 | 12th & Newton St NE,31501,38.933668,-76.991016
 74 | US Dept of State / Virginia Ave & 21st St NW,31220,38.894919,-77.046587
 75 | L'Enfant Plaza / 7th & C St SW,31218,38.886266,-77.022241
 76 | 10th St & Constitution Ave NW,31219,38.893028,-77.026013
 77 | Kennedy Center,31211,38.895184,-77.054845
 78 | Eastern Market Metro / Pennsylvania Ave & 7th St SE,31613,38.884,-76.995397
 79 | 18th & M St NW,31221,38.904742,-77.041606
 80 | Tenleytown / Wisconsin Ave & Albemarle St NW,31303,38.947607,-77.079382
 81 | 13th & H St NE,31611,38.9003,-76.9882
 82 | 5th & F St NW,31620,38.897222,-77.019347
 83 | New York Ave & 15th St NW,31222,38.8991,-77.0337
 84 | Convention Center / 7th & M St NW,31223,38.90572,-77.022264
 85 | Harvard St & Adams Mill Rd NW,31112,38.927872,-77.043358
 86 | 19th & L St NW,31224,38.903407,-77.043648
 87 | C & O Canal & Wisconsin Ave NW,31225,38.90375,-77.06269
 88 | 7th & Water St SW / SW Waterfront,31609,38.878925,-77.024016
 89 | D St & Maryland Ave NE,31612,38.894758,-76.997114
 90 | 34th St & Wisconsin Ave NW,31226,38.916442,-77.0682
 91 | 13th St & New York Ave NW,31227,38.900283,-77.029822
 92 | 8th & H St NW,31228,38.8997,-77.023086
 93 | 10th & Monroe St NE,31504,38.932514,-76.992889
 94 | Eckington Pl & Q St NE,31505,38.910972,-77.00495
 95 | 6th & H St NE,31615,38.900384,-76.99831
 96 | 3rd & H St NE,31616,38.90002,-77.002166
 97 | Bladensburg Rd & Benning Rd NE,31617,38.900413,-76.982872
 98 | 4th & East Capitol St NE,31618,38.889955,-77.000349
 99 | Lincoln Park / 13th & East Capitol St NE ,31619,38.890461,-76.988355
100 | Branch & Pennsylvania Ave SE,31701,38.8692,-76.9599
101 | 13th & D St NE,31622,38.894832,-76.987633
102 | New Hampshire Ave & T St NW,31229,38.91554,-77.03818
103 | Metro Center / 12th & G St NW,31230,38.898364,-77.027869
104 | 14th & D St NW / Ronald Reagan Building,31231,38.894514,-77.031617
105 | 7th & F St NW / National Portrait Gallery,31232,38.897324,-77.022322
106 | 17th & K St NW / Farragut Square,31233,38.902061,-77.038322
107 | 20th & O St NW / Dupont South,31234,38.908905,-77.04478
108 | 4th & D St NW / Judiciary Square,31621,38.895344,-77.016106
109 | 19th St & Constitution Ave NW,31235,38.8923,-77.0436
110 | 37th & O St NW / Georgetown University,31236,38.90774,-77.071652
111 | 11th & H St NE,31614,38.899983,-76.991383
112 | 25th St & Pennsylvania Ave NW,31237,38.903827,-77.053485
113 | Columbus Circle / Union Station,31623,38.89696,-77.00493
114 | North Capitol St & F St NW,31624,38.897446,-77.009888
115 | 11th & M St NW,31266,38.905607,-77.027137
116 | 36th & Calvert St NW / Glover Park,31304,38.922581,-77.070334
117 | 14th & G St NW,31238,38.898069,-77.031823
118 | Potomac Ave & 35th St S,31052,38.844015,-77.050537
119 | Ohio Dr & West Basin Dr SW / MLK & FDR Memorials,31240,38.88412,-77.04657
120 | 11th & F St NW,31262,38.897857,-77.026975
121 | 23rd & E St NW ,31260,38.896104,-77.049882
122 | Lynn & 19th St North,31014,38.897315,-77.070993
123 | Rosslyn Metro / Wilson Blvd & Ft Myer Dr,31015,38.8946,-77.072305
124 | Clarendon Blvd & Pierce St,31016,38.893648,-77.076701
125 | Court House Metro / Wilson Blvd & N Uhle St,31017,38.891696,-77.0846
126 | N Rhodes & 16th St N,31018,38.892164,-77.079375
127 | Fairfax Village,31706,38.86559,-76.952103
128 | 21st St & Constitution Ave NW,31261,38.892459,-77.046567
129 | Wilson Blvd & N Edgewood St,31019,38.889,-77.0925
130 | Columbia Rd & Belmont St NW,31113,38.920669,-77.04368
