The Nobel Prize is one of the most prestigious and well-known scientific awards in the world. It is awarded annually to individuals who have made outstanding contributions in various fields, including chemistry, literature, physics, physiology or medicine, economics, and peace. This readme file provides an overview of the content covered in the associated Jupyter notebook.
- Uploading Data
- Answering some questions on data
- 2.1 So, who gets the Nobel Prize?
- 2.2 The USA dominance
- 2.3 What is the gender of a typical Nobel Prize winner?
- 2.4 Who is the first woman to win the Nobel Prize?
- 2.5 What are the repeat laureates?
- 2.6 How old are you when they get the prize?
- 2.7 Age differences between prize categories
- 2.8 Who is the oldest and youngest winners?
In this section, the notebook loads the necessary libraries and imports a dataset of Nobel Prize winners. The dataset is used to answer various questions about the Nobel Prize and its recipients.
This section explores the gender and nationality of Nobel Prize winners. It analyzes the representation of male and female laureates and the top 10 nationalities among the winners.
The notebook investigates when the United States of America started dominating the Nobel Prize charts. It calculates the proportion of USA-born winners per decade.
This section examines the gender imbalance among Nobel Prize winners, including trends across different prize categories. It visualizes the gender proportions for each category over time.
The notebook identifies the first woman to receive a Nobel Prize and determines the category in which she received the award.
This section lists Nobel Prize laureates who have received the award multiple times.
The notebook calculates the age of Nobel Prize winners when they received the award and visualizes the age trends over time.
This section further analyzes age trends but separates the plots for each Nobel Prize category.
The notebook identifies the oldest and youngest individuals to have ever won a Nobel Prize.
This readme provides a brief overview of the analysis performed in the associated Jupyter notebook, which explores various aspects of the Nobel Prize and its recipients. You can refer to the notebook for more detailed information and data visualizations.