In this era of data-driven innovations, the demand for diverse, high-quality, reliable data is constantly rising. However, accessing and utilizing real-world data can often be challenging due privacy ...

Music has become an established complementary element of modern medicine, demonstrating beneficial effects towards various diseases such as dementia, hypertension, or chronic pain. Given its low cost ...

Minimalist plotting for Python, inspired by Edward Tufte’s principles of data visualization. Maximising the data–ink ratio: remove non-essential lines, marks, and colours. Content-driven spines and ...

The triangular distribution is a continuous probability distribution widely used in scenarios with limited data, such as project management, risk analysis, and Monte Carlo simulations. Its named for ...

Decarbonatization initiatives have rapidly increased the demand for lithium. This study uses public waste compliance reports and Monte Carlo approaches to estimate total lithium mass yields from ...

Isotopic composition modelling is a key aspect in many environmental studies. This work presents Isocompy, an open source Python library that estimates isotopic compositions through machine learning ...

The Empirical Cumulative Distribution-based Outlier Detection (ECOD) has a very intuitive approach: Outliers are the rare events in the tails of a distribution, they can be identified by measuring the ...

Thompson Sampling is an algorithm that can be used to analyze multi-armed bandit problems. Imagine you're in a casino standing in front of three slot machines. You have 10 free plays. Each machine ...

Diffusion Imaging in Python (Dipy) is a free and open source software project for the analysis of data from diffusion magnetic resonance imaging (dMRI) experiments. dMRI is an application of MRI that ...