Tallinn Restaurants
From www.vabalaud.ee
@kaggle.ilyasmelyanskiy_tallinn_restaurants
From www.vabalaud.ee
@kaggle.ilyasmelyanskiy_tallinn_restaurants
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)
All the data was scraped by me from www.vabalaud.ee using BS4.
Good luck!
CREATE TABLE restaraunts_tallin (
"restaraunt" VARCHAR,
"detailsurl" VARCHAR,
"address" VARCHAR,
"cuisine" VARCHAR,
"avg_bill" DOUBLE,
"additional" VARCHAR,
"atmosphere" DOUBLE,
"food" DOUBLE,
"service" DOUBLE,
"latitude" DOUBLE,
"longitude" DOUBLE
);
Anyone who has the link will be able to view this.