You are here
Home > Blogging > Python for the Data Science vs. Python for Web Development

Python for the Data Science vs. Python for Web Development


The blend of machine learning and data analysis is barely new information, but the fact that renders it intriguing is that machine learning /data sciences and web development overlap. Python development services have taken over the world by storm. It is omnipresent, from data science to machine learning and DevOps. Researches show that the unprecedented expansion in the machine learning and data sciences has made Python, the fastest-growing programming language.

Python development services have various applications and Python programming itself includes several frameworks and features to expand in data visualization, data science, and graphical user interface (GUI), web application development, among other aspects. Several enterprises use Python, on a large scale, for running data, for data visualization, and for evaluating extensive datasets.
Python for Web Development

Python is a dynamic programming language, powerful enough to offer a hassle-free option of writing the code. Meaning, that the programmer can use Python to write and run the code without having to bring an individual compiler into use. It supports numerous programming standards, including the likes of object-oriented programming an, functional programming and structured programming. The most exceptional part, the code written in Python language, can be easily embedded into several existing web applications requiring a programming interface. It is a programming language that requires accurate mathematical calculations and rapid execution.
Python programming language is the choice of perfectionists for research, academic, and scientific applications. With that said, python programming language is essential to learn numerous frameworks used for Python web development. It can be challenging since the libraries and documentation of these frameworks are not easy to comprehend.
Python programming language can be considered impractical as a web programming language for many reasons, including:

• Unlike other programming languages, Python web development does not involve a steep learning curve.
• Python development services are lesser demanded than its counterparts such as Ruby on Rails, Java, or PHP. However, if it is Gaining traction in the field of data science, as with the companies looking for skilled data Scientists, thanks to Python’s Increased Adoption in data science applications, including machine learning.
• Python web development, as compared to other web programming languages, requires higher development costs and expensive hosting.
However, there are numerous Python web application frameworks available for free that help web developers create quality web applications. The frameworks include:

1 Cherrypy

This framework lets programmers create web applications like they have been building with the object-oriented Python programming.

2 Flask

Flask emphasizes on providing lightweight and simple solutions for new coders who are getting started with Python programming. It provides a framework for developing single-page web applications. However, it doesn’t support for data abstraction layer, validation, and rest of the components offered by various frameworks.

3 Django

Experienced developers and perfectionists prefer Django over the rest, especially, for developing database-driven web applications including – templating system and an automatic admin interface. However, it consists of a strict directory structure, and a file system can be a little confusing.
Apart from the above, other frameworks include:
● Pylons
● Bottle
● Pyramid
Python for Data Science
Organizations and enterprises from different sectors and industries are adhering to Python-based development services to run their business. From small start-ups dealing in big-data analysis to large enterprises, companies are using Python data programming language for several applications driven by data science like machine learning and numerical computations, among others. Python, as a programming language, is not a performance-dependent language and cannot do low-level stuff. It is the statistical computations and data analysis that serve the true calling of Python, even though industries have learned it the hard way.
Unlike Python web development, which needs programmers to understand and master numerous web frameworks, learning Python data science alone requires to understand concepts of data visualization, get working with the scientific libraries, and the use of frequently used expressions.
Python for data science doesn’t require any prior knowledge of web programming concepts. It is a completely different field and can be put to use for a different purpose. So, any aspiring data scientist takes a plunge into Python for data science without requiring learning any Python web programming concepts.
Python is Best for Data Science
Thanks to its easy like – English syntax, actions like number crunching, statistics, finance, and handling big data becomes quite simple. The advancement in the Python data science environment with multiple packages for natural language processing, machine learning, data mining, data analysis, data exploration, and data visualization has resulted in the sudden growth of the data science industry.

Debaleena
A blogger with a zeal for learning technology. Enchanted to connect with wonderful people like you.
https://www.techentice.com

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Top