What are efficient ways to row-wise apply a function
f over a DataFrame? Looking through the DataFrames.jl documentation, I have found plenty of examples of column-wise aggregation. However, say that I want to take one or more columns, apply a function to each row, and output an array-like structure containing the results for each row, similar to Julia’s native vectorized dot notation for arrays:
f.(df[:A]) # something like this
Thus far, I have been doing as follows:
Is this a reasonable way to go about it?