# Encoder

<code py>
from sklearn.preprocessing import OneHotEncoder, LabelEncoder

oe = OneHotEncoder()
oe_result = oe.fit_transform(train['workclass'].values.reshape(-1,1)).toarray()

oe.get_feature_names(['workclass'])

pd.DataFrame(data=oe_result, columns=oe.get_feature_names(['workclass']))


le = LabelEncoder()
le.fit_transform(train['workclsss'].values.reshape(-1,1))

workclass_to_num = dict(zip(train['workclass'].unique(), range(0,10)))

train['workclass'].map(workclass_to_num)

</code>

### onehot 인코딩 일괄적으로 

<code>
dummied = pd.get_dummies(train)
</code>