scikit-sampling 1.1.0

A set of python modules for dataset sampling

🧪 Scikit-Sampling

Scikit-Sampling (or sksampling) is a Python library for dataset sampling techniques. It provides a unified API for common sampling strategies, making it easy to integrate into your data science and machine learning workflows.

Installation

You can install sksampling using pip:

pip install scikit-sampling

Features

sksampling offers a range of sampling methods, including:

• sample_size: Computes the ideal sample size based on confidence level and margin of error.
• confidence_level: Calculates the confidence level for a given sample size.

Documentation

For detailed information on the library's functions, including parameters and usage examples, please see our documentation in the docs/ folder.

A good place to start is the 📑 Estimation Functions Guide.

We are continuously working on expanding our documentation to cover all features.