import pandas as pd
from sklearn import preprocessing
x = df.values #returns a numpy array
min_max_scaler = preprocessing.MinMaxScaler()
x_scaled = min_max_scaler.fit_transform(x)
df = pd.DataFrame(x_scaled)
# define a method to scale data, looping thru the columns, and passing a scaler
def scale_data(data, columns, scaler):
for col in columns:
data[col] = scaler.fit_transform(data[col].values.reshape(-1, 1))
return data