Python – How it is becoming the survival of the fittest in data science industry

Python is the most popular and powerful programming language in the world of the data science industry. This general-purpose programming language is mostly used to design and develop different types of data science tools, creating software prototype, web applications, and so on.

Last few decades, Data Science gained unbelievable popularity among data developers and users. Initially, Python focused on converting the meaningful data into business strategies and marketing purposes to help the growth of an organization. Now it has a wider prospect and a handful of possibilities to expand wings of your organization in different fields.
There are several data management tools available in the market to analyze data such as R programming, SQL, Hadoop, SAS, and more others. However, Python is the best one regarding it’s easy to use tools and great possibilities.

Python is popularly known as the Swiss Army knife of Coding World because Python supports structured programming, functional programming languages as well as object-oriented programming and more.

Python: The fittest tools for Data Science

There is a unique attribute that has attached in this programming language to make it easy and fruitful when the term comes to analytical and quantitative computing. Further, it has been used to strengthen Google’s own infrastructure and also the building application like YouTube.

The massive libraries of python are widely used for several kinds of data manipulation and it is very easy to learn for everyone even for a beginner-level data analyst also. Another reason for its popularity is its flexibility and wide open-sourced language.

Apart from its independent platform Python is easy to integrate with any existing popular infrastructure that can mostly be used to solve different complex problems.

A large number of banks use Python for crunching the complex data for visualizing as well as processing the forecasting verdict analysis.

How is Python becoming Popular in Data Science industry?

According to the report of Stack Overflow Survey in 2019, Python outstripped the most popular programming language JAVA and took the position of second-most loyal and lovable programming language by the worldwide developers. They ranked Python as the fourth position after JavaScript, HTML, and SQL as per mostly used programming languages in the world. The popularity and accuracy with efficient data programmers is still growing and it seemed a very good time for self-examination by its own developers.

Why is Python known as the most preferable tool over other programming languages?

Python is popular for its amazing features and effective usage. Let’s see some of those which make it most preferable.

1. Easy to learn

The most captivating factor of Python is its easy-to-use key tools. Any aspiring candidate can learn this language easily and quickly without having any difficulties. This programming language is considered as the best companion of beginners students or research scholars. Anybody can learn this with just basic knowledge of data management.
When it is compared to other corresponding programming languages like Java, C, C#, developers consider this programming language as a difference for its outstanding ability for engaging less time on code implementation that helps to spend more and more time on research.

2. Well performed graphics and visualization

Python comes with a broad variety of visualization options. Matplotlib, the popular graphics tool of Python provides a solid foundation for the users like Seaborn, ggplot, and pandas plotting libraries for strong performance. This visualization package might be helpful for you and you will get a proper sense of data management, create charts, web-ready interactive plots, and graphical plots.

This well-performed graphics and visualization help the beginners to advanced level data scientists to make the program accurate.

3. Data science library

The most significant part of Python is its Data Science Library. Python provides huge numbers of the database of data science libraries as well as artificial intelligence that makes it more attractive. It makes a great push to upgrade Python to the top-level of Data Analysis. It helps the work easier and makes the data management efficient for the aspirants. StatsModel, SciPy, Scikit-Learn, and NumPy are some of the well-known libraries in the field of the Data Science community.

4. Scalability

When the times comes to compare Python with other programming languages like R, java, and more others, it has proved itself in the level of faster and highly scalable programming languages.

With more flexibility, its users enjoy problem-solving techniques effectively. Sometimes many high-level languages can’t solve some problems which can easily be solved by Python. Several enterprises use Python to develop their rapid growth and beneficial tools to enhance their data management.

5. Own community

Another effective reason for the phenomenal growth of Pythonlanguage is its characteristics related to its own ecosystem. Expanding wings of the data science community led the way of success for creating modern, updated, effective tools as well as processing ability.

The involved and widespread community promotes easy access mainly for aspirants who like to find multiple solutions regarding their coding problems. Which kind of query you need, a single click can help you to reach the ultimate destination.

Python as a programming language of beginners

At the very first or initial time, Python was used as a primary programming language mainly for university-level students. It was popular among the students, researchers, and coding campaigns worldwide. High school level and University level students were developing such programs to teach to use the code of Python.

But now, it has been seen that the trend of using and learning Pythonlanguage is gradually increasing. Due to its different types of uses and easy to handleability, it becomes more and more popular among the group of beginners. As per the result of a statistical survey conducted by an American organization, 16.1% of Python users are 12 to 13 years old students in their school days. 19.6% of users belong to the group of 14 to 16 years old. From this statistical survey, it is clear that the maximum numbers of beginners are involved in the world’s second-most preferable programming language.

Future of Python

In the year 2019, Python was declared as the fastest-growing programming language by many data analysts. It has been awarded to a multi-paradigm, dynamic, open-source, and extensible language throughout the world.
Its future is luminous. With exceptional innovations and friendly uses, Python is embracing the programming community every day.

Due to its amazing attachments and well-known improvement over the last two years, Python was able to take an effective platform. With the proper and adequate power of evolution since its releasing date, Python is considered as the survival of the fittest in the Data Science Industry. All the machine learning experts and developers always prefer pythonlanguage mainly for building applications and natural language processing.

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