It is an open source, general programming language with countless libraries that aid in data analysis and manipulation. Python is often a data scientist’s first choice for data analysis. With this in mind, it is important for academics transitioning into professional data science to broaden their skill set to include free and open source tool kits.

The source code is hidden from the user and any programs written with MATLAB can solely be used by MATLAB license holders. MATLAB’s main drawbacks, when it comes to analysis, stem from its proprietary nature. MATLAB’s other strengths include its deep library of functions and extensive documentation, a virtual “instruction manual” full of detailed explanations and examples. Of course, the true power of MATLAB can only be unleashed through more deliberate and verbose programming, but users can gradually move into this more complicated space as they become more comfortable with programming. Because of this, MATLAB is a great entrance point for scientists into programmatic analysis. It is possible to import, model, and visualize structured data without typing a single line of code. This means new users can quickly get up and running with their data without knowing how to code. MathWorks has put a great deal of effort into making MATLAB’s user interface both expansive and intuitive. Perhaps most important is its low barrier of entry for users with little programming experience. MATLAB has several benefits when it comes to data analysis. Luckily, for experienced MATLAB users, the transition to free and open source tools, such as Python’s NumPy, is fairly straight-forward. It is simply too expensive for most companies to be able to afford a license. However, due to its high cost, MATLAB is not very common beyond the academy. įor many of us with roots in academic research, MATLAB was our first introduction to data analysis. This article was originally published on October 25, 2017, on The Data Incubator. This technical article was written for The Data Incubator by Dan Taylor, a Fellow of our 2017 Spring cohort in Washington, DC.

Matlab vs python numpy