Why data frames are central to R in R Programming - See It in Action

Why data frames are central to R

📖 Scenario: Imagine you are a small business owner who wants to keep track of your sales data. You have information about the products sold, the quantity, and the price. You want to organize this data so you can easily analyze it and make decisions.

🎯 Goal: You will create a simple data frame in R to store sales data, add a helper variable for a sales threshold, filter the data based on this threshold, and then display the filtered results. This will show why data frames are central to R for handling tabular data.

📋 What You'll Learn

Create a data frame called sales_data with columns Product, Quantity, and Price using exact values

Create a variable called min_sales with the value 50

Use a subset operation to create a new data frame filtered_sales with rows where Quantity is greater than min_sales

Print the filtered_sales data frame

💡 Why This Matters

🌍 Real World

Data frames help organize and analyze data like sales, customer info, or survey results in a clear table format.

💼 Career

Many jobs in data analysis, statistics, and research use R data frames to handle and explore data efficiently.

1

Create the sales data frame

Create a data frame called sales_data with these exact columns and values: Product with values 'Apples', 'Bananas', 'Cherries'; Quantity with values 30, 60, 45; and Price with values 1.2, 0.5, 2.0.

R Programming

# Create the sales_data data frame with Product, Quantity, and Price columns
# Your code here

Need a hint?

Use the data.frame() function with named vectors for each column.

2

Set the minimum sales threshold

Create a variable called min_sales and set it to the number 50.

R Programming

sales_data <- data.frame(
  Product = c('Apples', 'Bananas', 'Cherries'),
  Quantity = c(30, 60, 45),
  Price = c(1.2, 0.5, 2.0)
)
# Create min_sales variable and set it to 50
# Your code here

Need a hint?

Just assign the number 50 to the variable min_sales.

3

Filter the sales data by quantity

Create a new data frame called filtered_sales that contains only the rows from sales_data where the Quantity is greater than min_sales.

R Programming

sales_data  min_sales
# Your code here

Need a hint?

Use the subset() function to filter rows where Quantity is greater than min_sales.

4

Display the filtered sales data

Print the filtered_sales data frame to show the products with quantity greater than min_sales.

R Programming

sales_data  min_sales)
# Print filtered_sales
# Your code here

Need a hint?

Use the print() function to display the filtered_sales data frame.