FabioCaxa / FIFA2023_Dashboard

Interactive Dashboard with the official data from FIFA.

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FIFA 2023 Data Analysis Dashboard ⚽

Welcome to the FIFA 2023 Data Analysis Dashboard! This interactive dashboard provides comprehensive insights into professional football players and clubs based on the official FIFA 2023 dataset.

Overview

The dashboard offers three main sections:

  1. Home: Provides an introduction to the dataset and allows you to access it from Kaggle.
  2. Players: Explore detailed information about individual players, including their club, position, age, physical attributes, market value, and more.
  3. Teams: Dive into team statistics, including player profiles, overall ratings, market values, and contract details.

Features

  • Interactive Selection: Select clubs and players from dropdown menus to view specific data.
  • Visualizations: Visual representations such as images, progress bars, and data tables enhance the user experience.
  • Comprehensive Data: The dataset includes player demographics, physical characteristics, game statistics, contract details, and club affiliations.
  • Valuable Insights: Analyze player attributes, performance metrics, market evaluation, club analysis, player positioning, and player development over time.

How to Run

  1. Install Required Libraries: Make sure you have Python installed on your system. You can install the required libraries by running:

    pip install streamlit pandas
    
  2. Clone the Repository: Clone the repository containing the Streamlit app files:

    git clone https://github.com/FabioCaxa/FIFA2023_Dashboard.git
    
  3. Navigate to the Directory: Move to the directory where the Streamlit app files are located:

    cd FIFA2023_Dashboard
    
  4. Run the Streamlit App: Run the Streamlit app using the following command:

    streamlit run 1_🏠Home.py
    
  5. Access the Dashboard: Once the app is running, access the dashboard by opening the provided URL in your web browser.

Credits

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Interactive Dashboard with the official data from FIFA.


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Language:Python 100.0%