Always drop the first column after performing One Hot Encoding?

Since one of the columns can be generated completely from the others, and hence retaining this extra column does not add any new information for the modelling process, would it be good practice to always drop the first column after performing One Hot encoding, regardless of the algorithm of choice ?

In fact in pandas.get_dummies there is a parameter i.e. drop_first allows you whether to keep or remove the reference (whether to keep k or k-1 dummies out of k categorical levels). Please note default = False meaning that the reference is not dropped and k dummies created out of k categorical levels! You set default = True, then it will drop the reference column after encoding.