In [90]: df = pd.DataFrame(np.random.randn(5, 3), index=list('abcde'), columns=list('xyz'))
In [91]: df
Out[91]:
x y z
a -0.325882 -0.299432 -0.182373
b -0.833546 -0.472082 1.158938
c -0.328513 -0.664035 0.789414
d -0.031630 -1.040802 -1.553518
e 0.813328 0.076450 0.022122
In [92]: from sklearn.preprocessing import MinMaxScaler
In [93]: mms = MinMaxScaler()
In [94]: df[['x','z']] = mms.fit_transform(df[['x','z']])
In [95]: df
Out[95]:
x y z
a 0.308259 -0.299432 0.505500
b 0.000000 -0.472082 1.000000
c 0.306662 -0.664035 0.863768
d 0.486932 -1.040802 0.000000
e 1.000000 0.076450 0.580891