https://github.com/salma-mamdoh/a-visual-history-of-nobel-prize-winners-project

My project aims to practice Data Analysis and Data Visualization on DataCamp
https://github.com/salma-mamdoh/a-visual-history-of-nobel-prize-winners-project

data-analysis data-visualization datacamp matplotlib pandas python seaborn

Last synced: about 5 hours ago
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My project aims to practice Data Analysis and Data Visualization on DataCamp

• Host: GitHub
• URL: https://github.com/salma-mamdoh/a-visual-history-of-nobel-prize-winners-project
• Owner: Salma-Mamdoh
• Created: 2023-07-25T23:19:18.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-08-20T14:30:37.000Z (about 1 year ago)
• Last Synced: 2023-08-20T15:41:01.474Z (about 1 year ago)
• Topics: data-analysis, data-visualization, datacamp, matplotlib, pandas, python, seaborn
• Language: Jupyter Notebook
• Homepage:
• Size: 1.01 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        


    

    

    
Nobel Prize Analysis 



   
This project involves analyzing a dataset of Nobel Prize winners to gain insights into their demographics, distribution, and trends over time. The dataset contains information about Nobel Prize laureates from 1901 to 2016, including details like birth country, gender, category, and more. The goal of this analysis is to uncover patterns, trends, and significant observations related to Nobel Prize recipients.


   
Table of Contents

    


        
Introduction

        
Dataset Overview

        
Project Structure

        
Data Analysis

        
Findings

        
Conclusion

    


  
Introduction

    
The Nobel Prize is a prestigious international award presented annually to individuals or organizations that have made significant contributions to various fields, including Physics, Chemistry, Medicine, Literature, Peace, and Economics. This project focuses on exploring the Nobel Prize dataset to uncover insights about laureates, including gender distribution, country representation, categories dominance, and historical trends.


   
Dataset Overview

    
The dataset used for this analysis contains information about Nobel Prize laureates and includes various attributes such as:

    


        
Name and surname of the laureate

        
Birth and death dates

        
Birth and death places (countries)

        
Nobel Prize category and year

        
Summary of the laureate's contribution

        
Gender and organization (if applicable)

    

    
The dataset spans from 1901 to 2016 and provides a comprehensive collection of Nobel Prize laureate information for in-depth analysis.


  
Project Structure

    
The project follows a structured organization:

    


        


data/: Contains the dataset files

        


notebooks/: Jupyter notebooks for data cleaning, exploration, visialization and analysis

        


README.md: Documentation about the project (you are here)

    


  
Data Analysis

    
The data analysis process involves several steps:

    


        
Data cleaning: Handling missing values, correcting inconsistencies

        
Exploratory data analysis: Visualizing demographics, categories, trends

        
Statistical analysis: Extracting insights from the data

    


   
Findings

    
After analyzing the dataset, several key findings were discovered:

    


        
Gender distribution among laureates

        
Most awarded countries

        
Dominant Nobel Prize categories

        
Historical trends and changes

    


  
Conclusion

    
The analysis of the Nobel Prize dataset provides valuable insights into the demographics, distribution, and trends of laureates. This project highlights the importance of recognizing contributions across various fields and regions.