| I am currently a data scientist. Educational background in cs, few hobby web projects and currently updating my skills in java/ kotlin with the idea to go in mobile dev. I use only Python in my work. I learnt R and honestly, it's the same thing as using Python scientific packages. It's mostly vectorized operations, spaghetti functional, if people know how to write functions, code just to get it done. To make graphs, web dashboard(no, we are not doing web dev, it's dark magic frameworks), build machine learning and eventually some reports. Stuff like that. I do some software engineering but that s optional and I do it because I can. Most data scientists/ ml engineers can't. So you guys are not fair. R and Python in these environments are not even being used for building stuff. This language is not build for that. Hence it's not good from the perspective you look at it from(software engineers). Unlike Python , R is solely for statistics, data science and probably some basic ml( I haven't tried tho). Also Shiny for building web dashboards. But don't look at the code for dashboards, it's bad, with 'get it done and forget' approach. That being said. Good luck scrapping, mining, cleaning data with something not called R/Python. Good luck with data engineering. Exploring and visualizing trends. Creating dashboards even. Machine learning. Monitoring and reporting in scientific manner. Try This type of work with your favorite languages. Then see how quickly and easily it's done with R/Python . Come back and say it's bad language. It's the same thing as embedded dev complaining about how bad js is for his job. You just totally ignore the context. |