Why is Python Programming Language Important in Data Science

Before getting started in data science, there is one question that comes to the mind of the aspiring data scientists ‘Which is the most popular language used by data scientists?’. ‘Which programming language is most important in data science?’. There are many programming languages that are used by data scientists like Python, R, C++.

However, Python holds a special place among all. Python is an object-oriented, open source, flexible and easy to learn a programming language. It has a rich set of libraries and tools that make the tasks easy for Data scientists. Moreover, Python has a huge community base where developers and data scientists can ask their queries and answer queries of others. Data science as a service is using Python for a long time and it will continue to be the top choice for data scientists and developers.

Brief History of Python Programming language

Python was first introduced in 1980. However, with constant improvements and updates, Python was officially launched as a full-fledged programming language in 1989. Python Programming language was created by Guido Van Rossum. Python is an open source programming language and can be used for commercial purpose. The main goal of Python programming language was to keep the code easier to use and understand. Python’s huge library enables Data Scientists to work faster with the ready to use tools.

What Is The Python?

Python is a high-level programming language that is widely used for web development, scientific computing, data analysis, artificial intelligence, and more. It is known for its clear syntax, readability, and ease of use, making it a popular choice for beginners and experienced programmers alike. Python is an interpreted language, which means that the source code is not compiled into machine language, but instead is executed line by line by an interpreter.

Features of Python Programming language

Some of the important features of Python are:

• Python is a dynamically typed language, so the variables are defined automatically.
• Python is more readable and uses lesser code to perform the same task as compared to other programming languages.
• Python is strongly typed. So, developers have to cast types manually.
• Python is an interpreted language. This means that the program need not be compiled.
• Python is flexible, portable and can run on any platform easily. It is scalable and can be integrated with other third-party software easily.

Python Programming language Important in Data science

Data science consulting companies are encouraging their team of developers and data scientists to use Python as a programming language. Python has become popular and the most important programming language in very short time. Data scientists have to deal with huge amount of data known as big data. With simple usage and a large set of python libraries, Python has become a popular option to handle big data.

Also, Python can be easily integrated with other programming languages. The applications built using Python are easily scalable and future-oriented. All the above-mentioned features of Python makes it important for the data scientists. This has made Python the first choice of Data Scientists.

Let us discuss the importance of Python in Data Science in detail:

Easy to Use

Python programming is easy to use and has a simple and fast learning curve. New data scientists can easily understand Python with its easy to use syntax and better readability. Python also provides plenty of data mining tools that help in better handling the data. Python is important for data scientists because it provides a vast variety of applications used in data science. It also provides more flexibility in the field of machine learning and deep learning.

Python is Flexible

Python is a flexible programming language that gives the facility to solve any given problem in less time. Python can help the data scientists in developing machine learning models, web services, data mining, classification etc. It enables programmers to solve the problems end to end. Data science service providers are making exhaustive use of Python programming language in their processes.

Python builds better analytics tools

Data analytics is an integral part of data science. Data analytics tools provide the information about various matrices that are necessary to evaluate the performance in any business. Python programming language is a better choice for building data analytics tools. Python can easily provide better insight, understand patterns and correlate data from big datasets. Python is also important in self-service analytics. Python has also helped the data mining companies to better handle the data on their behalf.

Python is important in Data Science for Deep Learning

Python has got a lot of packages like Tensorflow, Keras, and Theano that is helping data scientists to develop deep learning algorithms. Python provides a better support when it comes to deep learning algorithms. Deep learning algorithms are based on the human brain neural networks. It deals with building artificial neural networks that simulate the behavior of the human brain. Deep learning neural networks provide weight and biasing to various input parameters and provide the desired output.

Huge Community Base

Python has a huge community base of developers and data scientists. Python developers can share their problems and thoughts with the community. Python Package index is the great place to explore the various horizons of Python Programming language. Python developers are constantly making improvements in the language that is helping it to become better over the time.

Conclusion

Python in data science has enabled the data scientists to achieve more in less time. Python is a versatile programming language that can be easily understood and is very powerful too. Python is highly scalable and can work in any environment easily. Also, with minimal changes, it can run on any operating system and can be integrated with other programming languages. All these characteristics have made Python the top choice for data scientists and developers.