We could intuitively say that these professionals make such a pick because they need an easy-to-use language with a variety of tools to make their lives easier. Their training helps them to digest complicated numbers and algorithms to help their companies be as successful as possible.

According to recent studies, Python is the number one choice of data scientists. And given that there are many situations within the field of data science for which Python is a natural fit, it’s ranking at the top seems obvious.


This means using the best tools available on the market to help accomplish their goals. For many, one of their top tools is the Python development language.

What Makes Python the Preferred Data Science Language and Tool?

Python provides the tools necessary to effectively complete the problem-solving process with dedicated tools available and attributed to each step. Data scientists must face complex problems on the regular. Python is also the top language choice by data scientists for the following reasons:

1. It’s easy to learn

In that sense, one of the most alluring factors of Python is that anyone aspiring or in need of learning this language is able to do so easily and relatively quickly. They must have a wheelhouse of tools at their disposal that they can rely on and thoroughly understand while not dedicating their entire careers to learning the art of coding.

Compared to other languages used in data science (namely R), Python offers a condensed learning curve and easily understood syntax for simplified code work. Data scientists aren’t experts in a single area – they aren’t only developers or only statisticians.

2. Python is scalable, more flexible, and faster than other languages

Many of the top sites of today, including YouTube, utilize Python for its flexible and fast nature. Compared to R, the second leading language in data science, Python is a much more scalable language and is ultimately faster, including when compared to other languages such as Stata and Matlab.

Its flexibility allows data scientists to build data models, create machine learning-powered algorithms, apply data mining, and systemize data sets to accomplish many different tasks in a shorter period of time than with another language.

3. It features notable graphics and visualization tools

Data scientists must have the ability to communicate complicated data sets to their other team members through data visualization. Python offers a pack of diverse visualization options to make data much more accessible and easier-to-use in the real world. This includes traditional charts and graphs but also web-ready interactive plots and such to get the best sense of the data as possible.

4. Python comes with a huge collection of libraries

This helps ensure that data scientists and coders alike will continue to receive support as libraries constantly grow and provide more robust solutions. These libraries make the language a great solution without the hassle and additional expenses associated with expansion. Python is one of the most supported languages on the internet. Every Python user has access to an incredible list of completely free libraries.

5. It offers an expanded pack of tools for analytics

Python’s built-in data analytics tools work excellently for tasks such as the reduction of data, pattern penetration, and the correlation of information. Python helps data scientists handle data after they’ve gathered it. This means they must use the perfect tool for completing the processing of complex data.

6. The language’s online community is enormous and ever-growing

Whatever queries or questions a data scientist comes across in the field, or even if they just need a quick solution to their coding problems, professionals know that another dev probably found a solution for their exact problem.

The Python ecosystem is always expanding. This online support paved the way for the creation of the most modern tools and data processing systems. Many volunteers create new data science libraries to help the language extend further into the field.

Bottom Line

In that context, Python is the top choice by data scientists in the field for a reason: it helps companies accomplish those goals. The success of a company directly depends on its ability to collect data, extract knowledge and insights, and use said knowledge to make the most informed and effective business decisions.