Nobel Prize Laureates Scraper — Winners, Years & Motivations

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Extract complete Nobel Prize winner data from the official Nobel Prize API. This scraper gives you structured, ready-to-use data on every laureate since 1901 — including award year, category, prize motivation, prize amount, birth country, institutional affiliation, and Wikipedia link.

Features

• Full coverage: All ~1,000 Nobel Prize laureates from Physics to Literature to Peace
• Flexible filtering: Filter by category, award year, gender, or name
• Flattened output: One record per laureate-prize pair — ideal for data analysis and spreadsheets
• Enriched fields: Prize amounts, inflation-adjusted amounts, affiliations, and Wikipedia URLs included
• Official source: Pulls directly from the official Nobel Prize API — no scraping of HTML, no fragile selectors
• LLM-ready output: Clean, structured JSON suitable for RAG pipelines and AI research tools

Data Fields

How to Scrape Nobel Prize Data

Follow these steps to extract Nobel Prize laureate data using this Actor:

1. Go to the Actor page on Apify Store and click Try for free
2. Set your filters in the input form:
   • Leave all fields empty to fetch all ~1,000 laureates
   • Select a Prize Category (e.g., Physics, Chemistry, Peace) to narrow results
   • Enter an Award Year (e.g., 2024) to get only that year's laureates
   • Use the Gender filter to analyze gender representation over time
   • Enter a Name Filter to look up a specific laureate (e.g., Einstein)
3. Set Max Results — default is 500 laureates. Set to 0 for all available records
4. Click Start — the Actor runs in seconds (no browser, no proxy needed)
5. Download your data in JSON, CSV, or Excel from the Dataset tab

Input Example

{
"category":"phy",
"year":"",
"gender":"",
"nameFilter":"",
"maxResults":500
}

Output Example

{
"laureateId":"941",
"fullName":"Donna Strickland",
"gender":"female",
"birthDate":"1959-00-00",
"birthCountry":"Canada",
"deathDate":"",
"awardYear":2018,
"category":"Physics",
"motivation":"for their method of generating high-intensity, ultra-short optical pulses",
"prizeAmount":9000000,
"prizeAmountAdjusted":9000000,
"affiliation":"University of Waterloo",
"affiliationCountry":"Canada",
"wikipediaUrl":"https://en.wikipedia.org/wiki/Donna_Strickland"
}

Pricing

This Actor uses pay-per-result pricing at $0.003 per result. A full run fetching all ~1,000+ laureate-prize records costs approximately $0.003–$0.005 total.

There are no proxy costs — this Actor calls the official Nobel Prize REST API directly, so compute costs are minimal.

Other Scrapers

Looking for more research-grade data scrapers? Check out these other Actors by the same author:

• CISA Known Exploited Vulnerabilities (KEV) Scraper — CVE threat intelligence feed with filtering
• Hotfrog Scraper — Business directory data with addresses, phones, and categories

FAQ

Q: Does this Actor require an API key or login? A: No. The Nobel Prize API is fully open and requires no authentication.

Q: How current is the data? A: The Nobel Prize API is maintained by the Nobel Prize organization and is updated annually after each October announcement.

Q: Why does a laureate appear multiple times? A: Records are flattened by prize. Marie Curie, for example, won both Physics (1903) and Chemistry (1911), so she appears as two separate records.

Q: Can I filter by multiple categories at once? A: Currently the API supports one category filter per run. Run the Actor multiple times with different category codes and merge the outputs.

Q: What does prizeAmountAdjusted mean? A: It is the prize amount adjusted for inflation to a consistent base year, as provided by the Nobel Prize API.

Q: What category codes should I use? A: phy (Physics), che (Chemistry), med (Medicine/Physiology), lit (Literature), pea (Peace), eco (Economics).

Legal Disclaimer

This Actor retrieves data from the official Nobel Prize API (api.nobelprize.org), which is publicly accessible and intended for programmatic use. No authentication bypass is performed. The data is provided by the Nobel Prize Outreach AB for educational and research purposes. Always review the Nobel Prize API terms before using this data commercially. For support, contact the Actor author via the Apify platform.