Well, it is a trickier task to handpick a specific language when there are numerous languages that provide the much-needed option to execute data science jobs. Like we know Data has become a fundamental part of our everyday life and even Data Scientist has turned into an essential tool of this AI driving world. Now you might be wondering what a data scientist does? Let me make it simple for you; each and every company around the world wants to incorporate data analysts into their company to make better and faster business decisions; be it a start-up, well-established companies or the top MNCs, everyone wants to take full advantage of the critical data around them to stay ahead of the industrial competition. However, Data scientist also need the best tools to leverage the techniques that can turn data into insights and popular languages like R and Python offer great value in bringing data science jobs outstanding completion. But, it is a trickier task to handpick a specific language when there are numerous languages that provide the much-needed option to execute data science jobs. Nonetheless, in the race of language of choice for Data Scientist, Python always tops the chart.
Now, you might be wondering 'Why is Python preferred over other languages like R? Well, it is because Python has many enticing features such as schooling Python programming language is as simple as learning ABC; which draws the point to 'easy and quick learning'. While comparing it with R and others languages, it offers a shorter learning curve, along with promoting an easy-to-understand syntax. When we say Python is the King of the programming languages, we are not kidding! Python has an abiding lead by emerging as a scalable language. It allows you to work faster and more flexible to solve problems and address the problems of specific nature, when compared to other languages like R. Moreover, the variety of data science/data analytics libraries it offers serves as another significant factor that contributes to deep-rooting its leadership among other languages. Another reason for the phenomenal rise of Python is that it actually comes with the option of varied visualization, further more, Python has become the most preferred machine learning tool in the way it lets you 'do math' easily. Well, after considering all these amazing features of Python, now you might consider learning Python over R! Now there are some other reasons for choosing Python as a most preferred language for Data Science:

1. Simple to use and Easy to learn
   The most enticing factor of Python is that schooling its programming language is as simple as learning ABC; which draws the point to 'easy and quick learning'. While comparing it with R and others languages, it offers a shorter learning curve. While also making a lead over other languages by promoting an easy-to-understand syntax. As well the simple use of the code, especially making it close resemblance to the English language, makes it better suited for beginners.
   
2. A Faster too
   When we say Python is the King of the programming languages, we are not kidding! Python has an abiding lead by emerging as a scalable language. It allows you to work faster and more flexible to solve problems and address the problems of specific nature, when compared to other languages like R. The portable and extensible properties of Python also allow you to perform cross-language operations seamlessly, by integrating programming platforms like Java, .Net, C and C++.
   
3. Choice of libraries
   The variety of data science/data analytics libraries it offers serves as another significant factor that contributes to deep-rooting its leadership among other languages. Tensor Flow, Pandas, Stats Models, Numpy, SciPy and Scikit-Learn are some of the popular libraries in the data science community.
   
4. Python a tool for ML
   As you know, Machine Learning is all about statistics, mathematical optimization and probability. Thus, Python has become the most preferred machine learning tool in the way it lets you 'do math' easily. It also offers a customization for neutral networks and deep learning with libraries like TensorFlow.
   
5. Graphics and Visualization
   Another reason for the phenomenal rise of Python is that it actually comes with the option of varied visualization. The visualization packages help you to get a good sense of data, create charts, graphical plot and to create web-ready interactive plots.
   
6. Quick application development
   As compared to other languages like R, Microsoft Excel, python quickly develops applications and even save the developers from writing code from scratch.
   
7. Ample access to online python learning resources & Python is extensively adopted and used across different industries:
   Many top-notch companies have successfully developed around 1,26, 424 websites using python programming language. Moreover, Python has been widely used among companies like Google, Pinterest, Instagram, Disney, Yahoo!, Nokia, IBM, and many others. Nearly 14% of the programmers use it on the operating systems like UNIX, Linux, Windows and Mac OS. Python is extensively adopted and used across different industries
8. Python's IDE for data science
   Python along with its libraries, frameworks and other features, it also offers development environment for Data Scientist that provides a possible learning curve, visualize and report your results and also let you to collaborate with others easily. And such Python IDE's for data science Jupyter notebook, Spyder, PyCharm, Thonny, Atom etc.
   

With these features and enriched collection of industry-standard Python libraries, frameworks, IDEs, any Data scientist can carry out complex mathematical computations, manipulate Data frames, visualize meaningful insights, patterns and build complicated-dynamic models seamlessly.