https://github.com/crenshaw-dev/cville-airbnbs

Data about Charlottesville AirBnBs
https://github.com/crenshaw-dev/cville-airbnbs

Last synced: 25 days ago
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Data about Charlottesville AirBnBs

• Host: GitHub
• URL: https://github.com/crenshaw-dev/cville-airbnbs
• Owner: crenshaw-dev
• Created: 2024-01-01T21:12:23.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2024-05-05T16:26:32.000Z (6 months ago)
• Last Synced: 2024-05-05T21:25:19.577Z (6 months ago)
• Language: Python
• Size: 2.75 MB
• Stars: 0
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Charlottesville Airbnb Data

## What?

Information about Airbnbs in Charlottesville, with a nice [map](https://crenshaw-dev.github.io/cville-airbnbs/).

Map pin color key:

* Green: address known, registered with the city for 2023

* Red: address known, not registered with the city for 2023

* Grey: address unknown

## Why?

Data is good.

## How?

I run [main.py](main.py) occasionally. That updates [data.csv](data.csv). The script pulls listings from Airbnb's API by

filtering on the rough rectangle around Charlottesville and then filtering by city name.

The coordinates from Airbnb are obfuscated. Where possible, I manually inspect the Airbnb listing and try to find an

address. Where I find an address, I also update the coordinates.

Many of the addresses were copied from [Erin's CSV](https://github.com/erinleeryan/cville_airbnb/blob/fe5500c2c9236623e7ba0f8094731cdcd5f51811/data/cville_airbnb_locations.csv).

The script is designed to preserve the manually updated coordinates and address.

Listings come and go from the API results. Where the `active` column contains `true`, the most recent API scrape

contained the listing. Where the `active` column is `false`, the listing was once present in the API response but is no

longer. Some listings appear/disappear frequently. Use the "blame" feature in GitHub to view the history of a certain 

listing.

The "2023 approved" column contains "true" if the address is known to have been approved in 2023. The list of approved

addresses is in [2023_approved.csv](2023_approved.csv). It's joined to data.csv whenever main.py is run.

## Roadmap

* Make it easy to swap in a different city. This would mean making the 2023_approved.csv file optional and more general.

  Maybe the approval status should be added by a separate script.

* Make the script handle missing CSVs more gracefully. Right now the script fails if CSV isn't present.

* Get date of most recent review, so we have a sense of whether the listing is active.

* Get the number of reviews left in the last 12mo.

* Note in data whether the listing falls in a zoning area that requires registration. (This may be difficult if we don't have GIS data for the new zoning areas yet.)

* Generate a human-readable report from the data.

* Add arbitrary "notes" column.

* Generate a report describing single addresses with multiple listings.