If we wanted to transpose the axes of this array in Python, we’d need to write a loop of some kind. NumPy allows us to do this kind of operation with a single command: x2 = np.transpose(x1) ...

The for loop construction in Python easily iterates over a collection of items. Here’s what you need to know to use it well. ... This yields 1 3 5 7 9 11 13 15 17 19, then Done.

Python is incredibly popular because it's easy to learn, versatile, and has thousands of useful libraries for data science. But one thing it is not is fast. That's about to change in Python 3.11 ...