Data Standardization
Another approach to scale the data is to standardize it: transform in such a way that mean is equal to 0 and std is equal to 1. Look at the formula:
Here μ is a mean value of x and σ is a standard deviation. This way, we move each value such that total mean is 0, and normalize it with std, so new std is equal to 1.
Aufgabe
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Standardize the data in SibSp column by calculating mean and std values and use the formula above. Output some sample to see the modified data and check if the new values of mean and std are equal to 0 and 1 respectively.
Lösung
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import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/10db3746-c8ff-4c55-9ac3-4affa0b65c16/titanic.csv')
sibsp = data['SibSp']
mean, std = sibsp.mean(), sibsp.std()
sibsp = (sibsp - mean) / std
print(sibsp.sample(10))
new_mean, new_std = sibsp.mean(), sibsp.std()
print(round(new_mean, 2), round(new_std, 2))
War alles klar?
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Abschnitt 4. Kapitel 2
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import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/10db3746-c8ff-4c55-9ac3-4affa0b65c16/titanic.csv')
sibsp = data['SibSp']
# standardize the sibsp
print(sibsp.sample(10))
# check the new values of mean and std
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