python del vs pandas drop
In drop method using "inplace=False" you have option to create Subset DF and keep un-touch the original DF, But in del I believe this option is not available.
I know it might be old debate, but out of pandas.drop and python del function which is better in terms of performance over large dataset?
I am learning machine learning using python 3 and not sure which one to use. My data is in pandas data frame format. But python del function is in built-in function for python.