When new members join our team, they usually are already fluent in data analysis with pandas and know their way around the typical quirks. They know that they should use vectorised functions where possible and avoid using apply with a slow Python callable. There are two main reasons, I teach them the BlockManager quite at the beginning. The first reason is that it is actually a core architectural component that is neither visible from the API nor is it part of the most tutorials through which people learn pandas. The other reason is that it has an impact on performance that is neither obvious from the code you were using nor that it always have the same (constant) impact on performance. Even after writing this post, I cannot reliably tell you the performance of a simple df.loc[0:10, 'column'] = 1, my answer will be a “it depends!”.