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)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)pandas normalize df
# min-max normalization:
df=(df-df.min())/(df.max()-df.min())
# or...
# mean normalization:
df=(df-df.mean())/df.std()Copyright © 2021 Codeinu
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