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 vote335 views1 answer
50 terms of fibonacci sequence python
Python
1 vote352 views2 answers
Python dataframe remove header
Python
0 vote338 views1 answer
Pyfiglet not coming up
Python
4 votes373 views1 answer
Format python limit to {:2f}
Python
0 vote378 views1 answer
How to install threading module in python
Python
0 vote337 views1 answer
Json on desktop python
Python
0 vote352 views1 answer
Ssl server python
Python
31 votes393 views3 answers
How to add one to the index of a list
Python
8 votes370 views2 answers
Import math sqrt python
Python
0 vote398 views1 answer
Django dumpdata specific app
Python Django