Normalize data python pandas

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

Pandas normalize df

# min-max normalization:
df=(df-df.min())/(df.max()-df.min())

# or...

# mean normalization:
df=(df-df.mean())/df.std()

Function to scale features in dataframe

# 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

-1

Source: stackoverflow.com

Similar codes

-1 vote297 views1 answer
Expected ")" pylance python
Python
1 vote370 views1 answer
True positive true negative manually
Python
1 vote381 views1 answer
An array of dates python
Python
0 vote358 views1 answer
Add image pptx python
Python
1 vote331 views1 answer
Listas en python
Python
21 votes353 views5 answers
Format string to 2 decimal places python
Python
-1 vote392 views3 answers
List all pip packages
Python
2 votes328 views2 answers
Pandas set options
Python
0 vote315 views1 answer
Serversocket.accept() python
Python
-1 vote348 views1 answer
Python string: the in syntax
Python