In this case `d` is the entire dataframe. It's just a way of "piping" the object without having to rename it.
You are probably thinking about `df.apply(lambda row: ..., axis=1)` which operates on each row at a time and is indeed very slow since it's not vectorized. Here this is different and vectorized.
You are probably thinking about `df.apply(lambda row: ..., axis=1)` which operates on each row at a time and is indeed very slow since it's not vectorized. Here this is different and vectorized.