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What is SciPy and why should we use it?
SciPy, pronounced as “Sigh Pie”, is an ecosystem of Python open-source libraries for performing Mathematical, Scientific, and Engineering computations. SciPy stands for Scientific Python and is comprised of the following core packages, called SciPy ecosystem −
NumPy − NumPy is a base N-dimensional array package for SciPy that allows us to efficiently work with data in arrays.
Matplotlib − Matplotlib is used to create comprehensive 2-D charts and plots from data.
Pandas − Pandas is an open-source Python package used to organize and analyze our data.
Apart from SciPy ecosystem, there are other related but distinct entities SciPy refers to −
Community − It refers to the community of the people who use and develop this library.
Conferences − There are several conferences named SciPy, EuroSciPy, and SciPy.in which are dedicated to scientific computing in Python.
The SciPy library − It is one of the core packages providing us many userfriendly and efficient numerical routines. The numerical routine includes routine for integration, interpolation, optimization, linear algebra, and statistics.
Why use SciPy
One of the key reasons to use SciPy is that it has optimized the frequently used functions in Data Science. Other reasons include −
There are various issues related to Scientific Computation that arises while working with data science. SciPy provides us with a variety of sub-packages to solve these issues efficiently.
SciPy library has amazingly fast computational power and easy to use.
It can operate an array of NumPy libraries and has also optimized the functions used in NumPy.
After GNU Scientific library, SciPy is one of the most used Scientific libraries.
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