131 | 17th & Rhode Island Ave NW,31239,38.906602,-77.038785
132 | Thomas Circle,31241,38.9059,-77.0325
133 | Wilson Blvd & Franklin Rd,31020,38.8904,-77.0889
134 | Clarendon Blvd & N Fillmore St,31021,38.8881,-77.09308
135 | Clarendon Metro / Wilson Blvd & N Highland St,31022,38.88786,-77.094875
136 | 18th St & Pennsylvania Ave NW,31242,38.89968,-77.041539
137 | Maryland & Independence Ave SW,31243,38.887299,-77.018939
138 | 4th & E St SW,31244,38.88412,-77.017445
139 | 3rd & G St SE,31625,38.881185,-77.001828
140 | 7th & R St NW / Shaw Library,31245,38.912719,-77.022155
141 | 9th & Upshur St NW,31404,38.9418,-77.0251
142 | 1st & Rhode Island Ave NW,31506,38.915417,-77.012289
143 | Columbia Rd & Georgia Ave NW,31115,38.928156,-77.02344
144 | California St & Florida Ave NW,31116,38.917761,-77.04062
145 | Benning Rd & East Capitol St NE / Benning Rd Metro,31707,38.889935,-76.93723
146 | 3000 Connecticut Ave NW / National Zoo,31307,38.930282,-77.055599
147 | Anacostia Ave & Benning Rd NE / River Terrace ,31708,38.896544,-76.96012
148 | M St & Pennsylvania Ave NW,31246,38.905126,-77.056887
149 | 15th St & Massachusetts Ave SE,31626,38.88732,-76.983569
150 | Congress Heights Metro,31806,38.844711,-76.987823
151 | N Quincy St & Glebe Rd,31035,38.876393,-77.107735
152 | Wilson Blvd & N Oakland St,31033,38.8815,-77.10396
153 | N Veitch  & 20th St N,31029,38.896923,-77.086502
154 | 11th & K St NW,31263,38.90268,-77.02674
155 | Fairfax Dr & Wilson Blvd,31023,38.885801,-77.097745
156 | Key Blvd & N Quinn St,31027,38.896015,-77.078107
157 | 1st & K St SE,31628,38.87861,-77.006004
158 | 39th & Calvert St NW / Stoddert,31306,38.922649,-77.077271
159 | 1st & Washington Hospital Center NW,31507,38.928743,-77.012457
160 | Virginia Square Metro / N Monroe St & 9th St N,31024,38.882788,-77.103148
161 | Central Library / N Quincy St & 10th St N,31025,38.88397,-77.10783
162 | Washington Blvd & 10th St N,31026,38.884734,-77.093485
163 | Jefferson Dr & 14th St SW,31247,38.888553,-77.032429
164 | Smithsonian / Jefferson Dr & 12th St SW,31248,38.888767,-77.02858
165 | George Mason Dr & Wilson Blvd,31036,38.87887,-77.1207
166 | 6th St & Indiana Ave NW,31264,38.894573,-77.01994
167 | N Veitch & Key Blvd,31028,38.893241,-77.086045
168 | N Adams St & Lee Hwy,31030,38.89593,-77.089006
169 | 15th & N Scott St,31031,38.89054,-77.08095
170 | Washington Blvd & 7th St N,31032,38.880834,-77.091129
171 | Ballston Metro / N Stuart & 9th St N,31037,38.881044,-77.111768
172 | N Randolph St & Fairfax Dr,31034,38.882629,-77.109366
173 | Jefferson Memorial,31249,38.879819,-77.037413
174 | Good Hope Rd & 14th St SE,31803,38.866611,-76.985238
175 | Glebe Rd & 11th St N,31038,38.883921,-77.116817
176 | N Quincy St & Wilson Blvd,31039,38.880151,-77.107673
177 | Fairfax Dr & Kenmore St,31040,38.884616,-77.10108
178 | Gallaudet / 8th St & Florida Ave NE,31508,38.90509,-76.9941
179 | 20th & L St NW,31250,38.903584,-77.044789
180 | 12th & L St NW,31251,38.903819,-77.0284
181 | 21st St & Pennsylvania Ave NW,31252,38.901539,-77.046564
182 | 19th & K St NW,31253,38.902204,-77.04337
183 | Prince St & Union St,31041,38.803124,-77.040363
184 | Market Square / King St & Royal St,31042,38.804718,-77.043363
185 | Saint Asaph St & Pendleton  St,31043,38.810743,-77.044664
186 | King St & Patrick St,31044,38.805317,-77.049883
187 | 15th & K St NW,31254,38.902,-77.03353
188 | Commerce St & Fayette St,31045,38.805648,-77.05293
189 | Henry St & Pendleton St,31046,38.811456,-77.050276
