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README.md

San Francisco Housing Pipeline Project

Having a shared interest with stakeholders in creating a more inclusive San Francisco through enabling accessible housing, we use Data Science to understand the facts and predict the potential impact of housing policy. We are not partisan or political.

Living Project Document

This is a project of the Data Science Working Group at Code for San Francisco. slack: #datasci-housingreport

SF Brigade Team

(Team, please keep your level of desired involvement up to date here)

Name Slack Handle Role RACI
Clare Corthell @clare Lead, Product Manager Responsible
Jason Kalmeida @jasonkalmeida ? ?
Vijai Narayanan @VijaiNarayanan ? ?
Rahele Tesfu @? Asso. Product Manager ?
Adam Szabunio @? Data Scientist ?
Sanat Moningi @sanat DSWG Founder Informed
Brian Goggin @bgoggin - inactive
Jeff Quinn @jfquinn - inactive
Arash Aghevli @aaghevli - inactive
Tyler Field @tyler - inactive
Earl Dos Santos @earldossantos - inactive
Juan Carlos Collins @juancarlos - inactive
Alwyna Lau @alwynalau - Active
Geoffrey Pay @gpay - inactive
Angelique DeCastro @angeliquedecastro - inactive
Caressa Cunningham @caressalc27 - inactive
Ehrik Aldana @ehrik - Consulted

Partners & Stakeholders

For PM management of stakeholders, see Living Project Document.

Entity Name Contact Role RACI
SF Planning Department Paula Chiu paula.chiu@sfgov.org @pchiu-sf SF Planning Department Informed
Govt Data Portal Jason --- --- Informed
SF Supervisors --- --- --- --
SF Supervisor D5 London Breed London.Breed@sfgov.org Legislature stakeholder Informed
SF Supervisor D8 Jeff Sheehy Jeff.Sheehy@sfgov.org Legislature stakeholder -
SF Supervisor D9 Hillary Ronen Hillary.Ronen@sfgov.org Legislature stakeholder -
SF Mayor --- --- ---
Candidate for Mayor (6/2018) London Breed london@londonformayor.com City Executive Stakeholder Informed
CA State Legislative Representatives --- --- --- --
CA State Legislative Representatives --- --- --- --
Coalitional / Advocacy Organization --- --- --- --
Non-SF CfA Housing Projects --- --- --- --
San Francisco Residents by survey --- --- --
Real Estate Developers --- --- --- --
Press / Journalists --- --- --- --

How do I access the data?

See data/README.md for information about analyzing the data. The data is checked into the repository under data/cleaned.

History of the Project

Started in December 2015 by the SF Data Science Working Group, the project focused on integrating and exploring data, guided by opening questions of the the original ask.

In December 2017, Phase II began to incorporate new stakeholders and build further analysis on top of work in Phase I.

Links

The pipeline dataset
The pipeline website
Notes from March 2017 convo with Paula

See data/README.MD for details about the data

Annual Housing Inventory Reports

Affordable Housing Reports


Getting Started

Setting up Python Environment

First make sure you have python3 and virtualenv installed.

Run this command to make a virtualenv:

virtualenv --python=$(which python3) VE

Run this command to enter the virtualenv:

source VE/bin/activate

Then run this command to install the dependencies:

brew install gdal --HEAD
pip install -r requirements.txt