🏆 Nobel Prize Data Analysis (1901–2025)

Who actually wins the Nobel Prize? I analyzed 124 years of data to find out.

Interactive dashboard visualizing Nobel Prize trends across 124 years

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🎯 The Question

We all know Marie Curie and Malala Yousafzai, but are they the exception or the rule?

I analyzed over 1,000 Nobel laureates from 1901 to 2025 to understand:

• Who actually wins (gender, geography, age)
• How the landscape has changed (solo vs team science)
• Why some fields dominate

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📊 Key Findings

🔴 The Gender Gap Is (Slowly) Closing

• Historically: Women = 6.6% of all winners
• 2020s: Women = 19.4% of winners this decade
• But: Physics still sits at 2% female

🟡 Solo Geniuses Are Extinct

• Early 1900s: 78% of prizes went to individuals
• Today: 65% are shared among 2-3 people
• Conclusion: Modern science is a team sport

🔵 The "Legends" Club

Only 7 laureates have won more than once:

• Red Cross (3× Peace)
• Marie Curie (Physics + Chemistry)
• Linus Pauling (Chemistry + Peace)
• John Bardeen (Physics 2×)
• Frederick Sanger (Chemistry 2×)
• Barry Sharpless (Chemistry 2×)
• UN High Commissioner for Refugees (2× Peace)

📌 Other Surprises

• Average winner age: 60 years (recognition takes decades)
• Youngest ever: Malala Yousafzai (17, Peace Prize 2014)
• Oldest ever: John Goodenough (97, Chemistry 2019)

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🛠️ Tools & Methodology

Data Cleaning (R)

# Key transformations
nobel_clean <- nobel_raw %>%
  mutate(
    born_date = ymd(born, quiet = TRUE),
    age_at_win = year - year(born_date),
    decade = (year %/% 10) * 10,
    prize_type = ifelse(share == 1, "Solo", "Shared")
  )

Challenges solved:

• Handling inconsistent date formats ("1950-00-00" → cleaned)
• Identifying repeat winners across different categories
• Calculating accurate age at win (accounting for missing birthdates)

Visualization (Looker Studio)

Built an interactive dashboard featuring:

• Line chart: Age trend over time
• Donut chart: Gender breakdown
• Stacked bar: Solo vs shared prizes
• Treemap: Category × Gender breakdown
• Heatmap: Geographic dominance

Dashboard includes:

• Dynamic filters (category, year range)
• KPI cards (total laureates, avg age)

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📊 Data Source

Nobel Prize API (1901–2025)
Official dataset from: http://api.nobelprize.org/v1/laureate.csv

Dataset includes:

• 1,026 laureates (individuals + organizations)
• Birth/death dates, countries, affiliations
• Prize categories, years, sharing information

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📜 License

This project is open source. Data sourced from the Nobel Prize API.

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