Python is a general-purpose programming language (in technical terms). Let me tell you one secret thing for Python there is no easiest way to learn Python (seems not good). I think you people are in shock right! Bye the way I was just kidding. According to the Python experts, it is the easiest programming language to learn and implement in the production. Some people learn Python for creating websites and other might be created apps. Like this, so many peoples are learning Python for a different purpose. Once Peoples start to learn Python they get a high level of proficiency. The main agenda of this blog is Why should we learn Python for Data Science. Through this blog learn Python for Data Science.

If you have to learn this language, then Get in touch with Python Online Training you create amazing things by using Python.

What is Python?

The word Python is taken from the Guido favorite television show “Monty Python’s Flying Circus”. In this language no worries about if anyone is new to the programming or have been experts in other languages. It requires unique syntax that focuses on readability. So, developers can read and translate Python code very easily compare to other programming languages. It can support different operating systems like Linux, Mac-OS, and Windows. According to the Indeed Job, Python is the widely used language in all software companies. Many industries can use Python to automate the complicated task of such companies are Google, Instagram, YouTube, NASA is using Python as a back-end development. It is the most important language in Data Science. If anyone is going to learn Data Science, it’s mandatory to meet with Python.

Here popular 3 main reasons:

It’s very fair easy to interpret and learn

It can handle different data structures

It has very powerful data visualizations and statistical libraries.

About Data Science:

Data Science has been floating for the better part last 30 years and it can be used to substitution for “computer science” in 1960. 15 years later the term is used for data processing in several applications. According to the review of Harvard Business article in 2012, calling Data Science as “popular job for the 21st century”.

Before the Data Science trend, peoples who used to work with data are called Computer Scientists, Bussiness Analysts, and Statisticians. Now they are called Data Scientists. Data Scientists are peoples who work on making data useful in various ways with a mix of coding and statistical skills. It is a big field for Big Data which provides meaning information for all large amount of complex data. It helps the company improvement like collects, analyze, and interprets large volume of data. Data Science professionals implement statistical models to analyze the data and use different analytics find trends, patterns, and relationship with datasets. Nowadays, through Data Science companies are employing big data to give good result to the customers. Banking Institutes are taking an advantage on big data to increase their fraud detection successes. Let’s come to the point on which we discuss these matter Python for Data Science.

Python for Data Science:Python for Data Science

When it’s come to learn data coding, we should take a view on below languages

SQL

Python

R

Bash

Yes, it’s very good to know four languages for Data Science. But Somebody is new to the coding for those members pick up Python. Using this language almost Data Science will complete. Now see why is it benefit learning Python for Data Science? Python is very easy and fun. It suitable many packages for simpler Analytics projects (eg: explorative analytics, segmentation, etc.) for Advanced Data Science (eg: building machine learning models). Nowadays job markets require more peoples on data professionals with good Python knowledge. It means Python is the more complicated element in everyone CV.

Basis of Python for Data Science

Variables: In Python no need to declare the variables before using them. Variables have reserved memory location for values.

Data Types: It supports countless data types. The list of data types are – Strings, Dictionary, and Numeric.

Operators: Operators helps to handle the Operands. Operands are – Assignment, Comparision, Logical, Bitwise, Arithmetic, and Identity.

Loops: Loops can test the condition before execution. They are 3 types – For, While, and Nested loops.

Functions: By using the function we can save the time. It makes more readable by divide the code into useful blocks. I hope this blog may get some idea for you on Python for Data Science. Peoples who want in-depth Knowledge, Get in touch with Python Online Training.

Recommended Audience :

Software  Developers

 Team Leaders

Project Managers

Database developers

Prerequisites:

Better to know C or Java languages. But not mandatory. Trainers of OnlineITGuru will teach you from the basics if you don’t have that knowledge. All Trainers are Real-Time Experts you get more knowledge from those peoples.

 Become a Master in Python from OnlineITGuru through Python Online Course.

 
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