## What is SciPy in Python?

An open-source toolset called SciPy, pronounced “sigh pie,” is used primarily in engineering, mathematics, and scientific computing. It is based on the Python Numpy extension and offers a lot of useful modules for Signal- and image processing, integration, optimization, linear algebra, Fourier transforms, statistics and many other topics.

SciPy can be easily installed on all common operating systems based on Linux. Using the Pip package manager, in this tutorial we will walk you through the process of installing SciPy on a virtual private Linux server. The following section discusses pip in more detail.

SciPy is neatly organized into sub-packages that address many areas of scientific computing. clusters, constants, integrate, io, linalg, SignalSparse, Stats, etc. are some of them.

## What is NumPy in Python?

An open source library for the Python programming language is called NumPy (Numerical Python). It is used in array manipulation and scientific computing. In addition to being a multidimensional array object, it provides high-level array manipulation capabilities.

NumPy is based on linear algebra. It involves performing mathematical operations on matrices and vectors. Basic operations like average, minimum, maximum, standard deviation, variance and many more are supported by NumPy.

Pip’s command line can be used to install NumPy once it has been configured. Enter the below given command to install NumPy with Python 2.

The package manager for Python is named pip by default. Additional packages not included by default in Python’s standard library are also available for installation.

## How do I install Scipy on Linux?

SciPy can usually be installed on a Linux computer using one of two simple techniques. The first is as simple as using the built-in package manager that comes with Linux installation. The second is as complex as using pip, the Python package manager. To install SciPy, use the single command of either method.

## Install scipy via pip command

The Python package manager that pip used to install and update packages. Python’s standard library contains several built-in functions.

Statsmodel and other data science libraries like scikit-learn are NOT part of the Python standard library. They can be set up using the command line and pip, the default package manager for Python.

This approach explains how to install Scipy using the pip command. Launch the command prompt terminal on your PC. You can launch Command Prompt on Windows, Terminal on Mac, or the Linux terminal that comes with your Linux distribution.

After typing, run “python -m pip install -U pip”. By using this command you can ensure that your system has the latest pip files installed for use in managing packages.

At the command prompt, type “pip install scipy” and run it. The main SciPy packages are installed on your computer using the Python package index. The “pip install numpy” and “pip install matplotlib” commands can be used to install other core packages such as numpy and matplotlib.

Below is the result of running the “pip install scipy” command.

## Install Scipy using the package manager command

The easy installation instructions for Python-Scipy on Ubuntu Server can be found here. Try clicking the Copy button to capture the command and place it in your command prompt terminal if you want to use the built-in APT package manager.

For a quick step-by-step guide to SSH commands, see the details below. Copy/paste is recommended to avoid typos and unintentional package installations.

Run the update command to update package repositories and get the latest package information.

Issue the install command with the -y parameter to install the packages and dependencies.

## Example:

Since the libraries were installed in a virtual environment, you will now get a ModuleNotFoundError error if any of the modules for NumPy, SciPy, Matplotlib, etc. are not installed successfully. We can evaluate ScipPy and Matplotlib by creating the small test program below.

You can see in the code that the first two modules added are scipy and matplotlib. With features to control line styles, font attributes, formatting axes, and other features, it provides a module called pyplot that simplifies plotting. Let’s examine each line of code in detail.

The import scipy command was used to import the scipy module in the first line of code. The matplotlib library is then loaded as plt. A variable was then constructed using the “arrange()” method, in which the graph specification was given. One of the most commonly used Python functions is the arrange() function. After creating equidistant values, the arrange() method returns the reference to those values.

In the last line of code, we displayed the plot using the show() method.

Here is the output screen showing the chart. This demonstrates the installation of your system and the successful operation of the SciPy module.

## Conclusion:

How to install Scipy has been covered in this post. Several features are included in the SciPy installation. The package has a code return that can be used to access the functions contained in its subpackages. Installation of this package is required to use Python’s features. Due to the open source nature of the package, there is huge potential for growth. There are several installation methods available to you. Depending on your needs, we can make full use of it.