asa datathon: best buddies bus brigade

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Bus Brigade Lei Jiang, Duncan Graham, Derek Steer

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Slides from our presentation at the end of the ASA Datachon.

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Page 1: ASA Datathon: Best Buddies Bus Brigade

Bus BrigadeLei Jiang, Duncan Graham, Derek Steer

Page 2: ASA Datathon: Best Buddies Bus Brigade

Does SF public transportation underserve those in low-income communities or without cars?

Page 3: ASA Datathon: Best Buddies Bus Brigade

Bus Data from Swissnex Urban Data Challenge

• October 1-7, 2012

• Passengers getting on and off each bus at each stop

• Location of all stops and routes

Page 4: ASA Datathon: Best Buddies Bus Brigade

Methodology:

• Cleaned Bus data in SQL: limited to weekdays and commute hours (7:30-9a, 5-6:30p), calculated average loads, boarding rates, etc.

• Attached census data using Data Science Toolkit

• Correlations in Python

• Visualization in D3.js, Excel

Page 5: ASA Datathon: Best Buddies Bus Brigade

People in low-income neighborhoods own fewer cars… sort of

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Page 6: ASA Datathon: Best Buddies Bus Brigade

A bus route’s placement in a low-income area was more correlated with bus load than any

other metric we looked at

…but still not very correlated

attribute rlow income 0.37pop 18-24 0.36pop 25-64 0.36no vehicles 0.34population 0.34

density 0.14

Page 7: ASA Datathon: Best Buddies Bus Brigade

In strong examples of this correlation, it’s clear that another factor is not being accounted for

Yes, this shows all the stops on one bus route (8bx)

Page 8: ASA Datathon: Best Buddies Bus Brigade

Specific stops that fit this trend best also exhibit attributes that likely affect this correlation

TOURISTS

Page 9: ASA Datathon: Best Buddies Bus Brigade

Similarly, areas in which people do not own cars also happen to be on the way into downtown

Bus stops for which fewer than 50% of nearby households own cars

Page 10: ASA Datathon: Best Buddies Bus Brigade

The “gateway to downtown” effect is apparent in the high load in the middle of most lines

Page 11: ASA Datathon: Best Buddies Bus Brigade

The most impacted lines are the 38 and 38L, which connect downtown to the Richmond

Page 12: ASA Datathon: Best Buddies Bus Brigade

Reverse commute: people get off in clusters

Page 13: ASA Datathon: Best Buddies Bus Brigade

Reverse commute: but they get on everywhere

exception: 35, 37, 54, 28 - mass boarding 17, 54, 56 - nobody uses

Page 14: ASA Datathon: Best Buddies Bus Brigade

the evening commute: people really get on in clusters early on the line

Page 15: ASA Datathon: Best Buddies Bus Brigade

and they get off in smaller groups throughout the trip

Page 16: ASA Datathon: Best Buddies Bus Brigade

the 28: passengers really care about one stop

that’s Daly City Bart

Page 17: ASA Datathon: Best Buddies Bus Brigade

There’s a lot of activity on the South end of San Francisco relative to the number of lines

Popular stops are near other public transit

Daly City BART

Balboa Park BART

142829

Page 18: ASA Datathon: Best Buddies Bus Brigade

There could be opportunities to improve people’s ability to get to other types of public transit

Page 19: ASA Datathon: Best Buddies Bus Brigade

Isolated neighborhood lines don’t see much use

39

83x

37

66

Page 20: ASA Datathon: Best Buddies Bus Brigade

Check out the data yourself:

http://dvncan.com/buses.html

Page 21: ASA Datathon: Best Buddies Bus Brigade

Future work:

• Data Accuracy

• Understand connections between transit types (BART, Caltrain)

• Look into fewer stops for inbound lines: 30, 28, 19. For 38L, possibly run an AX or BX instead

• Look into scheduling and available buses