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

0 vote333 views1 answer
Python messaging networking
Python
0 vote393 views1 answer
Flask admin forgeign keys show literal
Python Flask
0 vote370 views1 answer
Csr_matric scipy lib
Python
0 vote389 views1 answer
Windows 10 reset django migrations
Python Django
0 vote332 views2 answers
Java to python conversion
Python
0 vote325 views2 answers
Remove nans and infs python
Python
2 votes333 views2 answers
What is a print statement
Python
2 votes361 views1 answer
Fill zero behind number python
Python
0 vote342 views1 answer
Travis deployment script for django applications to heroku
Python
5 votes375 views1 answer
Write multiple df to excel pandas
Python