time-series-features

What problem does it solve?

This Skill provides tools and guidance for crafting high-quality features from time-series data, crucial for forecasting, machine learning models, and data science analysis.

Core Features & Use Cases

• Feature Engineering: Offers a variety of classical feature engineering techniques tailored for time-series data, such as lags, rolling windows, and point-process features.
• Avoiding Leakage: Helps to create time-series datasets without future leakage, suitable for various predictive modeling tasks like demand forecasting and sales prediction.
• Use Case: With this Skill, a data scientist can generate features from retail sales data to feed into a machine learning model for demand prediction.

Quick Start

Analyze the sales data of the past week by running the script analyze_sales.py.