Why is pd.unique() faster than np.unique()?
np.unique() is treating the data as an array, so it goes through every value individually then identifies the unique fields.
whereas, pandas has pre-built metadata which contains this information and pd.unique() is simply calling on the metadata which contains 'unique' info, so it doesn't have to calculate it again.
I tried to compare the two, one is pandas.unique() and another one is numpy.unique(), and I found out that the latter actually surpass the first one.
I am not sure whether the excellency is linear or not.
Can anyone please tell me why such a difference exists, with regards to the code implementation? In what case should I use which?