One hot encoding

One hot encoding python pandas

y = pd.get_dummies(df.Countries, prefix='Country')
print(y.head())
# from here you can merge it onto your main DF

Source: stackabuse.com

One hot encoding numpy

  labels = (np.arange(num_labels) == labels[:,None]).astype(np.float32)

One hot encoding

from sklearn.preprocessing import OneHotEncoder
encoder = preprocessing.OneHotEncoder(handle_unknown='ignore')
y = np.array([1, 2, 1, 3])
y = y.reshape(-1,1)
encoder.fit(y)
y_oh = encoder.transform(y).toarray()
print(y_oh)
>>[[1. 0. 0.]
 [0. 1. 0.]
 [1. 0. 0.]
 [0. 0. 1.]]

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