Cryptocurrency Market Analytics

This repository contains a project for analyzing cryptocurrency market data. The data was scraped from CoinMarketCap using Selenium and Python. After performing exploratory data analysis (EDA) and visualizations, the insights were compiled into a Tableau public dashboard for interactive exploration.

Overview

The goal of this project was to gain insights into the cryptocurrency market by:

• Scraping live market data from CoinMarketCap using Selenium.
• Performing basic exploratory data analysis (EDA) to uncover trends and patterns.
• Visualizing key metrics like market capitalization, trading volume, and price trends.
• Hosting an interactive dashboard on Tableau Public for easy access and analysis.

Dataset Size

• After cleaning, the dataset contains 8,495 entries.

Tableau Dashboard

Explore the interactive dashboard here: Tableau Public Dashboard

Key Findings

From the visualizations in the Tableau dashboard, here are some key insights:

• Most Expensive Cryptos: The top five most expensive cryptocurrencies have valuations exceeding $100,000, with "Ponzio The Cat" leading at over $35 billion.
• Top Circulating Cryptos: "Trump Inu" and "Tesla AI" have the highest circulating supply among the top 20 cryptocurrencies.
• Most Fluctuated Cryptos: "Fake Official Trump" had the highest fluctuation in a day, peaking at 426.3%.
• Top Trading Volume: "Tether" and "Bitcoin" dominate the market in terms of daily trading volume.
• Volume-to-Price Ratio: Cryptos like "Pepe" and "Shiba Inu" have high trading volumes relative to their price, indicating high liquidity.

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How to Run the Project

Follow these steps to set up and run the project locally.

Prerequisites

Make sure you have the following installed:

• Python 3.7 or above
• pip
• Google Chrome browser
• ChromeDriver (compatible with your Chrome version)

Steps

1. Clone the Repository

   git clone https://github.com/azzusCode/Cryptocurrency-Market-Analytics

2. Set Up a Virtual Environment Create and activate a virtual environment to manage dependencies:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install Dependencies Install the required Python libraries:

   pip install -r requirements.txt

4. Run the Script Start the data scraping process:

   python scraper.py

5. Analyze the Data Use the provided Jupyter Notebook or Python scripts to perform EDA and visualizations.

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Project Files

• scraper.py: Python script to scrape cryptocurrency data from CoinMarketCap.
• Basic_EDA_&_Visualization_of_Crypto_Data.ipynb: Colab Notebook for exploratory data analysis and visualizations.
• Data/: Folder containing the scraped data.
• requirements.txt: File listing all the required Python libraries.
• README.md: Project documentation.

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License

This project is licensed under the MIT License. See the LICENSE file for details.

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Feel free to explore the dashboard and use the code for learning or extending your own projects. Contributions and suggestions are welcome!

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