We'll tackle this in three parts:
(a) Plot a histogram and boxplot of the Amounts: We'll start by visualizing the distribution of the amounts spent using a histogram and a boxplot. This will help us understand the variation in the data.
(b) Create a cross tabulation of recommendations and purchase decisions: Next, we'll examine the relationship between product recommendations and purchase decisions through a cross tabulation.
(c) Scatter plot and correlation: Finally, using the provided code snippet, we'll create an aggregated DataFrame to analyze the relationship between the amount spent and the proportion of product recommendations clicked. We'll create a scatter plot, label the axes, calculate the correlation, and discuss the relationship.
Let's begin with part (a) by plotting the histogram and boxplot.