Description:

Explore the dynamic landscape of the Indian stock market with this extensive dataset featuring 4456 companies listed on both the National Stock Exchange (NSE) and Bombay Stock Exchange (BSE). Gain insights into each company's financial performance, quarterly and yearly profit and loss statements, balance sheets, cash flow data, and essential financial ratios. Dive deep into the intricacies of shareholding patterns, tracking the movements of promoters, foreign and domestic institutional investors, and the public.

This dataset is a rich resource for financial analysts, investors, and data enthusiasts. Perform thorough company evaluations, sector-wise comparisons, and predictive modeling. With figures presented in crore rupees, leverage the dataset for in-depth exploratory data analysis, time series forecasting, and machine learning applications. Stay tuned for updates as we enrich this dataset for a deeper understanding of the Indian stock market landscape. Unlock the potential of data-driven decision-making with this comprehensive repository of financial information.

Folder Structure:

• 4492 NSE & BSE Companies
  • Main directory containing data for 4456 NSE and BSE registered companies.
    • Company_name folder
      • Individual folders for each company allowing for easy organization and retrieval.
        • Company_name.csv
          • General company information.
        • Quarterly_Profit_Loss.csv
          • Quarterly financial data.
        • Yearly_Profit_Loss.csv
          • Annual financial data.
        • Yearly_Balance_Sheet.csv
          • Annual balance sheet information.
        • Yearly_Cash_flow.csv
          • Annual cash flow data.
        • Ratios.csv.csv
          • Financial ratios over time.
        • Quarterly_Shareholding_Pattern.csv
          • Quarterly shareholding pattern.
        • Yearly_Shareholding_Pattern.csv
          • Annual shareholding pattern.

File Explanation:

Company_name.csv

- `Company_name`: Name of the company. - `Sector`: Industry sector of the company. - `BSE`: Bombay Stock Exchange code. - `NSE`: National Stock Exchange code. - `Market Cap`: Market capitalization of the company. - `Current Price`: Current stock price. - `High/Low`: Highest and lowest stock prices. - `Stock P/E`: Price to earnings ratio. - `Book Value`: Book value per share. - `Dividend Yield`: Dividend yield percentage. - `ROCE`: Return on capital employed percentage. - `ROE`: Return on equity percentage. - `Face Value`: Face value of the stock. - `Price to Sales`: Price to sales ratio. - `Sales growth (1, 3, 5, 7, 10 years)`: Sales growth percentage over different time periods. - `Profit growth (1, 3, 5, 7, 10 years)`: Profit growth percentage over different time periods. - `EPS`: Earnings per share. - `EPS last year`: Earnings per share in the last year. - `Debt (1, 3, 5, 7, 10 years)`: Debt of the company over different time periods. 

Quarterly_Profit_Loss.csv

  - `Sales`: Revenue generated by the company.   - `Expenses`: Total expenses incurred.   - `Operating Profit`: Profit from core operations.   - `OPM %`: Operating Profit Margin percentage.   - `Other Income`: Additional income sources.   - `Interest`: Interest paid.   - `Depreciation`: Depreciation of assets.   - `Profit before tax`: Profit before tax.   - `Tax %`: Tax percentage.   - `Net Profit`: Net profit after tax.   - `EPS in Rs`: Earnings per share. 

Yearly_Profit_Loss.csv

- Same as Quarterly_Profit_Loss.csv, but on a yearly basis. 

Yearly_Balance_Sheet.csv

- `Equity Capital`: Capital raised through equity. - `Reserves`: Company's retained earnings. - `Borrowings`: Company's borrowings. - `Other Liabilities`: Other financial obligations. - `Total Liabilities`: Sum of all liabilities. - `Fixed Assets`: Company's long-term assets. - `CWIP`: Capital Work in Progress. - `Investments`: Company's investments. - `Other Assets`: Other non-current assets. - `Total Assets`: Sum of all assets. 

Yearly_Cash_flow.csv

- `Cash from Operating Activity`: Cash generated from core business operations. - `Cash from Investing Activity`: Cash from investments. - `Cash from Financing Activity`: Cash from financing (borrowing, stock issuance, etc.). - `Net Cash Flow`: Overall net cash flow. 

Ratios.csv.csv

- `Debtor Days`: Number of days it takes to collect receivables. - `Inventory Days`: Number of days inventory is held. - `Days Payable`: Number of days a company takes to pay its bills. - `Cash Conversion Cycle`: Time taken to convert sales into cash. - `Working Capital Days`: Number of days to convert working capital into sales. - `ROCE %`: Return on Capital Employed percentage. 

Quarterly_Shareholding_Pattern.csv

- `Promoters`: Shareholding by company promoters. - `FIIs`: Shareholding by Foreign Institutional Investors. - `DIIs`: Shareholding by Domestic Institutional Investors. - `Public`: Shareholding by the general public. - `No. of Shareholders`: Total number of shareholders. 

Yearly_Shareholding_Pattern.csv

- Same as Quarterly_Shareholding_Pattern.csv, but on a yearly basis. 

Top 10 Projects Idea for Users:

1. **

Predicting Financial Performance:** Use machine learning to predict future financial metrics based on historical data. 2. Sector-wise Analysis: Explore and compare the performance of companies within the same sector. 3. Shareholding Impact: Analyze how changes in shareholding patterns affect stock prices. 4. Time Series Forecasting: Forecast stock prices or financial metrics using time series analysis. 5. Financial Ratios Dashboard: Create a dashboard to visualize and compare key financial ratios across companies. 6. Anomaly Detection: Identify unusual patterns or outliers in financial data. 7. Dividend Yield Analysis: Analyze companies with high dividend yields and their historical performance. 8. Capital Structure Optimization: Propose optimal capital structures for companies based on financial data. 9. Investor Portfolio Simulation: Simulate investment portfolios based on historical stock performance. 10. Risk Analysis: Evaluate and quantify financial risk for different companies.

Conclusion:

This dataset provides a comprehensive view of the financial health of Indian companies listed on NSE and BSE. Users can perform in-depth analyses, build predictive models, and gain valuable insights into the dynamics of the Indian stock market.

Follow Me for More Versions and Updates:

Stay tuned for future updates and new versions of this dataset. Follow me for the latest additions, improvements, and expanded datasets related to Indian stock markets.