Python is a multi-purpose programming language, meaning it can be used to develop several applications like data analysis, desktop and web development, machine learning and statistical analysis. Python is an open source language used in a wide range for data analysis and easily available.
Why Python Programming is popular for Data Science
Python is popular for Data Science with the attributes listed below:
Python is a high-level programming language with fewer lines of code to solve complex problems when compared to C# and java script.
Python is easy to learn, and support is available for newbies.
Increase in productivity and speed
Python has a huge community of developers with an open source for community development.
Python has a large Eco-system.
Python is readable.
Python has extensive support libraries.
Python programming is expressive and dynamically typed.
Python has a robust Integration feature, used across multiple platforms (Windows, Mac and UNIX). Its user-friendly data structures make python a top notch for Data Science.
Professionals who work with Python
Python has shown its relevance by improving and automating processes across various professions such as: Data Analysts, Software Engineers, Mathematicians, Data Scientists, Data Engineers, Network Engineers and Accountants.
These professionals use python programming for different reasons: Data Analysis, Automation, Artificial Intelligence and machine learning.
Applications of Python
Python as a general purpose and high-level programming language can be applied in:
- Web/Software development
Python as an object-oriented programming language is used for software and server-side development because of efficiency, readability, reliability and robustness.
Python has libraries that help integrate machine learning algorithms.
- Data Analysis, visualization and scripting
Python has helped applications develop process for studying, mining storing, and visualizing data. Its libraries have been useful for scripting and analyzing data.
- Embedded applications
Python can interact with almost all platforms.
The ability of python with its built-in data types to harness internet data handling, interaction with internet protocol (IPs), cryptographic services, third-party modules makes hackers prefer python for scripting.
- Mobile apps
Python is used to build mobile web solutions for customer and enterprise engagement to increase productivity of workforce.
- Artificial Intelligence
Python has helped improve processes like natural language processing, deep learning, predictive analysis, robotics engineering, speech and image recognition.
- GUI desktop applications (Scientific and computational applications, Game development, Image processing and design applications).
Python as a multipurpose object-oriented programming language is easy to learn and have a lot of importance in any industry (technology, healthcare, finance, transportation and so on).