Challenge: Scaling the Features
In this challenge, you need to scale the features using StandardScaler. The data is the penguins dataset (encoded and with no missing values).
import pandas as pd
df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a65bbc96-309e-4df9-a790-a1eb8c815a1c/penguins_imputed_encoded.csv')
print(df)
import pandas as pd df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a65bbc96-309e-4df9-a790-a1eb8c815a1c/penguins_imputed_encoded.csv') print(df)
Here is a little reminder of the StandardScaler class.
Завдання
Swipe to start coding
- Import the class that standardizes features by making the mean equal to 0 and the variance equal to 1.
- Initialize the scaler.
- Scale the
Xmatrix of features.
Рішення
import pandas as pd
from sklearn.preprocessing import StandardScaler
df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a65bbc96-309e-4df9-a790-a1eb8c815a1c/penguins_imputed_encoded.csv')
# Assign X,y variables
X, y = df.drop('species', axis=1), df['species']
# Initialize a sclaer and scale the X matrix
scaler = StandardScaler()
X = scaler.fit_transform(X)
print(X)
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Секція 2. Розділ 11
import pandas as pd
from sklearn.preprocessing import ___
df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a65bbc96-309e-4df9-a790-a1eb8c815a1c/penguins_imputed_encoded.csv')
# Assign X,y variables
X, y = df.drop('species', axis=1), df['species']
# Initialize a sclaer and scale the X matrix
scaler = ___
X = ___
print(X)
