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? D) Assuming a single gender prediction was made for each customer, generate a confusion matrix for predicted gender. 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.