Luxury Perfume Prices - FULL

**Overview**

This dataset delivers a comprehensive snapshot of the global luxury perfume market, covering nearly 3,000 high-end fragrances across 638 premium brands.It includes detailed pricing intelligence spanning an exceptional range—from accessible luxury to ultra-premium collectibles—paired with rich product metadata and embedded image thumbnails for visual analysis.
Designed for data engineers, analysts, and ML practitioners, the dataset is production-ready in Parquet format and optimized for large-scale analytics on Databricks.Typical use cases include price elasticity modeling, brand positioning analysis, visual ML workflows, and competitive market intelligence.With anonymized sellers and rigorous quality controls, the dataset is safe, compliant, and immediately actionable.

**Provenance**

The data was ethically sourced from publicly available resources and compiled by the #1 Kaggle Dataset Grandmaster globally.All seller identifiers were fully anonymized to ensure GDPR and CCPA compliance, and no personally identifiable information (PII) is included.
The dataset underwent a comprehensive quality assurance process, including schema validation, completeness checks, price distribution analysis, and image integrity testing.It is distributed under the Creative Commons Attribution 4.0 (CC BY 4.0) license.

Acknowledgements:
Compiled and curated by a Kaggle Grandmaster.Distributed by AIDC Data LLC.Licensed under as CC-4, public with attribution.

**Use Cases**

This dataset enables high-value analytics and ML workflows on Databricks and other platforms:

- **Luxury Price Intelligence**: Analyze pricing distributions, outliers, and premium segmentation across global luxury brands.
- **Brand & Portfolio Analysis**: Compare brand positioning, assortment breadth, and price tiers across hundreds of luxury houses.
- **Visual ML & Multimodal Models**: Leverage embedded image thumbnails for visual classification, similarity search, or multimodal learning.
- **Market Trend Monitoring**: Track quarterly pricing dynamics and product availability shifts in the luxury fragrance sector.
- **Anomaly & Fraud Detection**: Identify abnormal pricing patterns or suspicious listings using scalable Spark-based pipelines.

**Column Dictionary**

- **brand** (string): Luxury perfume brand name.
- **title** (string): Product title or listing name.
- **type** (string): Fragrance concentration or formulation (e.g., EDT, EDP).
- **condition** (string): Item condition at time of listing.
- **price** (decimal): Numeric price value.
- **priceWithCurrency** (string): Price including currency symbol.
- **image** (string): Embedded image thumbnail reference.
- **seller** (string): Fully anonymized seller identifier.
- **shipsTo** (string): Shipping destination coverage.
- **excludesShipping** (string): Shipping exclusion regions, if any.
- **itemLocation** (string): Item location at time of listing.
- **lastUpdated** (string): Last update timestamp of the listing.
- **perfumeType** (string): Gender or target classification (e.g., men’s, women’s).

**Technical Metadata**

- **Geographic Coverage**: Global
- **Update Frequency**: Quarterly
- **Collection Granularity**: Event-level
- **Data Source**: Publicly available luxury perfume listings, professionally curated and cleaned
- **Time Range**: 2024-05-18 to 2024-05-20
- **Size (GB)**: 0.0016
- **Keywords**: luxury perfume prices, fragrance market data, brand analytics, pricing intelligence, parquet dataset, retail analytics, multimodal ML, Databricks marketplace

**Quality Summary**

- **Overall Quality Score**: 99.06% (Grade A+)
- **Brand Coverage**: 100% (638 brands)
- **Image Coverage**: 99.6%
- **Sellers**: 100% anonymized
- **Status**: Production-ready