Nobel Prize Winner Analysis
This project explores trends and insights from the Nobel Prize dataset, using Python and data visualization tools to answer five analytical questions about Nobel laureates.
📁 Dataset The analysis uses the nobel.csv dataset, which contains information about Nobel Prize winners, including:
-Name
-Gender
-Birth Country
-Organization
-Year and Category of award
-More metadata on laureates
🎯 Questions Answered What is the most commonly awarded gender and birth country?
Which decade had the highest ratio of US-born Nobel Prize winners to total winners in all categories?
Which decade and Nobel Prize category combination had the highest proportion of female laureates?
Who was the first woman to receive a Nobel Prize, and in what category?
Which individuals or organizations have won more than one Nobel Prize throughout the years?
🛠️ Tools & Libraries Pandas – for data wrangling
NumPy – for numerical operations
Matplotlib & Seaborn – for data visualization
Jupyter Notebook / Python Script – for execution and exploration
📊 Visualizations The project includes several insightful plots:
Line plot showing the rise in US-born Nobel Prize winners over time.
Multi-line chart of female laureate proportions across prize categories.
Print summaries of individuals and organizations winning multiple times.