This repository contains a Python program developed to analyze the performance of a U.S. equity fund comprising 150 companies across multiple industries. The analysis is based on the most recent quarterly data and focuses on metrics like debt-to-equity ratio, debt-to-income ratio, and state-wise performance statistics. The program loads data from an Excel file, performs various data processing tasks, and generates insights to help the fund managers rebalance their holdings.
- Data Import: Reads the dataset from an Excel file.
- Duplicate Identification: Detects and removes duplicate records.
- State-wise Grouping: Groups data by company location (state) and calculates descriptive statistics (mean, median, min, max) for key financial metrics.
- Debt-to-Equity Filtering: Filters businesses with negative debt-to-equity ratios.
- Debt-to-Income Ratio Calculation: Calculates the debt-to-income ratio for each company.
- Data Export: Outputs the results into new Excel files for further analysis.
D598 Data Set.xlsx: The dataset containing the financial data for 150 U.S. companies.analysis_script.ipynb: The Jupyter Notebook containing the Python code for data analysis.grouped_statistics.xlsx: The output file containing descriptive statistics for each state.negative_debt_equity.xlsx: The output file containing companies with negative debt-to-equity ratios.updated_with_debt_to_income.xlsx: The final data file, including the calculated debt-to-income ratios.
- Clone the repository:
git clone https://github.com/yourusername/D598-Equity-Fund-Analysis.git
- Open the Jupyter Notebook
analysis_script.ipynb. - Run the notebook to perform the data analysis.
- Python 3.x
- pandas
- numpy
- Jupyter Notebook
- openpyxl (for handling Excel files)
Install the dependencies using:
pip install pandas numpy openpyxl