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Why is Python the most preferred tool in the Data Science industry? Being a non-programmer, how can one learn it effectively?

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Why is Python the most preferred tool in the Data Science industry?

Should you learn Python for Data Science?

As a non-programmer, how can you learn Python?

Data is no less than gold in global commerce today. It is replacing various methodologies and becoming the key driver behind analytics and business decisions. While there are numerous popular languages such as C++, MATLAB, JavaScript, etc., Python has always been one of the most prominent choices of professionals for leveraging Data Science and Machine Learning.

A survey by Business Over Broadway shows that around 60% of professionals in Data Science and Analytics prefer to use Python over other languages. Furthermore, the study by Gartner shows that 71% of Data Science professionals use python or are planning to shift to Python for data analytics use.

Why is Python the most preferred tool in the Data Science industry?

The data science industry is rapidly evolving. Therefore, it has become extremely important to use the right tools for further progress. Python plays an important role in making tasks such as the incorporation of statistical code easier and ensures better integration across web-based applications.


Professionals consider Python to be dynamic in nature. It is a well-interpreted, high-level programming language. Furthermore, it also contributes to Rapid Application Development (RAD) with features such as dynamic binding and typing making it the ideal language for algorithm working, which is an important part of data analytics.

One of the main reasons why Python is an important tool for Data Science is the fact that it allows professionals to deconstruct data into meaningful reports and insights. As a result, data professionals have the flexibility to simplify their workflow.

Below are some of the common reasons why Python is an important tool for Data science:

Easy learning curve
Python for data science can be pretty easy to learn. It is extremely beneficial for busy professionals. They can easily keep a check on it and pick up the concepts while being on the go.

Compared to programming syntax, Python can be easier to learn. Professional developers can refer to Python for ensuring that things are fast and easy.

High scalable nature
The scalable capacity of Python has led to it becoming one of the most popular options. It can easily scale faster than other languages such as SCALA and MATLAB. Since Python is so scalable, big giants like Facebook, YouTube, and Netflix are also using it.

Python makes it possible for data scientists and developers to approach the problem in different ways. Furthermore, it also uses various agile methodologies that are crucial in the data science industry.

Helpful for the developer community
Python has an active, informative, and engaging developer community because it is extremely popular. With the usage becoming more important, the contributors are creating additional libraries across the data science activities. Reaching out to people from the same community can be extremely helpful.


The developer community for Python is not only huge but also tightly knit. Within a tightly knit community, working becomes extremely easier. The programmers and developer community can connect and stay ahead.

Visualization and graphical properties
The visualization and graphics capacity of Python is quite high, making the library Matplotlib one of the most noteworthy ones. Furthermore, it is divided into various libraries such as pandas, scikit learn, and StatsModels. Every day, more and more libraries are added to Python to enhance the active community.

Needless to say, Python refers to the paradise for creators. It helps in creating single reports and details with the necessary data. Things that were hard earlier suddenly become easy. Furthermore, there are over 70,000 libraries included within the Python package. Considering the rapid development, there are chances that the number would keep growing.

Should you learn Python for Data Science?

Let's admit that Python is the future. It is becoming one of the most prominent choices for companies. Therefore, it is one of the most important skills that you should have.

Over the years, Python has helped various professionals develop a firm ground in the Analytics and Data Science industry. Comparatively, it is easier to learn compared to other programming languages. It is a must to learn Python if you want to make a career in this space.

As a non-programmer, how can you learn Python?

Many people fear that they won't be able to learn Python if they aren't familiar with programming languages. However, the truth is that you don't have to be a programmer to learn Python. Even as a beginner, you can easily learn it. As suggested above, Python has an easier learning curve which is a boon for individuals.

If you diligently practice Python each day, you will be able to pick up the concepts with ease. However, as a non-programmer, you need to be patient. Python isn't a programming language that you can learn in a day. It is necessary that you start with the base and build a strong foundation. To make this process easier, start your journey with Business Toys today!

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