R Programming is no doubt one of the popular programming languages that are used for a number of Data Science projects. But,there are some limitations that make Data Scientists take a step back while handling complex data. Talking about the cons of using R programming for Data Science, we have mainly three factors - slow command processing, hard to learn,and erratic functionalities when dealing a machine learning project. 

These are some of the negative sides of R programming language that should not be ignored.However, these limitations can be met if chosen at the right time for the right project. For example, if R Programming is giving you erratic results for machine learning projects, don’t use it there. Opt for some other language that can work well on such projects and leave R programming for better things.

Talking about the slow command processing, well, complex problems do take time to solve and this what R programming is expected to do. Try handling complex problems with other