For a data analyst/data scientist, displaying only R or only Python on a resume underlines very clear professional boundaries : - Only R : you're a pure statistician/analysis person, usually with an academic background, R is your high tower and you're not going to get your hands dirty in the data infrastructure stuff. Mostly useful if, for example, the company already has a skilled data engineering team, able to perfectly deliver to you, and you're mostly interacting with the stakeholders and management. - Only Python : you're able to be closer to the data infrastructure people, exchange code with the data engineers to implement stuff into production. Would be weird to ask a data analyst profile to do some infrastructure stuff, but clearly some "data scientist" hires are asked to do that in smaller companies, and it usually involves a lot of Python. Python is also essential in Machine Learning, so even pure academic people need to learn it to go into this area. Clearly, R is a signal for a pure data analyst & math heavy profile, while Python implies, potentially, more general programming ability and versatility. If you want to stay in this pure data analyst role, I would say just go for R as it's the right signal and tool for this objective. But if you want to open some potential new paths for your professional career, for example, if you want to work with data engineering or machine learning at some point, you can't do that without Python. That's why a lot of data people have the capacity to switch between being data analyst, data scientist and data engineer, given a few years. You can't have these trajectories by only sticking to R. Answer from Nabugu on reddit.com