Top 12 Programming Languages for Data Scientists

Programming Languages

Data scientists use these languages to manipulate, analyze, and extract information from data across various domains, including machine learning, natural language processing, and more.

1. Python:

Python remains the most popular programming language for data science, offering versatility in the industry and other domains like web development and video game development.

2. R:

R, though not as trendy as Python, is a top choice for data scientists, especially for data manipulation, processing, and visualization.

3. SQL:

SQL is essential for working with databases and is a must-know for data scientists as they frequently interact with relational databases.

4. Java:

Java, an open-source, object-oriented language, is popular for various technologies and software applications.

5. Julia:

Despite its recent release, Julia is becoming a rising star in numerical computing, offering effective data analysis tools.

6. Scala:

Scala is emerging as a language for machine learning and big data tasks, providing an alternative to Java.

7. C/C++:

C and C++ are well-suited for computationally intensive data science tasks and play a role in core components of machine learning libraries.

8. JavaScript:

JavaScript’s versatility extends beyond web development, making it a notable language for machine learning and visualization in data science.

9. Swift:

Swift, developed by Apple, is aimed at mobile app development and is increasingly relevant for mobile and machine learning integration.

10. Go:

GoLang’s popularity is growing for machine learning projects due to its flexible and understandable language.


MATLAB is a powerful language for numerical computing but comes with a cost for licensing, making it less attractive.

Also Read: 2023’s Top 5 Programming Languages for Game Development

12. SAS:

SAS is a well-established software environment for business intelligence but is losing popularity due to licensing barriers.

Selecting a programming language for data science depends on learning history and work requirements. Python, R, SQL, and other languages offer a range of tools and capabilities for data scientists.

Read More: Top programming languages for data scientists in 2023