Group 6: Katy Fuentes, Nicole Pipkins, Reza Abasaltian, Radhika Balasubramaniam
HEROKU Dashboard Deployment - https://airbnb-dashboard-g6.herokuapp.com/
Github Dashboard Deployment - version requires the execution of the Python Flask app: /Airbnb-v1/app.py on localhost:5000: https://abasaltr.github.io/Airbnb_Dashboard/Airbnb-v1/index.html
PostgreSQL database username and password are required entries in file: /Airbnb-v1/db_key.py
Heatmap visualization requires Mapbox API access token (https://account.mapbox.com/) key entries in file: /Airbnb-v1/static/js/config.js
For database installation, run the sql script located at .
Once the tables are created you can import the data in the folder to the tables at the ! folder.
The order and the mapping of files to tables for the import are
- top_airbnb_cities <-- top_airbnb_cities.csv
- top_neighborhood_overview <-- top_neighborhood_overview.csv
- city_nbh <-- city_nbh.csv
- neighborhood_overview <-- neighborhood_overview.csv
- neighborhood_insights <-- neighborhood_insights.csv
- rental_rates <-- rental_rates.csv
- rental_rates_info <-- rental_rates_info.csv
- listings_info <-- listings_info.csv
- merged_census_crime <-- merged_census_crime.csv
- historical_insights <-- historical_insights.csv
The Airbnb Dashboard provides guests fun interactive way to plan their vacation, and hosts a general idea about the airbnb market in the area with a few key components in mind:
Can you get to where you’re planning by foot?
Will you be paying an arm and a leg for a cleaning fee?
And what kind of neighborhood is the listing in?
How much rental income do hosts generally make?
What are the rental rates in the area and other general statistics?
What are the rental rates in the area and other general statistics?
What is the investment score, income score and walkscore for the neighborhood?
Neighborhood facts
Compare nightly rates, nights booked and cleaning fees for each property type
Heat map analysis for the nights booked, reviews for the property listings
Average annual income realised for each property type
Average annual income vs occupancy for each property type
Average annual income vs occupancy for rental size
https://rapidapi.com/
https://www.mashvisor.com/data-methodology
https://www.census.gov/data/developers/updates/new-discovery-tool.html
https://www.kaggle.com/mikejohnsonjr/united-states-crime-rates-by-county
https://public.opendatasoft.com/api/records/1.0/search/?dataset=airbnb-averages&q=&rows=1000&sort=date&facet=neighbourhood&facet=room_type&facet=number_of_rooms&facet=date&facet=location&refine.location=United+states
Using a compilation of Airbnb top cities, narrowed search by five states that included: Texas, New York, California, Florida, and District of Columbia.
Made 6 days of API data calls to obtain neighborhoods, neighborhood overview, rental rates, and listing information
Used census and crime statistic CSV files and merged data by condensed counties to integrate with the API information.
Created a relational database "airbnb_db" on SQL.
Tables include:
city_nbh
listings_info
merged_census_crime
neighborhood_insights
neighborhood_overview
rental_rates
rental_rates_info
top_airbnb_cities
top_neighborhood_overview
historical_insights
Flask Routes:
cities = "/api/cities"
overview = "/api/nbh-overview"
city_nbh = "/api/city-nbh"
census_crime = "/api/census-crime"
rental_income = "/api/income_change"
crime_stats = "/api/crime_stats"
top_nbh = "/api/top-nbh"
map = "/map/<nbh_id>"
heatmap = "/api/map/<nbh_id>"
statistics = "/api/statistics/<city_id>/<nbh_id>"
rental_size = "/api/rental_size/<city_id>/<nbh_id>"
rental_type = "/api/rental_type/<city_id>/<nbh_id>"
income_change = "/api/income_change"
historical= "/api/historical/<city>/"
houstonId = "api/getHoustonId
Javascript files:
app.js - for the index file functions
rentalapp.js - for the rental analysis file functions
app-heatmap.js - heatmap module
rentalincome2.js - Rental Size vs occupancy chart
rentalincomebyprop.js - Rental income by property chart
rentalTypes.js - Comparison for cleaning costs, rooms booked chart module
roistat.js - Bullet chart for ROI module
statistics.js - statistics module
HTML integration:
index.html - main dashboard file
trends.html - rental analysis file
heatmap.html - heatmap analysis file
icon.html - icon for heatmap analysis
The Airbnb Dashboard includes interactive visualizations and tables on the following:
-Walking score scale to assess if you can walk to places or plan for transportation. The scores include: 0-24 is Almost All Car-Dependent,
25-49 is Most Car-Dependent, 50-69 Somewhat Walkable, or 70-89 is Very Walkable.
-Map to detail the cleaning fees, nights booked, Airbnb listings with a summary of the listing. The leaf's represent total reviews.
-Cleaning Fees to review the associated cleaning fees by property listing.
-Return on investment compare rental income to home values and assess the potential return on owning an Airbnb in a certain city or neighborhood.
-Rental income to discover how much rental income hosts make in the listing area.
-Income by property type to evaluation.
-Demographics/Crime Data with a summary of population, income per capita, crime rate, demographics, and statistics by crime types.
-Rental statistics with average rental rates, nightly rates, cleaning fee, occupancy rates, Airbnb count, and review counts.
- Average annual income by property type
- Average income by property type vs occupancy
- Average income by Rental Size vs occupancy