Everyone is always asking the age old question: R or Python? Why not both? I refuse to choose! They each have their own strengths and weaknesses, and I often find myself seamlessly interweaving between the two depending on the task at hand.
Being ambidextrous with R and Python has never been easier, as cross-pollination across the two languages has resulted in many of the same constructs now existing for both. For example, data frame implementations such as pandas and tibble are largely converging on many of the same patterns and tooling.