CheatsheetScipy
Scipy is a Python library used for scientific and technical computing. It provides a variety of functions and tools for performing mathematical operations, data analysis, signal processing, optimization, and more. Scipy is built on top of the NumPy library, and provides additional functionality for scientific computing beyond what is available in NumPy.
Scipy includes a wide variety of sub-packages, each with its own set of tools for performing specific tasks. For example, the scipy.optimize package provides tools for optimization and root-finding, while the scipy.signal package provides tools for signal processing and filtering. Other sub-packages include scipy.stats for statistical functions, scipy.integrate for numerical integration, and scipy.linalg for linear algebra operations.
Scipy is designed to be efficient and fast, and provides tools for working with large datasets and for parallel computing. It is also highly extensible and can be easily integrated with other Python libraries, such as Matplotlib and Pandas, making it a popular tool for scientific computing and data analysis in Python.