scikit-sampling 1.0.2

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 confidence level and interval.

Usage

sksampling follows the scikit-learn API, making it intuitive to use.

from sksampling import sample_size

# Example usage
population_size: int = 100_000
confidence_level: float = 0.95
confidence_interval: float = 0.02
sample_size(population_size, confidence_level, confidence_interval) # approx 2345