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In this report we will be analyzing Rome Airbnb properties dataset from inside airbnb and try to find what variables influences the income generted by the property. We got our dataset from inside airbnb. Inside Airbnb is a project that provides data and advocacy about Airbnb's impact on residential communities. They provide data and information to empower communities to understand, decide and control the role of renting residential homes to tourists.
| Variable | Description |
|---|---|
| host_name | Name of the host. |
| neighbourhood | Name of the neighbourhood. |
| latitude | Used to make an interactive map. |
| longitude | Used to make an interactive map. |
| room_type | Entire apt, private room, hotel room. |
| Price | Price in Euro. |
| minimum_nights | minimum number of night stay for the listing. |
| number_of_reviews | The number of reviews the listing has. |
| last_review | The date of the last/newest review. |
| availability_365 | The availability of the listing x days in the future. |
| number_of_reviews_ltm | The number of reviews the listing has (in the last 12 months). |
| amenities | A list of amenities in the listing. |
- pandas
- numpy
- matplotlib
- seaborn
- plotly
- folium
- ast
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent