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README.md
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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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---
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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! 📨
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