A Python-based project that simulates and processes a large dataset of sales transactions. The script generates random sales data, processes it using pandas, and performs basic analytics on the dataset, such as calculating total sales by category, daily average sales, and standard deviation of sales.
- Simulate sales data: Generate a synthetic dataset of sales transactions, including categories, amounts, and dates.
- Data processing with pandas: Efficiently handle and process large datasets with pandas.
- Basic analytics: Calculate useful statistics like total sales by category, daily average sales, and more.
- Customizable dataset size: Adjust the number of generated records (up to millions of entries) for flexible simulations.
- Easy to modify: Adaptable for various use cases and easy to expand with additional features.
Este proyecto requiere las siguientes bibliotecas de Python:
pandas(para la manipulación de datos)random(para generar datos de ventas aleatorios)datetime(para manejar fechas y horas)
Puedes instalar las bibliotecas necesarias usando pip:
pip install pandas