190 | Braddock Rd Metro,31047,38.814577,-77.052808
191 | King St Metro,31048,38.805767,-77.06072
192 | 24th & N St NW,31255,38.9066,-77.05152
193 | 10th & E St NW,31256,38.895914,-77.026064
194 | 22nd & I St NW / Foggy Bottom,31257,38.90088,-77.048911
195 | Utah St & 11th St N ,31049,38.883669,-77.113905
196 | Barton St & 10th St N,31050,38.884961,-77.08777
197 | Arlington Blvd & N Queen St,31051,38.889365,-77.077294
198 | Lincoln Memorial,31258,38.888251,-77.049426
199 | 20th St & Virginia Ave NW,31259,38.894722,-77.045128
200 | 5th St & Massachusetts Ave NW,31265,38.90093,-77.018677
201 | 39th & Veazey St NW,31308,38.943837,-77.077078
202 | Fessenden St & Wisconsin Ave NW,31309,38.954812,-77.082426
203 | M St & Delaware Ave NE,31627,38.905707,-77.003041
204 | Columbia Pike & S Courthouse Rd,31053,38.863833,-77.080319
205 | Walter Reed Community Center / Walter Reed Dr & 16th St S,31054,38.857803,-77.086733
206 | 28th St S & S Meade St,31055,38.846222,-77.069275
207 | 18th St & Wyoming Ave NW,31114,38.918809,-77.041571
208 | 5th & Kennedy St NW,31403,38.956595,-77.019815
209 | Georgia Ave & Emerson St NW,31405,38.949662,-77.027333
210 | 14th & Upshur St NW,31406,38.942016,-77.032652
211 | 14th St & Colorado Ave NW,31407,38.956432,-77.032947
212 | S Troy St & 26th St S,31056,38.847977,-77.075104
213 | S Four Mile Run Dr & S Shirlington Rd,31057,38.8444,-77.085931
214 | S Oakland St & Columbia Pike,31058,38.860789,-77.09586
215 | S Abingdon St & 36th St S,31059,38.835213,-77.094295
216 | S Arlington Mill Dr & Campbell Ave,31060,38.84232,-77.089555
217 | S Kenmore & 24th St S,31061,38.848454,-77.084918
218 | Connecticut Ave & Yuma St NW,31311,38.947175,-77.065131
219 | Wisconsin Ave & O St NW,31312,38.90849,-77.063586
220 | S George Mason Dr & 13th St S,31062,38.854691,-77.100555
221 | Connecticut & Nebraska Ave NW,31310,38.955016,-77.069956
222 | 17th St & Massachusetts Ave NW,31267,38.908142,-77.038359
223 | 15th & Euclid St  NW,31117,38.92333,-77.0352
224 | 8th & East Capitol St NE,31629,38.889988,-76.995193
225 | New Jersey Ave & R St NW,31509,38.912659,-77.017669
226 | 15th & East Capitol St NE,31630,38.889908,-76.983326
227 | 8th & F St NE,31631,38.897274,-76.994749
228 | 18th St & Rhode Island Ave NE,31510,38.927095,-76.978924
229 | 15th & F St NE,31632,38.897195,-76.983575
230 | 12th & Irving St NE,31511,38.928644,-76.990955
231 | 34th St & Minnesota Ave SE,31709,38.884085,-76.957461
232 | Alabama & MLK Ave SE,31800,38.843222,-76.999388
233 | Pleasant St & MLK Ave SE,31807,38.863897,-76.990037
234 | Neal St & Trinidad Ave NE,31512,38.903732,-76.987211
235 | 13th & U St NW,31268,38.916794,-77.029779
236 | S George Mason Dr & Four Mile Run,31063,38.852248,-77.105022
237 | S Stafford & 34th St S,31064,38.834108,-77.087323
238 | N Pershing Dr & Wayne St,31065,38.880705,-77.08596
239 | Columbia Pike & S Orme St,31066,38.867262,-77.072315
240 | 3rd St & Pennsylvania Ave SE,31269,38.887378,-77.001955
241 | 8th & D St NW,31270,38.894851,-77.02324
242 | 3rd & Elm St NW,31118,38.917622,-77.01597
243 | Rhode Island Ave & V St NE,31513,38.918155,-77.004746
244 | Constitution Ave & 2nd St NW/DOL,31271,38.892275,-77.013917
245 | Washington & Independence Ave SW/HHS,31272,38.88731,-77.01397
246 | Independence Ave & L'Enfant Plaza SW/DOE,31633,38.887397,-77.026154
247 | 


--------------------------------------------------------------------------------
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