Project Info

Ctrl+Alt+Elite thumbnail

Team Name


Team Members

Shayaan , Jahin , William , Usi , segun kayode , Izabella and 4 other members with unpublished profiles.

Project Description

Liveability in numbers.

Habistasis allows both individuals and policymakers alike to calculate liveability scores for postcode regions, with a breakdown on which stats contribute positive or negatively to an area's score, and its overall liveability. This insight allows for and promotes a more targeted and strategic plans, both individual and policy-level, to improve liveability in areas which need it most.

Habistasis additionally provides recommendations for government rebates, subsidies, and other schemes to individuals in low-liveability areas.

Please note: the Vercel application is currently unavailable. Please refer to https://github.com/ctrl-alt-elit3/habitasis#readme for information on setting up a local demo.

#liveability #python

Data Story

We started to see how to best approach the problem - we looked at datasets from transport, housing, bonds, FuelCheck to see how we could make sense of it

We spent time acquiring, processing, and collating data for analysis with automated tools and scripting to create a consistent format, "indexed" by postcode.

We started with a mockup of what the application should look like, with assets and a landing page, as well as the foundations for a scoring algorithm, that assigns scores to postcodes based on their average fuel prices, rental prices, and vehicle ownership.

Once we had a model for the scoring system, using Python (Flask) and React, we built an MVP: a web application with Python and React, where the user can enter their postcode, and the application calculates a liveability score for them.

Evidence of Work



Project Image

Team DataSets

NSW-Rental Bond Holdings

Data Set


Data Set

Rent and Sales Report - interactive dashboard

Data Set

NSW-Social Housing Delivery Dashboard

Data Set

Challenge Entries

Cost of Living Pressure NSW

Cost of living is key issue effecting many NSW citizens. What can data such as the rental bonds and fuel price data tell us about the impact and possible solutions?

Eligibility: Use at least 1 dataset from "data.nsw.gov.au”. Department of customer service employees are ineligible for this challenge.

Go to Challenge | 4 teams have entered this challenge.

COVID’s lasting impact on education

What impact has COVID had on student educational outcomes (for example retention/enrolment rates, HSC completions and more)? What lessons can we learn to minimise the impact on education for future pandemics?

Eligibility: Use at least 1 dataset from "data.nsw.gov.au”. Department of customer service employees are ineligible for this challenge.

Go to Challenge | 7 teams have entered this challenge.