FragDBnet/fragrance-database

FragDB — Fragrance Database (Sample)

The most comprehensive structured fragrance database available. This is a free sample containing 10 fragrances with related brands and perfumers.

Dataset Description

FragDB is a relational database of the fragrance industry containing:

File	Records	Fields	Description
fragrances.csv	10	28	Iconic fragrances (Chanel, Dior, Tom Ford...)
brands.csv	7	10	Luxury brand profiles
perfumers.csv	15	11	Master perfumer profiles

Full Database

	Sample	Full Database
Fragrances	10	119,000+
Brands	7	7,200+
Perfumers	15	2,700+
Year Range	1992-2015	1533-2026

Full database available at fragdb.net

Quick Start

Using Hugging Face Datasets

from datasets import load_dataset

# Load all files
dataset = load_dataset("FragDB/fragrance-database")

# Access each table
fragrances = dataset['fragrances']
brands = dataset['brands']
perfumers = dataset['perfumers']

Using Pandas

import pandas as pd

fragrances = pd.read_csv('fragrances.csv', sep='|')
brands = pd.read_csv('brands.csv', sep='|')
perfumers = pd.read_csv('perfumers.csv', sep='|')

# Join fragrances with brands
fragrances['brand_id'] = fragrances['brand'].str.split(';').str[1]
df = fragrances.merge(brands, left_on='brand_id', right_on='id', suffixes=('', '_brand'))

print(df[['name', 'name_brand', 'country', 'rating']])

Data Structure

fragrances.csv (28 fields)

Identity & Basic Info

Field	Description	Example
pid	Unique fragrance ID	9828
url	Direct link to fragrance page	URL
brand	Brand name and ID reference	Creed;b1
name	Fragrance name	Aventus
year	Release year	2010
gender	Target gender	for men, for women, for women and men
collection	Collection within brand	Text

Composition

Field	Description	Format
accords	Scent accords with strength	fruity:100:#FC4B29:#000;woody:67:#774414:#FFF
notes_pyramid	Notes by layer	top(Bergamot,url,img;...)middle(...)base(...)
perfumers	Perfumer names and IDs	Erwin Creed;p1;Olivier Creed;p2
description	Fragrance description	HTML text

Ratings & Votes

Field	Description	Format
rating	Average rating & vote count	4.33;24561
appreciation	Love/like/ok/dislike/hate	love:100;like:42.23;ok:11.85;...
price_value	Price perception votes	way_overpriced:6658;overpriced:2844;...
ownership	Ownership status	have_it:52.82;had_it:12.32;want_it:34.86
gender_votes	Gender suitability votes	female:149;unisex:866;male:7977;...
longevity	Duration votes	very_weak:784;weak:1459;moderate:5869;...
sillage	Projection votes	intimate:1816;moderate:8139;strong:4289;...
season	Seasonal suitability	winter:44.39;spring:97.60;summer:99.48;fall:74.81
time_of_day	Day/night suitability	day:100.00;night:68.93

Related Fragrances

Field	Description	Format
by_designer	Same brand fragrances	Semicolon-separated PIDs
in_collection	Same collection fragrances	Semicolon-separated PIDs
reminds_of	Similar fragrances	Semicolon-separated PIDs
also_like	Recommended fragrances	Semicolon-separated PIDs

Media

Field	Description
main_photo	Main bottle photo URL
info_card	Social card image URL
user_photoes	User-submitted photos (semicolon-separated)

brands.csv (10 fields)

Field	Description	Example
id	Unique brand identifier	b1
name	Brand name	Creed
url	Fragrantica brand page	URL
logo_url	Brand logo image	URL
country	Country of origin	France
main_activity	Primary business	Fragrance house
website	Official website	https://www.creed.com
parent_company	Parent company	Kering
description	Brand description	HTML text
brand_count	Number of fragrances	847

perfumers.csv (11 fields)

Field	Description	Example
id	Unique perfumer identifier	p1
name	Perfumer name	Alberto Morillas
url	Fragrantica perfumer page	URL
photo_url	Perfumer photo	URL
status	Professional status	Master Perfumer
company	Current company	Firmenich
also_worked	Previous companies	Quest International, Givaudan
education	Education	ISIPCA
web	Personal website	URL
perfumes_count	Number of fragrances	538
biography	Biography	HTML text

Sample Fragrances

The sample includes these iconic fragrances:

• Coco Mademoiselle (Chanel)
• Sauvage (Dior)
• Black Orchid (Tom Ford)
• Alien (Mugler)
• La Vie Est Belle (Lancôme)
• Black Opium (Yves Saint Laurent)
• Light Blue (Dolce & Gabbana)
• And more...

Use Cases

• Recommendation Systems — Build "if you like X, try Y" engines using accords, notes, and also_like data
• Market Analysis — Analyze trends by brand, country, year, or perfumer
• NLP — Process 9.4M words of descriptions in the full database
• Collection Apps — Build fragrance tracking and discovery apps
• E-commerce — Enrich product catalogs with detailed fragrance data

File Format

• Format: CSV (pipe | delimited)
• Encoding: UTF-8
• Quote Character: " (double quote)

Parsing Examples

Parse brand field

brand_name, brand_id = row['brand'].split(';')
# brand_name = "Chanel", brand_id = "b91"

Parse rating field

rating_avg, rating_votes = row['rating'].split(';')
# rating_avg = "4.33", rating_votes = "24561"

Parse accords field

accords = []
for accord in row['accords'].split(';'):
    name, strength, bg_color, text_color = accord.split(':')
    accords.append({'name': name, 'strength': int(strength)})

Parse notes pyramid

import re
layers = re.findall(r'(top|middle|base)\(([^)]*)\)', row['notes_pyramid'])
for layer_name, notes_str in layers:
    notes = [n.split(',')[0] for n in notes_str.split(';')]
    print(f"{layer_name}: {notes}")

Links

• Full Database: fragdb.net
• GitHub: github.com/FragDB/fragrance-database
• Kaggle: kaggle.com/datasets/eriklindqvist/fragdb-fragrance-database

License

This sample is released under the MIT License. Free for personal and commercial use.

The full database requires a commercial license — see fragdb.net for details.

Citation

@dataset{fragdb2026,
  title={FragDB Fragrance Database},
  author={FragDB},
  year={2026},
  url={https://fragdb.net},
  note={Sample dataset}
}