Comment by OutOfHere
2 days ago
Using `lambda` without care is dangerous because it risks being not vectorized at all. It risks being super slow, operating one row at a time. Is `d` a single row or the entire series or the entire dataframe?
2 days ago
Using `lambda` without care is dangerous because it risks being not vectorized at all. It risks being super slow, operating one row at a time. Is `d` a single row or the entire series or the entire dataframe?
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.
Appreciate the explanation, this is something I should know by now but don't
That's excellent.