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Python is an open-source programming language with unlimited scalability and scope for data scientists to use in business-critical operations. We have seen several powerful programming languages in the last five decades, but Python has a revolutionary scope for data scientists, researchers, and database managers. Python has full capabilities to build complex software applications for desktop, mobile, and web. Python is used to build ERP, e-commerce, teaching programming, and ebook development.

Python is very popular these days and data scientists are using it in enterprise applications for cleaning, sorting, and computing bulky business data. Java was one of the developer's favorite languages, but Python has replaced and became the most widely used language. Python's dynamic nature and a wonderful library with inbuilt features for almost everything making it a popular choice among developers and organizations.

Being an open-source language anyone can make modifications to existing functions. Data scientists often need to incorporate statistical code into the production database or integrate the existing data with web-based applications. Apart from these they also need to implement algorithms regularly. Python makes all these tasks a hassle-free affair for data scientists.

1. Python is used in scientific and numeric computing

Several data scientists use Python in scientific and numerical computing in large scale projects. SciPy has a collection of packages for mathematics, science, and engineering projects. Python has a library called Pandas which is used for data analysis and modeling. 

2. Python is easy to learn and adapt 

Since it is a general-purpose programming language, Python is easy to learn and someone can start implementing it in the project. If you want to start a career in data science, data integration, or as a data analyst. Technical and non-technical people can learn Python and its open-source libraries without having to invest a lot of time and resources into it. Busy professionals who often have limited time to learn anything new. Python, therefore, comes in handy with its easy to learn and easy to understand capabilities. Even if one compares it to other data science languages such as R and MATLAB, Python has a relatively easy learning curve.

3. Python is much scalable

Python excels when it comes to scalability. According to Piyush Jain, Founder of Simpalm, an app development company in Chicago, “Python is much faster than languages like MATLAB, R, and Stata. It does so by allowing data scientists and researchers to approach a problem in several ways, rather than just sticking to one particular approach”. Whether you choose to believe it or not, scalability is the reason why Youtube chose to migrate their processes to Python. In fact, the cloud titan Dropbox recently wrote more than 4 million lines of Python code for their application.

4. Python has many data science libraries

Python’s data science libraries and tools make assignments as simple and fast. It has a suite of arranged libraries such as StatsModels, Sci-kit-learn, Scipy, and Numpy. Python is a data scientist recommended as a robust programming language that answers a majority of their needs and helps solve problems that seemed unsolvable at first. 

5. Community support 

Several websites have built the Python community strong. Data scientists, engineers, new learners are using Python.org, Realpython, and full-stack python websites every day to support the community and solve technical and real time issues. PyPI which is known as Python Package Index is another amazing repository for Python developers to find and install software and allow it to be shared with the community. Developers are more actively helping other developers and data scientists in completing their projects. 

Wrapping up

Python is compatible and easy to use since its syntax is simple. Data science communities and groups are together making it more popular. Professionals from engineering and science backgrounds found it more compatible to learn within a quick time. Simpalm also considers Python as an incredibly productive language for development. You can accomplish more in less time and effectively. All of these capabilities and qualities make it the top choice of data scientists and engineers. 

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