Python vs R: Healthcare Software Develoment


Anastasiia Kholodna

May 18, 2018, 2:34 p.m.

At the vet beginning, there is always a question about which programming language to choose as the main one between a specially used for data processing (R) or effective in all areas, Python language.

Both Python and R have their advantages and disadvantages. In most cases, these are specific programming languages, since Python is focused on development simplicity and R is focused on statistics and visualization.

What is the similarity of Python and R?

  • Both Python and R languages are open source programming languages. A huge number of various programming community members contributed to the development of documentation and the development of these languages.

  • Both can be used to analyze data, analytic and in machine learning projects.

  • Both have advanced tools for implementing projects in the field of data science.

Why Python?

Python is used by developers, who:

  • Want to understand and get into data analysis

  • Work with statistical methods and large amounts of data

  • Build complex multi-protocol network applications

  • Work mainly with machine learning products

Why R?

  • Statistical models are written in several lines

  • Easier work with complex calculations

  • Well-documented algorithms and tools in work with the statistic

What should we use in healthcare software development?

Many specialists find it difficult to answer this question, as there is no particular best programming language for the healthcare apps. Every single programming language takes its own significance and comfort on the features of the apps and portals.

In the list of the most popular programming languages in the healthcare software development are included: Python, JavaScript, Java, C#, C++, etc. As for Java, C#, and C++, they are a bit difficult to use for data analysis. However we should not forget about such tools as Matlab, SAS, Stata, SPSS, and others.

R can be used mainly for research in scientific institutes, during statistical analyzes and data visualization. On the other hand, Python is used to simplify the process of data processing, data analysis, etc.

Python is slightly ahead of its competitors because of the code which is largely laconic and understandable even to those who have never written on it. Due to the simplicity of the code, further maintenance of programs becomes easier compared to other languages. From the business point of view, this entails reducing costs and increasing employees’ productivity.

If you still have concerns about which programming language you should choose for your product, feel free to get in touch with our tech team