Use of Python in Data Analysis and Data Science

by Shiva Joice Data Science Professional with 5 Years of Experien

Python is one of the fastest-growing programming languages in the world. This programming language is a very versatile and dynamic one. It is a general-purpose programming language that can be used for developing all sorts of web and desktop applications. Python is also used in various numerical and scientific applications as well. 

With so many advantages and uses, python has become very popular in the data science industries as well. This article will give you a more detailed idea of what is the use of python in these data dominant fields. 

Data Analysis

Data analysis is all about interpreting data and analyzing the results using all sorts of statistical applications. Even data collection systems are developed and implemented by data analysts. Also, data analysts develop algorithms all the time to increase the efficiency of statistical tools. The maintenance of the data sources and database falls under the umbrella of data analysis. 

All these end up in results that are used by various companies and businesses to optimize their performance in the market. 

Data Science

Data science is a multidisciplinary branch where various algorithms, and processes are developed in order to extract information from various structured and unstructured data. The data scientists study the present data and try to formulate some hypotheses based on the trends of the data. Based on these patterns or trends, the company gets to know where they stand in the market as compared with its competitors. 

Difference Between Data Analysis and Data Science

The reason why python is used in both the field is that both of these sectors are very overlapping with some distinctive differences. The main difference here is that data analysts work with the day to day present data but the data scientists have to work with hypothesis developed form the day to day data sets. 

Why Is Python Essential for Data Analysis and Data Science?

Here are some of the basic points as to why python is necessary for data analysis

  1. Python is a vet flexible program and if you have never programmed an application can before then python is the best platform to do it.

  2. It is a very simple and easy language to learn. It requires very few lines of codes and syntax to develop applications using python.

  3. Python is an open-source program which is why you can easily download it and use it for all data analysis purposes.

  4. Python is a very well supported program. It has a large number of followers and there are huge groups of python users online. Thus, if you ever fall into trouble or you are having issues with some python code then you can easily find help or solution to it, online.

Some additional points

When it comes to python for data science, python can also be used for developing machine learning algorithms, web scraping and data visualization. Python comes with a lot of built-in libraries that are adequate enough to even handle a huge amount of complex data as well.


Whether it be data science or data analysis, python can be used for all the data handling projects with ease. With all the mentioned features, python serves as the best programming language in these two fields.

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About Shiva Joice Junior   Data Science Professional with 5 Years of Experien

3 connections, 0 recommendations, 17 honor points.
Joined APSense since, February 3rd, 2020, From Bangalore, India.

Created on Feb 6th 2020 09:11. Viewed 655 times.


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