A) Assemble a dataframe with one row per customer and the following columns: * customer_id * gender * most_recent_order_date * order_count (number of orders placed by this customer) Sort the dataframe by customer_id ascending and display the first 10 rows. B) Plot the count of orders per week for the store. C) Compute the mean order value for gender 0 and for gender 1. Do you think the difference is significant? Justify your choice of method. D) Generate a confusion matrix for the gender predictions of customers in this dataset. You should assume that there is only one gender prediction for each customer. What does the confusion matrix tell you about the quality of the predictions? E) Describe one of your favorite tools or techniques and give a small example of how it's helped you solve a problem. Limit your answer to one paragraph, and please be specific.