convert categorical variable to numeric pandas code example

Example 1: convert column to numeric pandas

# convert all columns of DataFrame
df = df.apply(pd.to_numeric) # convert all columns of DataFrame

# convert just columns "a" and "b"
df[["a", "b"]] = df[["a", "b"]].apply(pd.to_numeric)

Example 2: pandas categorical to numeric

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

Example 3: panda categorical data into numerica

sex = train_dataset['Sex'].replace(['female','male'],[0,1])
print(sex)

Example 4: 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)

Example 5: pandas categorical to numeric

#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'})