Thousands of years back,there was a world where the person with many kingdoms was considered to be the most powerful person and now after thousands of years a person with the enormous amount of data and his ability to interpret and use this data correctly is considered to be the most powerful person. This brings in existence the concept of data science.
So what is data science?
Well according to Wikipedia, “Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data.” In simple words, data science belongs to the field of study that helps us study the data. It consists of extracting, recording, storing ,and analysing the data to put it into proper use. The objective of this field is to gain an understanding, Insight ,and knowledge from data whether it is structured or unstructured. Data science is practised by Data Analysts, Data Engineers, and Data Scientists. For understanding data science, one requires to have the knowledge of various programming languages like python, R, tensorflow, pytorch and many more but the most famous among these is python and why is that? Which is what exactly we are going to get to know about in this blog.
Python is the most common coding language. It is a basic requirement in data science. Most data scientists prefer python as a programming language . According to Wikipedia,” Python is an interpreted, high-level, general-purpose programming language.” Having a characteristic of versatility, one can use Python for nearly all the steps that take place in data science processes. It can take numerous formats of data and one can easily import SQL tables into your code. It permits one to create datasets and one can find any type of dataset one needs on Google.
Some of the features of python include:
The variables of python are defined automatically as It is a typed language.
Python uses less amount of codes to carry out any function as compared to any other programming language
Python is flexible and can run on any platform.
Now coming to why python is considered to be the backbone of data science, Here are the reasons for it.
1. Python is user friendly
Understanding and interpreting python is very easy. Python uses many tools, one of them being a data mining tool which helps to cater to needs of data easily. Python is also one of the important programming languages when it comes to machine learning. One can learn python through online courses or from anywhere and can use it easily.
2. Large number of users
Python is one of the most famous programming languages throughout the world thus it caters to all data scientists , data analysts, and data engineers. This creates a huge community base. Python Package index is one of the features to explore the various horizons of Python Programming language.Thus any problems faced by anyone can be addressed easily and solutions can be found easily . The developers of python are constantly trying to improve the program to cater to the needs of people using it.
3. Analytic tools
Analytics tools are the core of data science and there is nothing that one can do without analytic tools in data science.these tools provide the user with information which helps them to improve their business performances . These tools are developed by python very easily and helps businesses to get insight, and interpret the data. Python is also important in self-service analytics.
Python has made it easy to interpret the data.It provides the best result within the short period of time. And due to its large scale use , it is continuously updating itself to the better version of itself thus providing better service to data scientists,data analysts,and data engineers. And hence python proves to be the backbone of data science.