## Python SciPy TutorialSciPy tutorial provides basic and advanced concepts of SciPy. Our SciPy tutorial is designed for beginners and professionals. In this tutorial, we are going to discuss the following topics. - What is SciPy
- SciPy Sub packages
- SciPy Installation
- SciPy Cluster
- SciPy Constant
- SciPy FFTpack
- SciPy Integrate
- SciPy Interpolation
- SciPy I/O
- SciPy Linear Algebra
- SciPy Ndimage
- SciPy Optimize
- SciPy Stats
- SciPy Sparse Matrix
- SciPy Spatial
- SciPy ODR
## What is SciPyThe SciPy is an open-source scientific library of Python that is distributed under a BSD license. It is used to solve the complex scientific and mathematical problems. It is built on top of the Numpy extension, which means if we import the SciPy, there is no need to import Numpy. The It provides many user-friendly and effective numerical functions for numerical integration and optimization. The The ## HistoryPython was expanded in the 1990s to include an array type for numerical computing called numeric. This numeric package was replaced by Numpy (blend of Numeric and NumArray) in 2006. There was a growing number of extension module and developers were interested to create a complete environment for scientific and technical computing. ## Why use SciPy?SciPy contain significant mathematical algorithms that provide easiness to develop sophisticated and dedicated applications. Being an open-source library, it has a large community across the world to the development of its additional module, and it is much beneficial for scientific application and data scientists. ## Numpy vs. SciPyNumpy and SciPy both are used for mathematical and numerical analysis. Numpy is suitable for basic operations such as sorting, indexing and many more because it contains array data, whereas SciPy consists of all the numeric data. Numpy contains many functions that are used to resolve the linear algebra, Fourier transforms, etc. whereas SciPy library contains full featured version of the linear algebra module as well many other numerical algorithms. ## Note: Remember that if you are doing the scientific computing using Python, you should install both Numpy and SciPy. Because many features belong to SciPy rather than the Numpy.## PrerequisiteBefore learning SciPy, you should have a basic understanding of Python and Mathematics. ## AudienceOur SciPy Tutorial is designed to help beginners and professionals. ## ProblemWe assure that you will not find any problem in this SciPy Tutorial. But if there is any mistake, please post the problem in contact form. Next TopicSciPy Sub Packages |