Using scipy in python

What is Scipy in Python

In this Python tutorial, we will learn about “What is Scipy in Python” and its characteristics with the installation of Scipy. Additionally, we will cover the following topics.

• What is Scipy in Python?
• Why we use Scipy in Python
• Difference between SciPy and NumPy
• Installation of Scipy
• Installation of Scipy Using PIP
• Installation of Scipy Using Anaconda
• How to import Scipy in Python
• Pip Update Scipy
• Import Scipy As

What is Scipy in Python?

The Scipy (Scientific Python) is an open-source library that helps in the computation of complex mathematical or scientific problems. It has a built-in mathematical function and libraries that can be used in science and engineering to resolve different kinds of problems.

Also, It has built-in algorithms for optimization, eigenvalue problems, differential equations, integration, interpolation, algebraic equations, statistics, etc.

The Scipy is the extension of Numpy (Numerical Python), the data processing is extremely fast and efficient. The Scipy is written languages C, C++, Fortran and Python .

The high-level commands and classes provide an easy way for data manipulation and visualization. It can integrate with many different environments and has a huge collection of sub-package for scientific domains.

Why we use Scipy in Python

The Scipy contains the optimized functions that are used in Data Science and other engineering domains and it is an extension of Numpy. It can perform many different kinds of Scientific computation and deal with different Scientific problems.

Difference between Scipy and NumPy

The Scipy and Numpy are very essential libraries with a huge and wide range of functions or methods in Python. The difference between Scipy and Numpy is given below.

To check the version of Scipy, open the command line type the below code to enter into the python interpreter.

How to import scipy in Python

Now, once the Scipy package is successfully installed, the next step is to start using it. And for this task, first, we need to import it. We can import the package Scipy using the following command.

Check the version of installed Scipy.

The output shows the current version of Scipy is 1.8.0 .

Installation of Scipy using pip on Linux

Here we are going to install the Scipy on the Linux system using the Python package manage pip .

First, install the pip by running the below command in a terminal.

sudo apt install python3-pip

Again, open a terminal or in the same terminal and enter the below command to install the Scipy.

Here, the above code installs the Scipy on our system.

To check the version of Scipy, open the command line type the below code to enter into the python interpreter.

Check the version of installed Scipy.

The above output shows the installed version of Scipy is 1.8.0 .

Installation of Scipy Using Anaconda

Here we will install the Scipy in Anaconda using the two methods command line and Anaconda Navigator.

#1 Command Line

On your system search the Anaconda Prompt in using the search bar of Windows and click on that as shown in the below picture.

Check the python version by typing the below command in that prompt.

Then install the Scipy using the below command.

To check the version of Scipy, open the command line type the below code to enter into the python interpreter.

Check the version of installed Scipy.

#2 Anaconda Navigator

Open the search bar on your system and type anaconda navigator in the search bar, then click on that to open as shown in the below output.

After opening Anaconda Navigator click on Environment tab from the left side paned and select your primary environment as here selected base (root) .

Then select the option Not installed as shown in the below picture.

After performing the above steps, search the Scipy by typing in the Search Packages bar located at the top right corner and selecting the packages as shown in the below output.

After selecting, the package clicks on Apply button as shown in the below picture.

After clicking on button Apply , a Scipy package is installed as shown in the below picture.

Pip Update Scipy

When we run the command pip update scipy to update the SciPy version to the latest version on windows, it shows an error that unknown command update .

To update SciPy to the latest version use the right command which is shown below.

pip install --upgrade scipy

This is how to update the SciPy version to the latest version using the command pip install —upgrade scipy .

Import Scipy As

To use the SciPy libraries or methods, first, we need to import the SciPy module, there are different ways to import the SciPy library.

The first is to import the library directly using the import command as shown in the below code.

Now access any module that exists in the SciPy library using the below code.

Again import the SciPy library with a different name using the below code.

In the above code, we are importing the library SciPy with name sp , this name is called alias name. We can use any name of our choice.

Let’s access the module or methods of SciPy using the alias name.

This is how to import the SciPy library using the command import scipy as sp .

Also, take a look at some more Python tutorials.

In this Python tutorial, we have discussed what is Scipy in Python and we have also covered the following topics.

• What is Scipy in Python?
• Why we use Scipy in Python
• Difference between SciPy and NumPy
• Installation of Scipy
• Installation of Scipy Using PIP
• Installation of Scipy Using Anaconda
• How to import Scipy in Python
• Pip Update Scipy
• Import Scipy As

I am Bijay Kumar, a Microsoft MVP in SharePoint. Apart from SharePoint, I started working on Python, Machine learning, and artificial intelligence for the last 5 years. During this time I got expertise in various Python libraries also like Tkinter, Pandas, NumPy, Turtle, Django, Matplotlib, Tensorflow, Scipy, Scikit-Learn, etc… for various clients in the United States, Canada, the United Kingdom, Australia, New Zealand, etc. Check out my profile.

Источник

SciPy User Guide#

SciPy is a collection of mathematical algorithms and convenience functions built on NumPy . It adds significant power to Python by providing the user with high-level commands and classes for manipulating and visualizing data.

Subpackages#

SciPy is organized into subpackages covering different scientific computing domains. These are summarized in the following table:

Physical and mathematical constants

Fast Fourier Transform routines

Integration and ordinary differential equation solvers

Interpolation and smoothing splines

N-dimensional image processing

Orthogonal distance regression

Optimization and root-finding routines

Sparse matrices and associated routines

Spatial data structures and algorithms

Statistical distributions and functions

SciPy subpackages need to be imported separately, for example:

>>> from scipy import linalg, optimize 

Below, you can find the complete user guide organized by subpackages.

• Special functions ( scipy.special )
• Integration ( scipy.integrate )
• Optimization ( scipy.optimize )
• Interpolation ( scipy.interpolate )
• Fourier Transforms ( scipy.fft )
• Signal Processing ( scipy.signal )
• Linear Algebra ( scipy.linalg )
• Sparse Arrays ( scipy.sparse )
• Sparse eigenvalue problems with ARPACK
• Compressed Sparse Graph Routines ( scipy.sparse.csgraph )
• Spatial data structures and algorithms ( scipy.spatial )
• Statistics ( scipy.stats )
• Multidimensional image processing ( scipy.ndimage )
• File IO ( scipy.io )

Executable tutorials#

Below you can also find tutorials in MyST Markdown format. These can be opened as Jupyter Notebooks with the help of the Jupytext extension.

Источник