Why is Python the Most Popular Language for Data Science?

Why is Python the Most Popular Language for Data Science - featured image

Data is the new gold for the world of global commerce. It is rapidly replacing primary methodologies as the key driver behind informed business decisions and analytics.

The industry is in the process of chalking out solutions that have the ability to extract actionable insights from the unparalleled flow of data.

However, it needs a medium to make those insights actionable and thus, the language that effectively leverages visualization and reporting. 

Although most popular languages like javascript, C++, SCALA, MATLAB, and java hold the capability of working with data, the more preferred choices are R and Python due to their capability of leveraging the potential of both Machine learning and Data Science.

The dynamic industry is rapidly proceeding towards innovative technologies of the future like Machine Learning, Artificial Intelligence, Natural Language Processing, and Data Science, the importance of learning Python for the same is also on the rise. 

A survey on the most preferred tools for data science and analytics conducted by Business Over Broadway states that 60% of the responders prefer to use Python for applications in Data Science.

An independent survey by Gartner states that 71% of Data Science professionals already use Python or are in the process of shifting to it for data analytics. Now, this speaks volumes about the sheer potential of this language.

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Why is Python Rapidly Becoming the Preferred Choice for Data Science?

Python is often the ideal choice for Data Science professionals as it makes tasks like incorporating statistical code into production databases or integrating data with web-based applications smooth as butter.

It is often defined as interpreted, object-oriented, high-level programming language with semantics that is dynamic in nature.

It is a highly attractive option for Rapid Application Development due to features like dynamic typing and dynamic binding. It is also the ideal language for working with algorithms, which is a key part of the domain of data analytics. 

It comes equipped with packages that are tailor-made for data science functions like pandas, SciPy, NumPy, Matplotlib, etc.

Matplotlib is especially interesting as it enhances the capability of Python as a Data Visualization tool due to its ability to work with graphics and other visuals.

The most popular library in python for data science is pandas. It is a set of high-performance applications enabling data analysis in Python a hassle-free task.  

The primary factor that makes Python so interesting to work for Data Science is its ability to deconstruct hordes of data into meaningful reports and insights. This helps Data professionals to simplify their workflow by a huge margin.

Easy Learning Curve

One of the most fun parts of learning Python for data science is its relatively easier learning curve.

It is especially helpful for busy professionals to pick up the concepts on the go.

It as a comparatively easy programming syntax that makes it highly lucrative for professional developers who like to keep things fast and comprehensible. 

Highly Scalable Nature

Python has gained immense popularity due to its ability to scale. It is comparatively faster than other alternatives like MATLAB and SCALA.

Companies like NetFlix, Youtube, Facebook, etc. are making more and more use of this language due to its scalability.

It offers developers and data scientists the flexibility to approach a problem in multiple ways. It has also made significant marks in agile development methodologies making its usage widespread across the software and data science industry

A Helpful & Diverse Developer’s Community

Due to its sheer popularity, Python has a very active, informative and engaging developer’s community. As its usage becomes more primal in Data Science, contributors are volunteering by creating additional libraries for data science activities.

A quick internet search can help you to gain access to active information regarding any professional problem in Python.

It is a tight-knit community in general and finding information is relatively easier due to this. Developers and programmers can also interact with their peers over Stack Overflow and Codementor. 

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Visualization & Graphical Properties

The library Matplotlib, as discussed earlier, provides significant options in terms of graphics and visualization capabilities of Python.

It is further supported by libraries like StatsModels, scikit-learn, pandas, NumPy, etc. As we discuss, more libraries are being added to expand the potential of Python by its active community.

It is a creator’s paradise and producing detailed reports with seemingly meaningless data was never this easier. It has over 70,000 libraries at present in the Python package index and the number continues to grow as we speak. 

A Python Use Case

The weather forecasts of today rely on the century’s worth of weather records and data in order to make a prediction/ forecast.

With the help of Machine Learning, you can make accurate predictive models based on events and past weather reports. Python makes the process easier as it is lightweights and highly efficient at executing effective code along with being multi-functional.

Another significant advantage is that Python is object-oriented and thus, is a structured and functional programming style that can find an application in any use case. 

Why You Should Learn Python for Data Science?

Well, as we have already established earlier, Python is the future. It is rapidly becoming the language of choice for Data Science and Machine Learning making it a highly lucrative skill to pick up.

It has helped thousands of professionals give a new turn to their career and build a solid ground in the Data Science and Analytics industry. It is relatively easier and enjoyable to learn and you can pick the core concepts very easily. 

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Its approach to problems is highly systematic and can help in creating real solutions in the process. There is no better time to learning this highly engaging language than now!

The industry is geared to face a 1000% increase in the demand for skilled professionals in Python for Data Science and Machine Learning and this will help in opening up thousands of career opportunities across domains.

And, picking skill is very easy in today’s world with ample online training mediums that can help you to learn python easily. 

Ending Note

Now that we have elaborated on the potential and usage of Python in Data Science, you must be already excited to pick this skill soon. And, why not?

The industry is soon going to face a huge demand for professionals and experts in Python for data science and analytics and you don’t want to miss that train!

The opportunities coming your way will be highly rewarding both in terms of compensation as well as work satisfaction. 

It is not an imponderable phenomenon that Python is going to take over the Data Science and Machine Learning industry by storm. Its high flexibility, as well as versatility in usage, enables it to be one of the top choices to opt for in order to create scalable solutions that are highly significant and useful for the industry. 

If you are in the lookout for a great online course to learn Python then you can opt for JanBask Training’s Python course.

They have one of the most comprehensive Python training programs in the industry today. You also get a certificate to authenticate your skill upon successfully completing the course.

The course has an easy learning curve that will help you to easily keep track of the course’s progress and never feel left out.

You will also retrieve lifetime access to the course content along with the routine updates as per industrial standards. So, enroll yourself in the best Python training course and kickstart your Python learning journey in style!

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