SciPy

Built on top of NumPy, SciPy extends its functionality by offering a large number of scientific and technical computing features such as optimization, statistics, integration, interpolation, and Fourier transforms. It is an essential component of the Python scientific computing ecosystem, widely used in engineering, mathematics, scientific research, and more.

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NumPy

NumPy is a fundamental package for scientific computing with Python. It provides a powerful N-dimensional array object, sophisticated broadcasting functions, tools to integrate C/C++ and Fortran code, and useful linear algebra, Fourier transform, and random number capabilities. NumPy is essential in the field of data science due to its efficiency and flexibility.

Pandas

Pandas is an open-source library providing high-performance, easy-to-use data structures and data analysis tools for Python. With DataFrame and Series data structures, it simplifies data cleaning and analysis. Supporting loading data from various sources, handling missing data, and time series functionalities, Pandas significantly streamlines the data processing workflow.

SymPy

SymPy is a Python library for symbolic mathematics, capable of performing symbolic computations in areas like algebra, calculus, discrete mathematics, and geometry. Its goal is to become a full-featured computer algebra system (CAS) while keeping the code as simple and comprehensible as possible.