Python or R: Which Should You Learn as a Beginner Data Analyst?


As a beginner Data Analyst, one of the most important skills that you should possess is to have proficiency in a programming language. As you might already know, Data analysts use Structured Query Language or SQL to interact with databases. Still, Python or R are your best options for cleaning, manipulating, analysing, and visualising data.

A data analyst must have a good understanding of core python programming or R programming. But which one should you learn as a beginner data analyst? Keep reading, and you will find out the answer in this blog.

Before learning which programming language would be best for you, you should know the meaning of both of them.

What is Python?

Python is a high-level, all- purpose programming language renowned for its logical syntax that resembles natural language. There is a wide range of works that you can achieve with PythonPython, but three major applications are:
(i) Automation and scripting
(ii) Data science and data analysis
(iii) Web application development

What is R?

R is a software environment and statistical programming language that was designed for data visualisation and statistical computing. R offers a wide range of skills that typically fit into three categories:
(i) Visualising data
(ii) Manipulating data
(iii) Statistical analysis

Which programming language between Python and R should you learn as a beginner Data Analyst?

Before choosing, you should first know that there is no wrong choice between these two. Both R and PythonPython, are in-demand qualities that will enable you to handle almost any data analytics project you come across.

The answer to the question of “which one should you learn” entirely depends on your interest, background, and career goals. Here are some aspects that you can consider and decide which language suits you the best according to these aspects.

1. The learning curve

Both Python and R are regarded as being relatively simple to learn. Python was created initially for the purpose of developing software. Here is how you can decide–
(i) If you have prior experience with Java or C++, you may be capable of learning PythonPython more quickly and easily than R.
(ii) On the other hand, R might be a little simpler if you have a background in statistics.

2. Pros and cons

Even though both languages can accomplish many of the same data tasks, both of them have their unique pros and cons. You can choose to learn the language that best suits your interests and career.

You should choose Python if you have interest in the following:
(i) Dealing with enormous amounts of data.
(ii) Accomplishing non-statistical tasks, like saving to databases, running workflows and web scraping.
(iii) Developing deep learning models.

You should choose R if you have interest in the following:
(i) Creating data visualisations and graphics.
(ii) Developing statistical models.
(iii) Its robust ecosystem of statistical packages


As a beginner data analyst, it might confuse you as to which programming language you should choose. However, it totally depends on your interests and the career path you want to take. You can even choose to take a data structures course in which you can enhance your skills and understand which language you would want to pursue in the future.

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