Dataset: Airbnb Amsterdam Dataset

About this Dataset

Airbnb Amsterdam Dataset

Airbnb is an online marketplace for arranging or offering lodging, primarily homestays, or tourism experiences. More and more people choose to stay in a local house when they are traveling. The prices of the houses vary a lot depending on the location, the size, the service, or the surroundings of the houses.

Airbnb operates by acting as a mediator between travelers and tourists looking for a place to stay and hosts wanting to rent their properties to them. It facilitates the process of renting by providing an online platform where hosts can list and display their properties for people wishing to rent them.

Currently, there are over 5 million properties listed on the Airbnb website from across the globe by more than 4 million hosts. And the website is visited by over 100 million visitors each month.

Since Airbnb is very popular and operates online, it generates a lot of data. The data mainly focuses on the listed properties, hosts, bookings/rentals, and reviews.

When exploring different data sets for these assignments, we found the Airbnb data to be a well-structured, organized, and concise relational dataset - perfect for practicing MySQL.

We chose the InsideAirbnb for Amsterdam as it contained a sizable amount of data.

Tables

Listingsair

@kaggle.laibaanwer_airbnb_amsterdam_dataset.listingsair

846.76 KB
6173 rows
44 columns


CREATE TABLE listingsair (
  "id" BIGINT,
  "last_scraped" TIMESTAMP,
  "host_id" BIGINT,
  "host_since" TIMESTAMP,
  "host_response_time" VARCHAR,
  "host_is_superhost" VARCHAR,
  "host_listings_count" BIGINT,
  "host_total_listings_count" BIGINT,
  "host_identity_verified" VARCHAR,
  "neighbourhood_cleansed" VARCHAR,
  "property_type" VARCHAR,
  "room_type" VARCHAR,
  "accommodates" BIGINT,
  "bathrooms_text" VARCHAR,
  "bedrooms" DOUBLE,
  "beds" DOUBLE,
  "amenities" VARCHAR,
  "price" DOUBLE,
  "minimum_nights" BIGINT,
  "maximum_nights" BIGINT,
  "minimum_minimum_nights" DOUBLE,
  "maximum_minimum_nights" DOUBLE,
  "minimum_maximum_nights" DOUBLE,
  "maximum_maximum_nights" DOUBLE,
  "minimum_nights_avg_ntm" DOUBLE,
  "maximum_nights_avg_ntm" DOUBLE,
  "has_availability" VARCHAR,
  "availability_30" BIGINT,
  "availability_60" BIGINT,
  "availability_90" BIGINT,
  "availability_365" BIGINT,
  "number_of_reviews" BIGINT,
  "number_of_reviews_ltm" BIGINT,
  "number_of_reviews_l30d" BIGINT,
  "first_review" TIMESTAMP,
  "last_review" TIMESTAMP,
  "review_scores_rating" DOUBLE,
  "review_scores_value" DOUBLE,
  "instant_bookable" VARCHAR,
  "calculated_host_listings_count" BIGINT,
  "calculated_host_listings_count_entire_homes" BIGINT,
  "calculated_host_listings_count_private_rooms" BIGINT,
  "calculated_host_listings_count_shared_rooms" BIGINT,
  "reviews_per_month" DOUBLE
);