Python Tutorial

Introduction Python Features Python Applications System requirements for Python Python Installation Python Basics Python Variables Python Data Types Python IDE Python Keywords Python Operators Python Comments Python Pass Statement

Python Conditional Statements

Python if Statement Python elif Statement Python If-else statement Python Switch Case

Python Loops

Python for loop Python while loop Python Break Statement Python Continue Statement Python Goto Statement

Python Arrays

Python Array Python Matrix

Python Strings

Python Strings Python Regex

Python Built-in Data Structure

Python Lists Python Tuples Python Lists vs Tuples Python Dictionary Python Sets

Python Functions

Python Function Python min() function Python max() function Python User-define Functions Python Built-in Functions Anonymous/Lambda Function in Python

Python File Handling

Python File Handling Python Read CSV Python Write CSV Python Read Excel Python Write Excel Python Read Text File Python Write Text File Read JSON File in Python

Python Exception Handling

Python Exception Handling Python Errors and exceptions Python Assert

Python OOPs Concept

OOPs Concepts in Python Classes & Objects in Python Inheritance in Python Polymorphism in Python Python Encapsulation Python Constructor Static Variables in Python Abstraction in Python

Python Iterators

Iterators in Python Yield Statement In Python

Python Generators

Python Generator

Python Decorators

Python Decorator

Python Functions and Methods

Python Built-in Functions Python String Methods Python List Methods Python Dictionary Methods Python Tuple Methods Python Set Methods

Python Modules

Python Modules Python Datetime Module Python Calendar Module  

Python MySQL

Python MySQL Python MySQL Update Operation Python MySQL Delete Operation

Python MongoDB

Python MongoDB

Python Data Structure Implementation

Python Stack Python Queue Python Hash Table Python Graph

Python Advance Topics

Speech Recognition in Python Face Recognition in Python Python Rest API Python Command Line Arguments Python JSON Python Virtual Environment Type Casting in Python Collections in python Python Enumerate Python Debugger Python DefaultDict


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How to

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Python Sort List Sort Dictionary in Python Python sort() function Python Bubble Sort


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How to Install Python In Windows

How To Install Python In Windows?

Python is a language that every aspirant developer looks forward to. One thing we must keep in our mind is how to begin our hands-on practice with Python. So, first and foremost we should ensure that Python is installed on our PCs.

Today we will discuss the steps of installing Python-

  1. Go to the website “”
  2. You will find the ‘Downloads’ tab there and click on it to get the information related to the current version.
  3. On clicking that, an executable file of Python will be downloaded.
  4. In the ‘Downloads’ folder, you will find the file and click on it for installation.
  5. You will see the installation setup window of Python on your screen.
  6. Click on Install Now
  7. On clicking this, a dialog box would appear named ‘User Account Control’, it will ask you ‘Do you want to make changes to your device?”.
  8. Click on ‘Yes’ to start the installation process.
  9. Once it is installed, we need an IDE (Integrated Development Environment) to write our programs in Python.
  10. An IDE can help us to integrate the text editor with other essential features that can help in implementing various projects that earlier required complex coding.

There are many IDEs available that can provide us a humble beginning in this amazing universe of python programming.

  • Python IDLE
  • Spyder IDE
  • Jupyter Notebook
  • PyCharm

Let’s talk about the characteristics and installation of each IDE in detail-

Python IDLE

  • It has an interactive interpreter
  • It highlights the syntax
  • It has the feature of smart indentation
  • It formats the code automatically
  • It supports debugging

Installation of Python IDLE

  1. Look for the ‘Windows’ downloads and choose your system architecture.
  2. The next step is to run the installer and go through the prompts. This installs IDE.

Spyder IDE

1.  Advance editing options are available

2.  Tools like Numpy, Matplotlib, and scipy are available.

3.  Python & IPython consoles can work at the same time.

4.  Inserts colon after if & while automatically

5.  Supports the magic commands of IPython

Installation of Spyder IDE

  1. Go to the official website of Spyder.
  2. Select ‘Download’ from the menu.
  3. Click on the ‘Download Spyder with Anaconda’ button.
  4. This will direct you to the next screen where you will be asked to choose the operating system.
  5. Select the version of Python you want to download.
  6. Once you have downloaded the installer, a setup window will appear on your screen.
  7. Click the 'Next button.
  8. Click on ‘I Agree’ in the License Agreement
  9. Click on ‘Next’ to proceed in the further dialog boxes.
  10. Once you reach the required page, click on the 'Install' button.
  11.  The installation process will start after this.

Jupyter Notebook

1. Feature of markdown markup language that can describe code.

2. It can provide a piece of complete information about our project using description through formatted text, visual representation of our analysis, and mathematical functions.

3. Notebook maintains the privacy of our data.

4. The kernel present in Jupyter notebooks provides support to multiple languages.

5. It provides amazing features and tools for Data Science projects.

Installation of Jupyter Notebook

  1. The process of installation remains the same as Spyder IDE, what we need to do here is install Anaconda distribution.
  2. Select the operating system of your choice.
  3. The .exe installer will be downloaded.
  4. Open and execute the installer and launch the Anaconda Navigator.
  5. The installation process would then start and the packages will be loaded.
  6. We can check the version using the pip command in Anaconda Prompt.


1. Smart code editor that provides writing high-quality Python codes.

2.  Tools enhance code productivity.

3. It supports scientific libraries that can help in accomplishing Data Science & Machine Learning projects.

4.  It provides a good environment for testing and debugging.

5. The refactoring feature allows us to change the internal structure of the program and it doesn’t impact its external performance.

Installation of PyCharm 

  1. Visit the official website of Jetbrains to download PyCharm.
  2. It is available in two versions-
  3. Professional – It is used by professional developers.
  4. Community- It is open-source and used for learning Python applications.
  5. Click on the ‘Download’ button and choose ‘Community’ in the window that appears below.
  6. Download the ‘Community’ version.
  7. Keep clicking on ‘Next’ in the dialog boxes that will appear in series during the installation process.
  8. Click on ‘install’ to start the process and then click on ‘Finish’ once the installation process completes.