Python MinMaxScaler()
from sklearn.preprocessing import MinMaxScaler #Normal minmaxscaler function to standarise data. data = [[-1, 2], [-0.5, 6], [0, 10], [1, 18]] scaler = MinMaxScaler() scaler.fit(data) #get data for Max and Min from scaler functions, #best to store it in a dictionary and use it later make data normal again print(scaler.transform([[2, 2]])) Out>>> [[ 1.5 0. ]] # Inverse transform the the 0-1 dataframe. print(scaler.inverse_transform([[ 1.5 0. ]])) Out>>> [[ 2.0 2.0]]
