Python is a fairly complete language with relatively concise syntax. If you were writing out an algorithm in pseudo code on a whiteboard, you could probably turn your text into compiling Python with very little work. Its string manipulation syntax is concise and natural (which comes up a lot in my experience), lists and dictionaries work with no overhead, and it has an interpreter for rapid iteration. You’re going to be a lot more productive in your first hour of a Python project than you will be in more powerful languages.
By comparison, the two dominant full-featured languages, Java and C++, expect you to learn a lot of additional syntax and write a lot more text to achieve the same goal. That’s fine for a full-time software engineer. Java and C++ give you a lot of speed and power in return for all the additional things you need to know. They force you to really think through exactly what you want to do, which isn’t good in the first hour but is great in the following days, weeks, and years. For example, both have strong typing which requires a lot of additional typing and thought but also greatly reduce the number of ways your program can bite your head off. The time spent learning all their intricacies isn’t worthwhile for a data scientist who is mostly writing terminal code (i.e. code that isn’t going to be referenced by other code).
