This is a personal project where I conducted an exploratory analysis on the market of Non-Fungible Tokens (NFTs). NFTs have gained immense popularity in recent years, and I wanted to delve into the data to understand the trends, prices, changes, transactions, and mints associated with this emerging market. The project aimed to provide insights into the NFT market and visualize the data using various tools.

The motivation behind this project was the hype surrounding Web3 and NFTs at the time. With the growing interest in blockchain technology and digital assets, NFTs emerged as a unique concept with the potential to revolutionize ownership and provenance. I wanted to get a firsthand experience of the NFT market and leverage the tools available to me to perform a comprehensive analysis.

To conduct the analysis, I utilized the following tools:

• Pandas: Pandas is a powerful Python library for data manipulation and analysis. I used it to clean and preprocess the raw data, handle missing values, and perform various computations.

• Plotly Express: Plotly Express is a high-level data visualization library built on top of Plotly. It offers a simple and intuitive interface for creating interactive visualizations. I utilized Plotly Express to generate insightful charts and graphs to represent the NFT market data.

• Streamlit: Streamlit is a Python library that allows you to create interactive web applications with ease. I leveraged Streamlit to develop a visualization dashboard where users can explore the NFT market data interactively.

This exploratory analysis project includes the following features:

• Data collection and preprocessing: I gathered data from various sources related to NFTs and performed necessary preprocessing steps such as cleaning, handling missing values, and data transformation.

• Price analysis: I analyzed the price trends of NFTs over a specific period. This analysis helped to identify patterns and outliers in the market.

• Changes analysis: I examined the changes in NFT prices and identified significant price movements. This analysis aimed to understand the volatility and market dynamics.

• Transaction analysis: I explored the transaction data associated with NFTs to gain insights into buyer and seller behavior, trading volume, and popular marketplaces.

• Mint analysis: I investigated the mints of NFTs to identify popular creators, trends in minting activity, and potential influencers in the market.

• Visualization dashboard: I developed a user-friendly dashboard using Streamlit, where users can interact with the visualizations and explore different aspects of the NFT market.

Through this exploratory analysis project, I gained valuable insights into the NFT market. By analyzing the prices, changes, transactions, and mints of NFTs, I was able to observe trends, identify key players, and understand the dynamics of this rapidly evolving market. The use of tools like pandas, plotly express, and streamlit allowed me to perform data analysis efficiently and present the findings in an interactive manner.

The project served as a stepping stone to better comprehend the potential of Web3 and NFTs. It also provided a foundation for further