Normalize data python

>>> from sklearn import preprocessing
>>>
>>> data = [100, 10, 2, 32, 31, 949]
>>>
>>> preprocessing.normalize([data])
array([[0.10467389, 0.01046739, 0.00209348, 0.03349564, 0.03244891,0.99335519]])

Source: educative.io

Normalize data python pandas

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)

Source: stackoverflow.com

Data normalization python

from sklearn import preprocessing
normalizer = preprocessing.Normalizer().fit(X_train)  
X_train = normalizer.transform(X_train)
X_test = normalizer.transform(X_test)

Similar codes

2 votes108 views1 answer
Flask port number
Python
0 vote143 views1 answer
Python set with counts
Python
14 votes156 views3 answers
Pyautogui down arrow
Python
1 vote164 views1 answer
Remove minimize and maximize and cancle button python pyqt5
Python
0 vote115 views1 answer
Which day is today
Python
0 vote190 views4 answers
Plot idl
Python
0 vote155 views1 answer
Modulenotfounderror no module named 'config' python
Python
4 votes157 views2 answers
Freq count in python
Python
15 votes322 views6 answers
Install flask
Python Flask
0 vote285 views1 answer
Django show image in admin page
Python Django