Question

(Total Sales) Use a two-dimensional array to solve the following problem: A company has four salespeople \((1 \text { to } 4)\) who sell five different products \((1 \text { to } 5) .\) Once a day, cach salesperson passes in a slip for each type of product sold. Each slip contains the following: a) The salesperson number b) The product number c) The total dollar value of that product sold that day Thus, cach salesperson passes in between 0 and 5 sales slips per day. Assume that the information from all the slips for last month is available. Write an application that will read all this information for last month's sales and summarize the total sales by salesperson and by product. All totals should be stored in the two-dimensional array sales. After processing all the information for last month, display the results in tabular format, with each column representing a particular salesperson and each row representing a particular product. Cross-total each row to get the total sales of each product for last month. Cross-total each column to get the total sales by salesperson for last month. Your tabular output should include these cross- totals to the right of the totaled rows and to the bottom of the totaled columns.

Short answer

Create a 5x4 array, read slips to populate it, then sum rows and columns for totals, and print the table with these totals.

Step-by-step solution

Initializing the Sales Array

Create a two-dimensional array `sales` with dimensions [5][4]. This array will store the total dollar sales where each row corresponds to a product (1 to 5) and each column corresponds to a salesperson (1 to 4). Initialize all elements of the `sales` array to zero.

Reading Sales Slips

Iterate over last month's sales data. For each sales slip, identify the salesperson number, product number, and total sale amount. Use these to update the `sales` array. Specifically, for each slip, increase the corresponding entry in the `sales` array by the sale amount (i.e., `sales[product_number-1][salesperson_number-1] += total_sale_amount`).

Calculating Product and Salesperson Totals

After populating the `sales` array, calculate the total sales for each product and each salesperson. Sum each row to get total sales by product and each column to get total sales by salesperson.

Displaying Results

Print the sales data in a tabular format. Iterate over each product displaying the sales for each product by salesperson, followed by the total sales for that product. At the end of each product row, print the product's total sales. Then add a row at the bottom with the total sales for each salesperson. This row will also have a grand total that sums up the entire array to show total sales.

Key concepts

Sales Data Processing

Processing sales data using a two-dimensional array is an effective way to handle and analyze large amounts of structured information. In this problem, sales slips include the salesperson's ID, product ID, and the sales amount in dollars. Our goal is to sum the total sales by each product and by each salesperson.

To process the sales data, you need to update the entries of a `sales` array based on the sales slips. By iterating through each slip, you add the sale amount to the correct cell in the array. This approach ensures that you correctly accumulate sales for each product by each salesperson. Using a loop that goes over all slips can help maintain readability and efficiency.

By structuring data in this manner, it becomes easy to later extract summaries and perform other analyses.

Array Initialization

In the context of this exercise, initializing a two-dimensional array lays the foundation for effective data handling. Here, the `sales` array is structured with 5 rows, representing products and 4 columns for the salespeople. This structure, therefore, has dimensions [5][4].

Initializing the array with zeros is essential as it avoids any erroneous data leftovers and establishes a clean slate. Every slot in this structured way starts off without any prior influence. As you read in the sales slips, values are added to these initialized values, keeping results accurate.

This step is crucial in the setup, allowing for straightforward accumulation as sales slips are processed and ensures that all results are calculated starting from zero.

Tabular Data Display

Displaying data in a tabular format makes it easy to understand and analyze, especially when dealing with multiple dimensions like salespersons and product categories. In this task, each column represents a salesperson and each row depicts a product. This creates a clear matrix showing who sold what and how much was sold.

Once the sales array is fully processed, presenting the data in a neat table allows users to quickly grasp the sales performance. Adding cross-totals to the right of each row and at the bottom of each column offers comprehensive insights:

• Row Totals: Sum of sales per product.
• Column Totals: Sum of sales per salesperson.

This approach also makes spotting trends, such as which product is most popular or which salesperson is the top performer, much easier.

Cross-Total Calculation

Calculating cross-totals is a key step in summing up the results for analysis. Cross-totals provide a total sales figure for each product across all salespeople and for each salesperson across all products.

The process involves:

• Summing the entries of each row to obtain the total sales for each product.
• Summing the entries of each column to get total sales for each salesperson.

These cross-totals are then added to the table to show cumulative results on the right side for products and at the bottom for salespeople. The overall total, a sum of either the row totals or column totals, helps in understanding the entire month's sales performance.

This method ensures that the analysis is thorough and that stakeholders have actionable insights into sales performance.