Why text processing is common in R Programming - See It in Action

Why Text Processing is Common

📖 Scenario: Imagine you work at a company that collects customer feedback through online reviews. These reviews are written in plain text. To understand what customers like or dislike, you need to process this text data.

🎯 Goal: You will create a simple R program that stores some customer reviews, sets a keyword to search for, counts how many reviews contain that keyword, and then prints the count. This shows why text processing is common: to find useful information in written data.

📋 What You'll Learn

Create a vector called reviews with exactly these three strings: "Great product, fast delivery", "Poor packaging, but good quality", "Excellent customer service"

Create a variable called keyword and set it to the string "good"

Use a for loop with the variable review to go through each element in reviews

Inside the loop, check if keyword is found in review using grepl()

Create a variable called count to keep track of how many reviews contain the keyword

Print the final value of count

💡 Why This Matters

🌍 Real World

Companies often collect customer feedback, social media posts, or product reviews as text. Processing this text helps find common opinions or problems quickly.

💼 Career

Text processing skills are useful for jobs in data analysis, marketing, customer support, and anywhere understanding written feedback or documents is important.

1

Create the reviews vector

Create a vector called reviews with exactly these three strings: "Great product, fast delivery", "Poor packaging, but good quality", and "Excellent customer service"

R Programming

# Create the reviews vector
# Your code here

Need a hint?

Use the c() function to create a vector with the three exact strings.

2

Set the keyword variable

Create a variable called keyword and set it to the string "good"

R Programming

reviews <- c("Great product, fast delivery", "Poor packaging, but good quality", "Excellent customer service")
# Create the keyword variable
# Your code here

Need a hint?

Assign the string "good" to the variable keyword.

3

Count reviews containing the keyword

Create a variable called count and set it to 0. Then use a for loop with the variable review to go through each element in reviews. Inside the loop, use grepl(keyword, review) to check if keyword is in review. If yes, add 1 to count.

R Programming

reviews <- c("Great product, fast delivery", "Poor packaging, but good quality", "Excellent customer service")
keyword <- "good"
# Create count variable and loop through reviews
# Your code here

Need a hint?

Start count at 0. Use a for loop to check each review. Use grepl() to find the keyword.

4

Print the count

Write a print() statement to display the value of count

R Programming

reviews <- c("Great product, fast delivery", "Poor packaging, but good quality", "Excellent customer service")
keyword <- "good"
count <- 0
for (review in reviews) {
  if (grepl(keyword, review)) {
    count <- count + 1
  }
}
# Print the count
# Your code here

Need a hint?

Use print(count) to show how many reviews contain the keyword.