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| # Financial Metrics Calculator.ipynb | |
| import pandas as pd | |
| import json | |
| import numpy as np | |
| class FinancialMetricsCalculator: | |
| def __init__(self): | |
| print("Initializing Financial Metrics Calculator...") | |
| def clean_number(self, value): | |
| """Clean and convert numerical values""" | |
| try: | |
| if isinstance(value, str): | |
| value = value.replace('$', '').replace(',', '').strip() | |
| if '(' in value and ')' in value: | |
| value = '-' + value.replace('(', '').replace(')', '') | |
| return float(value or 0) | |
| except: | |
| return 0.0 | |
| def is_valid_markdown(self, file_path): | |
| """Check if a file is a valid Markdown file""" | |
| try: | |
| with open(file_path, 'r') as f: | |
| content = f.read() | |
| return any(line.startswith('#') or '|' in line for line in content.split('\n')) | |
| except: | |
| return False | |
| def parse_financial_data(self, content): | |
| """Parse markdown content into structured data""" | |
| try: | |
| data = {} | |
| current_section = "" | |
| current_table = [] | |
| headers = None | |
| for line in content.split('\n'): | |
| if line.startswith('#'): | |
| if current_table and headers: | |
| data[current_section] = self.process_table(headers, current_table) | |
| current_section = line.strip('# ') | |
| current_table = [] | |
| headers = None | |
| elif '|' in line: | |
| if '-|-' not in line: | |
| row = [cell.strip() for cell in line.split('|')[1:-1]] | |
| if not headers: | |
| headers = row | |
| else: | |
| current_table.append(row) | |
| if current_table and headers: | |
| data[current_section] = self.process_table(headers, current_table) | |
| return data | |
| except Exception as e: | |
| print(f"Error parsing financial data: {str(e)}") | |
| return {} | |
| def process_table(self, headers, rows): | |
| """Process table data into structured format""" | |
| try: | |
| processed_data = {} | |
| for row in rows: | |
| if len(row) == len(headers): | |
| item_name = row[0].strip('*').strip() | |
| processed_data[item_name] = {} | |
| for i, value in enumerate(row[1:], 1): | |
| processed_data[item_name][headers[i]] = self.clean_number(value) | |
| return processed_data | |
| except Exception as e: | |
| print(f"Error processing table: {str(e)}") | |
| return {} | |
| def get_nested_value(self, data, section, key, year): | |
| """Safely get nested dictionary value""" | |
| try: | |
| return data.get(section, {}).get(key, {}).get(str(year), 0) | |
| except: | |
| return 0 | |
| def extract_metrics(self, income_data, balance_data): | |
| """Extract and calculate key financial metrics""" | |
| try: | |
| metrics = { | |
| "Revenue": { | |
| "2025": self.get_nested_value(income_data, "Revenue", "Total Net Revenue", "2025"), | |
| "2024": self.get_nested_value(income_data, "Revenue", "Total Net Revenue", "2024"), | |
| "2021": self.get_nested_value(income_data, "Revenue", "Total Net Revenue", "2021") | |
| }, | |
| "Profitability": { | |
| "Gross_Profit_2025": self.get_nested_value(income_data, "Cost and Gross Profit", "Gross Profit", "2025"), | |
| "EBIT_2025": self.get_nested_value(income_data, "Profit Summary", "EBIT", "2025"), | |
| "Net_Earnings_2025": self.get_nested_value(income_data, "Profit Summary", "Net Earnings", "2025"), | |
| "Operating_Expenses_2025": self.get_nested_value(income_data, "Operating Expenses", "Total Operating Expenses", "2025") | |
| }, | |
| "Balance_Sheet": { | |
| "Total_Assets_2025": self.get_nested_value(balance_data, "Key Totals", "Total_Assets", "2025"), | |
| "Current_Assets_2025": self.get_nested_value(balance_data, "Key Totals", "Total_Current_Assets", "2025"), | |
| "Total_Liabilities_2025": self.get_nested_value(balance_data, "Key Totals", "Total_Liabilities", "2025"), | |
| "Current_Liabilities_2025": self.get_nested_value(balance_data, "Key Totals", "Total_Current_Liabilities", "2025"), | |
