This is one of the most basic questions involved in data sciences. I prefer using python rather than R.
This is because Python was made to favor readability and enhance productivity. It is much easier to learn and code. Python is much more user-friendly. But more importantly, python is a universal language in the tech world and finds its usage in many spheres. R is favored more by statisticians, researchers, and professors, but when it gets to the industry python is generally preferred over R. This is because python is also used for developing purposes (like web development or software development). And therefore it would be easier to perform data analysis in python and integrate it with your application.
R has a head start when it comes to packages for data analysis, however, it would be wrong to say that python is weak. A strong open source community has led to the development of various powerful data analysis libraries. Libraries like Pandas(almost like R), numpy, scipy, scikit-learn, statsmodel, etc make it very easy to perform data analysis in python. As far as visualization is concerned R can be used over python. Though python libraries like Matplotlib, Pygal, Bokeh, and Seaborn are very powerful and enable fast visualization. If you are a beginner and want to know more about Python and R programming language then do refer the following video tutorials:
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