get all the columns with non-numeric data. # Then create dummy variables for those columns python code example

Example 1: pandas categorical to numeric

#this will label the different catagories as 0,1,2,3....
dataset["sex"] = dataset["sex"].astype('category').cat.codes

Example 2: transform categorical variables python

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)