from sklearn.preprocessing import MinMaxScaler

scaler = MinMaxScaler()
scores = scaler.fit_transform(df["a"].values.reshape(-1,1))

91bbdc6b5c86932aff5dad03759710dd3174c7d2
<mask token>

<mask token>
scaler = MinMaxScaler()
scores = scaler.fit_transform(df['a'].values.reshape(-1, 1))

from sklearn.preprocessing import MinMaxScaler
scaler = MinMaxScaler()
scores = scaler.fit_transform(df['a'].values.reshape(-1, 1))

from sklearn.preprocessing import MinMaxScaler

scaler = MinMaxScaler()
scores = scaler.fit_transform(df["a"].values.reshape(-1,1))
