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.
This exercise is part of the course
Analyzing Survey Data in Python
Exercise instructions
- Find the z-score of the
Age
column. - Find the outliers in the survey using the
Age_zscore
for this survey.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# 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)