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.
Diese Übung ist Teil des Kurses
Analyzing Survey Data in Python
Anleitung zur Übung
- Find the z-score of the
Agecolumn. - Find the outliers in the survey using the
Age_zscorefor this survey.
Interaktive Übung
Vervollständige den Beispielcode, um diese Übung erfolgreich abzuschließen.
# 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)