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---
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license: other
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license_name: bright-data-master-service-agreement
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license_link: https://brightdata.com/license
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language:
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- en
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tags:
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- travel
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- hospitality
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- booking
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- hotels
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- hotel
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- pricing‑data
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- tabular‑data
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pretty_name: 'Booking.com Listings '
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size_categories:
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- 10K<n<100K
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---
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# Booking Listings – *Free Cancellation* 🏨✈️ |
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**Booking Listings** is a structured snapshot of accommodation offers worldwide as listed on **Booking.com**. |
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This subset contains **only properties that offer *free cancellation***, enabling analysts and data scientists to study flexible‑booking behaviour, derive pricing strategies, and build recommendation or revenue‑management systems. |
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> **Highlights** |
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> |
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> * 75 k hotels & apartments across **84 countries** |
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> * Rich pricing & availability metadata (final vs. original price, tax descriptions, currency, sustainability flags) |
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> * Guest sentiment — review score & count |
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> * Property configuration: bedrooms, kitchens, beds, star rating, sustainability level, ***free‑cancellation‑until*** timestamp |
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> * Scraped **Mar 19 2025** with Bright Data Web Scraper |
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--- |
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## Dataset Summary |
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| Metric | Value | |
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| --------------- | ------------------------------------------------- | |
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| Records | ≈ 75 000 (filtered free‑cancellation subset) | |
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| Columns | 36 | |
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| Time range | Check‑in/out dates centred on **19 Mar 2025** | |
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## Supported Tasks |
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* **Travel recommendation & personalisation** – rank properties by flexibility, price trends, amenities. |
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* **Dynamic pricing / revenue management** – benchmark competitors that allow free cancellation to fine‑tune rates. |
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* **Market research & trend analysis** – assess demand elasticity towards cancellation policies in different regions. |
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* **Real‑estate & investment insights** – locate high‑rated, sustainable, or luxury properties with lenient policies. |
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## Languages |
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All textual fields are in **English**. Currency codes follow ISO‑4217. |
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--- |
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## Dataset Structure |
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### Data Instances |
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Each row represents a single property returned by a user search (one check‑in/out pair). Below is a truncated example (JSON Lines): |
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```json |
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{ |
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"url": "https://www.booking.com/hotel/au/the-westin-perth.html?...", |
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"location": "Perth", |
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"check_in": "2025-03-19T00:00:00Z", |
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"check_out": "2025-03-20T00:00:00Z", |
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"adults": 1, |
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"rooms": 1, |
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"id": 3052882, |
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"title": "The Westin Perth", |
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"city": "Perth", |
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"review_score": 8.8, |
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"review_count": 1250, |
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"image": "https://cf.bstatic.com/xdata/images/hotel/...jpg", |
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"final_price": 47249, |
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"original_price": 47249, |
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"currency": "JPY", |
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"free_cancellation": true, |
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"free_cancellation_until": "2025-03-18T16:00:00Z", |
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"hotel_rank": 77, |
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"star_rating": null, |
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"tags": null, |
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... |
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} |
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``` |
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### Data Fields |
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| Column | Type | Description | |
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| ------------------------- | -------------------- | --------------------------------------------------- | |
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| `url` | string (URL) | Direct link to the property listing. | |
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| `location` | string | General destination (city/area) of the property. | |
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| `check_in` | datetime | Requested check‑in date. | |
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| `check_out` | datetime | Requested check‑out date. | |
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| `adults` | int | Number of adults in the query. | |
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| `children` | int \| null | Number of children (if provided). | |
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| `rooms` | int | Rooms requested. | |
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| `id` | string | Booking.com property identifier. | |
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| `title` | string | Property name. | |
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| `address` | string | Street address. | |
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| `city` | string | City name (may differ from `location`). | |
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| `review_score` | float | Average guest rating (0‑10). | |
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| `review_count` | int | Number of reviews. | |
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| `image` | string (URL \| null) | Thumbnail of main image. | |
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| `final_price` | float | Price returned by search (includes taxes). | |
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| `original_price` | float | Original price before discounts. | |
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| `currency` | string | ISO‑4217 currency code. | |
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| `tax_description` | string \| null | Additional taxes/fees description. | |
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| `nb_bedrooms` | int | Number of bedrooms. | |
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| `nb_all_beds` | int | Total beds available. | |
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| `full_location` | string | Normalised “City, Country” location. | |
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| `free_cancellation` | bool | *Always `true`* in this subset. | |
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| `free_cancellation_until` | datetime \| null | Deadline for free cancellation. | |
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| `property_sustainability` | JSON | Sustainability metadata + facility codes. | |
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| `hotel_rank` | int | Position in Booking search results. | |
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| `searched_country` | string | 2‑letter country code of the search. | |
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| `map_coordinates` | struct | `{ "lat": float, "lon": float }` (may be null). | |
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| `listing_country` | string | Country where property is located. | |
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| `total_listings_found` | int | Total search results for query. | |
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| `star_rating` | int \| null | 1‑5 stars. | |
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| `tags` | string \| null | Booking‑generated tags (e.g. "Travel Sustainable"). | |
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| nb_livingrooms | int | Number of living rooms in the property. | |
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| nb_kitchens | int | Number of kitchens in the property. | |
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| no_prepayment | bool | Indicates if prepayment is not required. | |
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Nested object keys: |
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full_location → description, main_distance, display_location, beach_distance, nearby_beach_names |
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property_sustainability → is_sustainable, level_id, facilities |
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--- |
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## Data Splits |
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| Split | Rows | Description | |
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| ------- | ----- | ------------------------------- | |
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| `train` | 0 | *not applicable* | |
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| `test` | 0 | *not applicable* | |
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| `all` | ≈ 75k | Complete snapshot (single CSV). | |
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This dataset is delivered as **one CSV file** (`booking_listings.csv`). |
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--- |
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## Usage Example |
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```python |
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from datasets import load_dataset |
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ds = load_dataset( |
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"BrightData/booking_listings", |
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data_files="booking_listings.csv", |
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split="train", |
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) |
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print(ds[0]["title"], ds[0]["free_cancellation_until"]) |
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``` |
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--- |
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## Source & Methodology |
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Data was collected on **19 Mar 2025** using the **Bright Data Infrastructure** and publicly available Booking.com search results. |
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For this subset, we retained only listings where the *free cancellation* flag was **`true`**. |
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--- |
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## Citation |
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If you use this dataset in your work, please cite it as: |
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```bibtex |
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@dataset{booking_listings_free_cancel_2025, |
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author = {Bright Data}, |
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title = {Booking Listings – Free Cancellation Subset}, |
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year = {2025}, |
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publisher = {Hugging Face}, |
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url = {https://huggingface.co/datasets/BrightData/Booking-Listings}, |
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note = {Scraped via Bright Data on 2025‑03‑19} |
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} |
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``` |
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--- |
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## Maintainers |
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**Bright Data** |
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[@Bright Data](https://github.com/luminati-io) |
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Have questions or need a refreshed dump? Open an issue or reach out! 📨 |
