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 vote148 views1 answer
How to Create a Pie Chart in Seaborn
Python
2 votes117 views1 answer
What does * mean in python in functions
Python
0 vote107 views1 answer
Pytorch forecasting
Python
0 vote170 views2 answers
Fetch api flask url redirect
Python Flask
16 votes133 views1 answer
Python reload file if changed
Python
0 vote191 views1 answer
Simulate robot arm using python
Python
1 vote144 views1 answer
How to restart loop python
Python
27 votes118 views5 answers
Panda python install
Python
0 vote133 views1 answer
WARNING: Ignoring invalid distribution c program files python39libsite-packages
Python
0 vote112 views1 answer
Configparser error reading relative file path
Python