Data Analysis on Indian Startups

📌 Overview

This project focuses on analyzing Indian startups using a dataset containing various attributes such as funding amount, industry sector, location, and funding sources. The analysis aims to uncover trends and insights about the startup ecosystem in India.

🚀 Features

• ✅ Data Cleaning and Preprocessing
• 📊 Exploratory Data Analysis (EDA)
• 📈 Visualization of funding trends
• 🏭 Industry-wise startup analysis
• 📍 Location-based startup distribution
• 🔍 Insights and conclusions

📦 Requirements

To run this project, you need the following dependencies:

pip install pandas numpy matplotlib seaborn

Run the cells sequentially to process the data and generate insights. Analyze the visualizations to understand trends in Indian startups.

📂 Dataset

The dataset contains information on:

• 🏢 Name of the startup
• 🏭 Industry sector
• 💰 Funding amount
• 🤝 Investor details
• 📍 City and state location
• 🔄 Funding rounds

📊 Results

Key findings include:

• 📌 Most funded sectors and their trends.
• 🗺️ Geographical distribution of startups.
• 🤝 Common investors and funding patterns.

🚀 Future Improvements

• 📈 Expanding the dataset with recent startup data.
• 🧠 Applying machine learning for predictive analytics.
• 🔄 Integrating real-time funding updates.

📜 License

This project is open-source and available under the MIT License.

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