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Computing the support metric

In the previous exercise, you one-hot encoded a small grocery store's transactions as the DataFrame onehot. In this exercise, you'll make use of that DataFrame and the support metric to help the store's owner. First, she has asked you to identify frequently purchased items, which you'll do by computing support at the item-level. And second, she asked you to check whether the rule {jam} \(\rightarrow\) {bread} has a support of over 0.05. Note that onehot has been defined and is available. Additionally, pandas has been imported under the alias pd and numpy has been imported under the alias np.

This exercise is part of the course

Market Basket Analysis in Python

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Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Compute the support
support = onehot.____()

# Print the support
print(____)
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