Why reproducible reports matter in R Programming - See It in Action

Why reproducible reports matter

📖 Scenario: You work as a data analyst in a company. Your manager asks you to create a report that shows sales data summaries. Later, your manager wants to update the report with new data and check the results quickly. To do this well, you need to make your report reproducible.

🎯 Goal: Build a simple R script that loads sales data, calculates total sales, and prints the result. This script should be easy to run again with new data, showing why reproducible reports matter.

📋 What You'll Learn

Create a data frame called sales_data with exact sales values

Create a variable called threshold to filter sales

Use a for loop with variables product and amount to sum sales above the threshold

Print the total sales amount

💡 Why This Matters

🌍 Real World

Reproducible reports let analysts update data and results quickly without errors or confusion.

💼 Career

Data analysts and scientists use reproducible reports to share clear, trustworthy results with teams and managers.

1

DATA SETUP: Create the sales data frame

Create a data frame called sales_data with these exact entries: product as 'A', 'B', 'C', 'D' and amount as 150, 80, 200, 50.

R Programming

# Create the sales_data data frame with product and amount columns
# Your code here

Need a hint?

Use data.frame() with two columns named product and amount.

2

CONFIGURATION: Set the sales threshold

Create a variable called threshold and set it to 100.

R Programming

sales_data <- data.frame(
  product = c('A', 'B', 'C', 'D'),
  amount = c(150, 80, 200, 50)
)
# Create the threshold variable and set it to 100
# Your code here

Need a hint?

Just assign the number 100 to a variable named threshold.

3

CORE LOGIC: Sum sales above the threshold

Create a variable called total_sales and set it to 0. Then use a for loop with variables product and amount to iterate over sales_data rows. Inside the loop, add amount to total_sales only if amount is greater than threshold.

R Programming

sales_data <- data.frame(
  product = c('A', 'B', 'C', 'D'),
  amount = c(150, 80, 200, 50)
)
threshold <- 100

# Initialize total_sales and sum amounts above threshold using a for loop
# Your code here

Need a hint?

Use a for loop from 1 to the number of rows in sales_data. Extract product and amount inside the loop. Add amount to total_sales only if it is greater than threshold.

4

OUTPUT: Print the total sales

Write a print statement to display the text Total sales above threshold: followed by the value of total_sales.

R Programming

sales_data  threshold) {
    total_sales <- total_sales + amount
  }
}

# Print the total sales with a message
# Your code here

Need a hint?

Use print(paste("Total sales above threshold:", total_sales)) to show the message and value.