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.

Cet exercice fait partie du cours

Anomaly Detection in Python

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Instructions

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.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

# 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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