#this will label the different catagories as 0,1,2,3.... dataset["sex"] = dataset["sex"].astype('category').cat.codes
from sklearn.preprocessing import LabelEncoder lb_make = LabelEncoder() obj_df["make_code"] = lb_make.fit_transform(obj_df["make"]) obj_df[["make", "make_code"]].head(11)
#this will label as one hot vectors (origin is split into 3 columns - USA, Europe, Japan and any one place will be 1 while the others are 0) dataset['Origin'] = dataset['Origin'].map({1: 'USA', 2: 'Europe', 3: 'Japan'})