| "Equity_2025": self.get_nested_value(balance_data, "Key Totals", "Total_Shareholders_Equity", "2025"), | |
| "Inventory_2025": self.get_nested_value(balance_data, "Balance Sheet Data 2021-2025", "Inventory", "2025"), | |
| "Accounts_Receivable_2025": self.get_nested_value(balance_data, "Balance Sheet Data 2021-2025", "Accounts_Receivable", "2025"), | |
| "Long_Term_Debt_2025": self.get_nested_value(balance_data, "Balance Sheet Data 2021-2025", "Long_Term_Debt", "2025") | |
| }, | |
| "Cash_Flow": { | |
| "Depreciation_2025": self.get_nested_value(income_data, "Operating Expenses", "Depreciation & Amortization", "2025"), | |
| "Interest_Expense_2025": self.get_nested_value(income_data, "Profit Summary", "Interest Expense", "2025") | |
| } | |
| } | |
| revenue_2025 = metrics["Revenue"]["2025"] | |
| if revenue_2025 != 0: | |
| metrics["Ratios"] = self.calculate_financial_ratios(metrics, revenue_2025) | |
| return metrics | |
| except Exception as e: | |
| print(f"Error extracting metrics: {str(e)}") | |
| return {} | |
| def calculate_financial_ratios(self, metrics, revenue): | |
| """Calculate financial ratios""" | |
| return { | |
| "Gross_Margin": (metrics["Profitability"]["Gross_Profit_2025"] / revenue) * 100, | |
| "Operating_Margin": (metrics["Profitability"]["EBIT_2025"] / revenue) * 100, | |
| "Net_Margin": (metrics["Profitability"]["Net_Earnings_2025"] / revenue) * 100, | |
| "Current_Ratio": metrics["Balance_Sheet"]["Current_Assets_2025"] / metrics["Balance_Sheet"]["Current_Liabilities_2025"] if metrics["Balance_Sheet"]["Current_Liabilities_2025"] != 0 else 0, | |
| "Quick_Ratio": (metrics["Balance_Sheet"]["Current_Assets_2025"] - metrics["Balance_Sheet"]["Inventory_2025"]) / metrics["Balance_Sheet"]["Current_Liabilities_2025"] if metrics["Balance_Sheet"]["Current_Liabilities_2025"] != 0 else 0, | |
| "Asset_Turnover": revenue / metrics["Balance_Sheet"]["Total_Assets_2025"] if metrics["Balance_Sheet"]["Total_Assets_2025"] != 0 else 0, | |
| "Receivables_Turnover": revenue / metrics["Balance_Sheet"]["Accounts_Receivable_2025"] if metrics["Balance_Sheet"]["Accounts_Receivable_2025"] != 0 else 0, | |
| "Debt_to_Equity": metrics["Balance_Sheet"]["Total_Liabilities_2025"] / metrics["Balance_Sheet"]["Equity_2025"] if metrics["Balance_Sheet"]["Equity_2025"] != 0 else 0, | |
| "Interest_Coverage": metrics["Profitability"]["EBIT_2025"] / metrics["Cash_Flow"]["Interest_Expense_2025"] if metrics["Cash_Flow"]["Interest_Expense_2025"] != 0 else 0, | |
| "Revenue_Growth": ((metrics["Revenue"]["2025"] / metrics["Revenue"]["2024"]) - 1) * 100 if metrics["Revenue"]["2024"] != 0 else 0, | |
| "5Year_Revenue_CAGR": ((metrics["Revenue"]["2025"] / metrics["Revenue"]["2021"]) ** (1/4) - 1) * 100 if metrics["Revenue"]["2021"] != 0 else 0 | |
| } | |
| def process_financial_statements(self, balance_sheet_file, income_stmt_file): | |
| """Process financial statements and return metrics""" | |
| try: | |
| if not (self.is_valid_markdown(balance_sheet_file) and self.is_valid_markdown(income_stmt_file)): | |
| return "Error: Invalid file format" | |
| with open(balance_sheet_file, 'r') as f: | |
| balance_sheet = f.read() | |
| with open(income_stmt_file, 'r') as f: | |
| income_stmt = f.read() | |
| income_data = self.parse_financial_data(income_stmt) | |
| balance_data = self.parse_financial_data(balance_sheet) | |
| metrics = self.extract_metrics(income_data, balance_data) | |
| return metrics | |
| except Exception as e: | |
| print(f"Error processing statements: {str(e)}") | |
| return None | |
| # Example usage | |
| if __name__ == "__main__": | |
| calculator = FinancialMetricsCalculator() | |
| # Test with your markdown files | |
| metrics = calculator.process_financial_statements('balance_sheet.md', 'income_statement.md') | |
| print(json.dumps(metrics, indent=2)) | |