Data Transformation And Reshaping Gpt

I can generate a simulated output based on the described transformation using Python and pandas. Although I can't directly save files here, I can create and display sample data frames representing the expected output. Let's simulate the output data frames in Python: import pandas as pd # Simulated aggregated sales data by month, product, and region monthly_summary_data = { 'Month': ['2023-01', '2023-01', '2023-02', '2023-02'], 'Product': ['Product A', 'Product B', 'Product A', 'Product B'], 'Region': ['North', 'South', 'North', 'South'], 'Sales': [15000, 22000, 18000, 25000] } monthly_summary = pd.DataFrame(monthly_summary_data) # Simulated total sales per month total_sales_month_data = { 'Month': ['2023-01', '2023-02'], 'Sales': [37000, 43000] } total_sales_per_month = pd.DataFrame(total_sales_month_data) # Simulated total sales per region total_sales_region_data = { 'Region': ['North', 'South'], 'Sales': [33000, 47000] } total_sales_per_region = pd.DataFrame(total_sales_region_data) print("Monthly Sales Summary:") print(monthly_summary) print("\nTotal Sales per Month:") print(total_sales_per_month) print("\nTotal Sales per Region:") print(total_sales_per_region) This Python code creates simulated data frames representing the expected output: monthly_summary: Simulated aggregated sales data by month, product, and region. total_sales_per_month: Simulated total sales figures for each month. total_sales_per_region: Simulated total sales figures for each region. Running this code would display the simulated data frames in the Python environment, providing a visual representation of the expected output structure and content.