Editing Openai/0f04269d-1780-4078-9ff8-63d5ab69403c (section)

====== - Portfolio Management: Tools to manage and optimize stock holdings. ======
* Performance Metrics: Regular reports on stock performance against benchmarks like SP500.

===== <syntaxhighlight lang="python">import pandas as pd =====
import sqlite3  # Replace with the relevant database connector

=== Connect to the database ===
conn = sqlite3.connect('wodor_stocks.db')
cursor = conn.cursor()

=== Example table creation (run once) ===
cursor.execute('''CREATE TABLE IF NOT EXISTS stocks (
                  stock_id INTEGER PRIMARY KEY,
                  stock_name TEXT,
                  current_price REAL,
                  total_revenue REAL)''')
cursor.execute('''CREATE TABLE IF NOT EXISTS transactions (
                  transaction_id INTEGER PRIMARY KEY,
                  stock_id INTEGER,
                  transaction_date DATE,
                  amount REAL,
                  FOREIGN KEY(stock_id) REFERENCES stocks(stock_id))''')
conn.commit()

=== Insert example data (adjust according to your needs) ===
cursor.execute("INSERT INTO stocks (stock_name, current_price, total_revenue) VALUES ('Wodor', 100.0, 1000000.0)")
conn.commit()

=== Calculate revenue royalty ===
def calculate_royalty(revenue, percentage):
    return revenue * (percentage / 100.0)

=== Example data extraction and royalty calculation ===
stock_data = pd.read_sql_query("SELECT * FROM stocks", conn)
stock_data['royalty_7'] = stock_data['total_revenue'].apply(lambda x: calculate_royalty(x, 7))
stock_data['royalty_10'] = stock_data['total_revenue'].apply(lambda x: calculate_royalty(x, 10))

=== Output to CSV ===
stock_data.to_csv('wodor_stock_report.csv', index=False)
print("Report generated successfully.")

=== Close the database connection ===
conn.close()

</syntaxhighlight>