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 ejercicio forma parte del curso
Analyzing Survey Data in Python
Instrucciones del ejercicio
- Find the z-score of the
Agecolumn. - Find the outliers in the survey using the
Age_zscorefor this survey.
Ejercicio interactivo práctico
Prueba este ejercicio y completa el código de muestra.
# 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)