Scipy advanced scientific computing library: It is closely related to Numpy. Scipy generally manipulates Numpy arrays to perform scientific calculations and statistical analysis, so it can be said to be based on Numpy.
Scipy library installation(Recommended learning: Python video tutorial)
pip install scipy
Scipy has many sub-modules that can handle different applications, such as interpolation operations, optimization algorithms, etc. SciPy is a scientific computing package that is more powerful and has a wider range of applications built on the basis of NumPy. It is for this reason that SciPy relies on NumPy support to install and run.
SciPy is the world's famous Python open source scientific computing library, built on Numpy. Its added functions include numerical integration, optimization, statistics and some special functions. The SciPy function library adds many library functions commonly used in mathematics, science and engineering calculations based on the NumPy library. For example, linear algebra, numerical solution of ordinary differential equations, signal processing, image processing, sparse matrices, etc.
SciPy is a Python module built on Numpy that integrates a variety of mathematical algorithms and convenient functions. By providing users with some high-level commands and classes, SciPy greatly increases the ability to manipulate and visualize data in an interactive Python session. With SciPy, an interactive Python session becomes a data processing and system-prototyping environment that rivals MATLAB, IDL, Octave, R-Lab, and SciLab. More importantly, using SciPy in Python, you can also use a powerful language - Python to develop complex and professional programs. Write scientific applications with SciPy and get help from modules developed by developers around the world. From parallel programs to web to database subroutines to various classes, there are already available for Python programmers. SciPy has these powerful functions, especially its mathematics library.
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