Python for data analytics #1

 What is Python and why it is used?

Python is a computer programming language often used to build websites and software, automate tasks, and conduct data analysis.

Python is a general-purpose language, meaning it can be used to create a variety of different programs and isn't specialized for any specific problems.

Python is an interpreted, interactive, object-oriented programming language. It incorporates modules, exceptions, dynamic typing, very high level dynamic data types, and classes. 

It supports multiple programming paradigms beyond object-oriented programming, such as procedural and functional programming.

Why Python is best for data analysis?

Python is one of the top most languages. It is used primarily for performing data analysis. One of the main factors why it is used for the analysis of data is because of the superb Python ecosystem. There are tons of data-centric Python packages which make the process of data analysis a lot quick and convenient.

For a small amount of data we can use microsoft excel.

Excel is spreadsheet which is platform compatible means it can be run in different operating systems.

Microsoft Excel enables users to format, organize and calculate data in a spreadsheet. By organizing data using software like Excel, data analysts and other users can make information easier to view as data is added or changed.

But when we want to analyse big data then spreadsheets are complex to manage large amount of data.

Python provides better tools and packages to analyse large amount of data.It can easily replace mundane tasks with automation.

Python also offers greater efficiency and scalability. It's faster than Excel for data pipelines, automation and calculating complex equations and algorithms.