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Practice

Analyzing Sales Data to Derive Insights

In this lesson, we will conduct a simple sales analysis based on the sales data and add quantitative insights derived from the analysis to the report.


How Does the Insight Analysis Code Work?​

The practice code operates in 6 steps as follows:


1. Initialize Variables for Data Analysis​

Initializing Variables
total_sales_by_product = {'Camera': 0, 'Computer': 0, 'Smartphone': 0}

highest_monthly_sales = 0

best_selling_product = ""

  • total_sales_by_product: A dictionary to store the total sales of each product. Initially, it starts at 0 for all products.

  • highest_monthly_sales: Stores the sales of the month with the highest sales.

  • best_selling_product: A variable to store the best-selling product.


2. Read Excel Data and Add to Table​

Adding Excel Data and Creating Table
for row in sheet.iter_rows(min_row=2, values_only=True):
    month, product, sales, price, revenue = row

  • sheet.iter_rows: Reads the data from the Excel sheet row by row. min_row=2 skips the first row (column titles) and only gets the data.

  • values_only=True: Ensures that only the cell values are retrieved.


Creating Table
row_cells = table.add_row().cells
  • Adds a new row to the table.

Adding Data to Table
row_cells[0].text = str(month)
row_cells[1].text = product
row_cells[2].text = str(sales)
row_cells[3].text = str(price)
row_cells[4].text = str(revenue)
  • Adds the data to each cell. Numerical data is converted to text to be inserted as a textual value.

3. Calculate Total Sales by Product and Find the Top-Selling Product​

Calculating Total Sales by Product
total_sales_by_product[product] += revenue
  • total_sales_by_product[product] += revenue: Accumulates the sales for each product.

Finding the Top-Selling Product
if revenue > highest_monthly_sales:
    highest_monthly_sales = revenue
    best_selling_product = product
  • If the sales revenue is greater than the current highest, it updates the highest sales and the corresponding product.

4. Add Sales Analysis Results​

Adding Sales Analysis Results
doc.add_heading('Sales Analysis and Insights', level=1)
  • Adds a heading "Sales Analysis and Insights" to the document.

5. Summary of Total Sales by Product​

Summary of Total Sales by Product
for product, total_sales in total_sales_by_product.items():
    doc.add_paragraph(f"Total sales for {product} in Q1: ${total_sales:,}")
  • doc.add_paragraph: Adds a paragraph to the document summarizing the total sales of each product in Q1.

6. Add the Best-Selling Product​

doc.add_paragraph(f"Best-selling product: {best_selling_product} (Monthly sales: ${highest_monthly_sales:,})")
  • Adds the best-selling product and the sales for the corresponding month to the document.

Sales Analysis and Insights​

  • Total sales for Camera in Q1: $65,400,000

  • Total sales for Computer in Q1: $120,250,000

  • Total sales for Smartphone in Q1: $242,500,000

Best-selling product: Smartphone (Monthly sales: $90,000,000)


We have learned how to analyze Excel data and use Python code to add tables and insights to a report in docx format.

To derive more insights, try advancing the Python code further using an AI code editor. :)

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