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Fair and square

You want to hold a sports competition for young adults. However, you want to make sure that those who participate have similar abilities, enabling winners to win fair and square. You conduct a survey of young adults called young_people, and ask respondents for their Gender, Age, Height, and Weight.

In this exercise, you will find outliers in the age column.

pandas and scipy.stats have been uploaded for you as pd and stats, respectively.

Este exercício faz parte do curso

Analyzing Survey Data in Python

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Instruções do exercício

  • Find the z-score of the Age column.
  • Find the outliers in the survey using the Age_zscore for this survey.

Exercício interativo prático

Experimente este exercício completando este código de exemplo.

# z-score of `Age` column
young_people['Age_zscore'] = ____.____(young_people.____)

# Outliers in `Age_zscore`
age_outliers = young_people[
  (young_people.____ >= ____)
  |(young_people.____ <= ____)
]
print(age_outliers)
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