Using outlier limits for filtering

In the previous exercise, you found the limits you will use for categorizing outliers. In this exercise, you'll apply them to the prices distribution to isolate the outliers.

The prices, lower_limit, and upper_limit variables are available from the last exercise.

Este exercício faz parte do curso

Anomaly Detection in Python

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Instruções do exercício

Create a boolean mask named is_lower that checks if the values of prices are less than lower_limit.
Create a boolean mask named is_higher that checks if the values of prices are greater than upper_limit.
Combine the masks and use boolean subsetting to filter for outliers.
Print the number of outliers found.

Exercício interativo prático

Experimente este exercício completando este código de exemplo.

# Create a mask for values lower than lower_limit
is_lower = ____

# Create a mask for values higher than upper_limit
is_higher = ____

# Combine the masks to filter for outliers
outliers = ____[____]

# Count and print the number of outliers
____

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