This project analyzes startup funding data to guide entrepreneurs in selecting the best location and investors for their startups in India. The analysis includes determining the optimal city for launching a startup based on funding history, identifying the most active investors, and refining investor lists to focus on those investing in diverse startups.
startup_funding.csv: Dataset containing funding information for various startups.Case_Study_On_IndianStartups.ipynb: Jupyter notebook with all analyses and visualizations.
To run this notebook, ensure you have Python installed, along with the following libraries:
- Pandas
- NumPy
- Matplotlib
- Install Python and Jupyter Notebook.
- Install required libraries using pip:
pip install pandas numpy matplotlib
- Open the notebook in Jupyter to view the analysis.
- Run each cell sequentially to reproduce the results.
- Data Loading and Cleaning: Initial steps involve loading the dataset and cleaning it for accurate analysis.
- Analysis of Optimal Startup Locations: Analyzing funding frequencies in Bangalore, Mumbai, and NCR to determine the best location for startups.
- Investor Analysis:
- Identifying the most active investors in the ecosystem.
- Refining the list to focus on investors funding multiple unique startups.
Contributions are welcome! Please fork the repository and open a pull request with your enhancements.
This project is licensed under the MIT License - see the LICENSE file for details.