Tallinn Restaurants
@kaggle.ilyasmelyanskiy_tallinn_restaurants
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From www.vabalaud.ee
Dataset Description
Dataset:
| Column name | Description |
|---|---|
| Restaurant | Restaurant name is displayed here |
| Details URL | This is URL from which data is acquired |
| Address | Address of the Restaurant |
| Cuisine | Comma list of types of cuisine served |
| Avg_Bill | Average bill (float), estimated |
| Additional | List of properties that the venue has |
| Atmosphere | Atmosphere rating (1-5), float |
| Food | Food rating (1-5), float |
| Service | Service rating (1-5), float |
| Latitude | Latitude of venue |
| Longitude | Longitude of venue |
Please, note. You may want to explode Cuisine and Additional columns can be useful if exploded into dummy columns, for examplie via:
cuisine = pd.get_dummies(pd.DataFrame(result['Cuisine'].tolist()).stack()).sum(level=0)
properties = pd.get_dummies(pd.DataFrame(result['Additional'].tolist()).stack()).sum(level=0)
Acquired:
All the data was scraped by me from www.vabalaud.ee using BS4.
Good luck!
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