sfbrigade/datasci-firerisk

Name: datasci-firerisk

Owner: SFBrigade

Description: This project attempts to model and acquire data from SF OpenData - and other sources - to predict the relative risk of fire in San Francisco?s buildings and public spaces.

Created: 2017-05-25 02:19:00.0

Updated: 2018-05-04 16:26:32.0

Pushed: 2018-05-14 23:32:46.0

Homepage: http://codeforsanfrancisco.org/projects/SF-Fire-Risk-Project

Size: 27657

Language: Jupyter Notebook

GitHub Committers

User	Most Recent Commit	# Commits

Other Committers

User	Email	Most Recent Commit	# Commits

README

San Francisco Fire Risk Project

This project is a part of the Data Science Working Group at Code for San Francisco. Other DSWG projects can be found at the main GitHub repo.

Project Status: Active Current Model's Average F1 Score: 0.67

Project Intro/Objective

This project attempts to model and acquire data from SF OpenData - and other sources - to predict the relative risk of fire in San Francisco?s buildings and public spaces.

Methods Used

• Data Science
• Machine Learning
• Data Visualization
• Predictive Modeling
• Data Analysis

Technologies

• Python
• NumPy / pandas
• Scikit-learn
• matplotlib
• R
• dplyr / tidyr
• ggplot2
• Jupyter Notebook

Project Description

The mapping software will allow the user to type in an address and see fire-related risks and incidences around their area, as well as provide recommendations by fire safety experts in cases where there may be a high enough score to warrant preventive actions. This project is modeled after Data Science for Social Good's (DSSG) Firebird Project in Atlanta, GA. Consultation is occasionally provided by members of the DSSG and former members of the Atlanta project.

Needs of this project

1) data scientists 2) data analysts 3) data visualizers 4) researchers and journalists (find trends and data related to fire incidents in the city) 5) product and project managers

Getting Started

1. Clone this repo. For help, see tutorial
2. Download data stored in the project Google Drive.
3. Review Project Wiki.
4. Check Issue Tracker and discuss with team members to understand current project needs.
5. Hack away! :)

Additional Documentation

Our workflow chart is here: SF Fire Risk Workflow

SF Fire Risk Attribute Sheet SF Fire Risk Predictive Model Attribute Sheet (Always adding more!)

Featured Notebooks/Analysis

May 2017 Presentation

CartoDB Visual Mock-Up

Contributing DSWG Members

| Name | Slack Handle | Role | Website | |—————|—————-|———————————|——————————-| | Ryan Tanaka | @ryangtanaka | Product Manager, Team Lead | http://product.ryangtanka.com | | Kel Yip | @yamariva2000 | Data Scientist, Technical Lead | | | Seward Lee | @sewardlee337 | Data Scientist | http://www.sewardlee.com | | Kenny Durell | @kennyd | Data Scientist | | | Sam Williams | @swilliams2099 | Research, Outreach | | | Kevin Stahler | @stahlerk | Data Scientist | | | Yuzhe Chen | @yzxchn | Data Scientist | | | Chris Quiambao| @ccquiambao | Data Scientist | https://github.com/ccquiambao | | Hannah Gorman | @hannahrosey | Data Scientist, Visualization | |

Contact

• If you haven't joined the SF Brigade Slack, you can do that here.
  
• Our Slack channel is #datasci-firerisk
• Feel free to contact team leads with any questions or if you are interested in contributing! Most of our activities are done in our Slack channel.