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okay second learn tip number 41 new in version .23 use drop equals if binary with one hot encoder to drop the first category only if its a binary feature meaning it has exactly two categories so lets take a look weve got two unordered categorical features also known as nominal features and shape has three possible values color has two possible values so were gonna use one hot encoder to encode both of them numerically by creating dummy variables and were gonna do this three different times and compare the differences so first we are going to use drop equals none which is the default for one hot encoder and it creates one feature column per category so thus you can see that shape becomes three columns and color becomes two columns next were gonna use drop equals first and that actually drops the first category in each feature so shape instead of becoming three columns becomes two columns and color instead of becoming two columns instead becomes one column now this is allowed becau