Global Chess Trends Explorer Project

Analysis of the top 100 players from every nation

Overview

This project leverages FIDE (International Chess Federation) data to provide interactive insights into chess player performance and trends over the past 5 years. The application updates monthly to incorporate the latest data and remains a work in progress as additional features and final deployment, are being developed. To see a preview click here!

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Features

• Monthly updates to keep the insights current.
• Analysis of the top 100 chess players from each country.
• Interactive visualizations and data filtering options.
• Tools to compare countries, analyze trends, and view top players dynamically.

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1. Data Collection

• Data sourced directly from the FIDE website, updated monthly.
• Downloaded data spanning 5 years, resulting in 60 text files with comprehensive player details.

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2. Data Cleaning and Preprocessing

• Extracted data for the top 100 players per country.
• Consolidated all extracted data into a single dataset for further analysis.
• Processed using Python and Jupyter Notebook.

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3. Database Design and Setup

• Designed a PostgreSQL database with the following normalized structure:
  • Players: Stores static player information (e.g., name, birthdate).
  • Countries: Stores geographic data (e.g., continent, subregion).
  • MonthlyUpdates: Contains dynamic player data (e.g., rating, activity status) that changes monthly.

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4. Data Aggregation and Analysis

• Utilized DBeaver, Python, and SQLAlchemy to analyze and extract insights.
• Key queries and functions include:
  • Median ratings, titled player counts, and Grandmasters per country.
  • Gender, age group, and rating distributions over time.
  • Player activity status percentages.
  • Participation trends by continent.

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5. Streamlit Application Development

Learned Streamlit through a course from ALURA LATAM and developed a 6-page interactive web application:

1. Introduction: Overview of the project.
2. Outlook: High-level data summary and key insights.
3. Continent Analysis: Regional performance and trends.
4. Comparison Tool: Compare two countries/regions across a selected period.
5. Top 5 Chess Players: Dynamic bar chart race showing top players over time.

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6. Visualization and Interaction

• Built dynamic and interactive visualizations using Plotly and Bar Chart Race:
  • Rating trends, distributions, and player participation by gender and country.
  • Bar chart races for engaging visual storytelling.
• Integrated filter options to refine insights by:
  • Gender
  • Rating range
  • Country
  • Title
  • Activity status

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7. Deployment (In Progress)

• Currently working on finalizing the deployment strategy to make the app accessible online.

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Future Work

• Finalize deployment to make the application publicly accessible.
• Explore additional features to enhance user interaction and insights.

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This project combines data science, database management, and interactive web development to provide valuable insights into the chess world. Stay tuned for updates as new features are added!