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Learn Challenge: Scaling the Features | Preprocessing Data with Scikit-learn
ML Introduction with scikit-learn

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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).

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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)
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Here is a little reminder of the StandardScaler class.

Task

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  1. Import the class that standardizes features by making the mean equal to 0 and the variance equal to 1.
  2. Initialize the scaler.
  3. Scale the X matrix of features.

Solution

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SectionΒ 2. ChapterΒ 11
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book
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).

12345
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)
copy

Here is a little reminder of the StandardScaler class.

Task

Swipe to start coding

  1. Import the class that standardizes features by making the mean equal to 0 and the variance equal to 1.
  2. Initialize the scaler.
  3. Scale the X matrix of features.

Solution

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

close

Awesome!

Completion rate improved to 3.13

Swipe to show menu

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