There are several factors you need to take into consideration.
1. For what do you want to do the analysis. Is it a simple use case or a project at the university or even in a company? In the first case, it's up to you. In the last two it depends on the complexity of the project and if it is done by one or many people.
2. On how much data do you want to do the analysis? If you have a simple set to make a test on it, R is the most simple. Do you have a lot of data? lets say some GB of pictures and other information? Then Phyton is your best new friend.
3. What should be done with the Analysis afterwards? If you need only to show the results, then both are great, but if you want the code to be close, then Phyton wins the case.