In this chapter, we covered the last important component of the ndarray object: strides. We saw a huge difference in memory layouts and also in performance when you use different ways to initialize your NumPy array. We also got to know the record array (structured array) and how to manipulate the date/time in NumPy. Most importantly, we saw how to read and write our data with NumPy.

NumPy is powerful not only because of its performance or ufuncs, but also because of how easy it can make your analysis. Use NumPy with your data as much as you can!

Next, we will look at linear algebra and matrix computation using NumPy.