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
.
Este exercício faz parte do curso
Market Basket Analysis in Python
Exercício interativo prático
Experimente este exercício completando este código de exemplo.
# Compute the support
support = onehot.____()
# Print the support
print(____)