Handling missing values (na.rm, na.omit) in R Programming - Mini Project: Build & Apply

Handling missing values (na.rm, na.omit)

📖 Scenario: You have collected temperature readings for a week, but some values are missing. You want to calculate the average temperature, ignoring the missing values.

🎯 Goal: Build a small R program that creates a vector with missing values, sets a helper variable to handle missing data, calculates the average temperature ignoring missing values, and prints the result.

📋 What You'll Learn

Create a numeric vector called temps with exactly these values: 23, NA, 25, 22, NA, 24, 26

Create a logical variable called remove_na and set it to TRUE

Calculate the average temperature using the mean() function with the argument na.rm = remove_na

Print the average temperature using print()

💡 Why This Matters

🌍 Real World

Handling missing data is common in real-world data analysis, like weather data, surveys, or sensor readings where some values might be missing.

💼 Career

Data analysts and scientists must know how to handle missing values to get accurate results and avoid errors in reports or models.

1

Create the temperature vector with missing values

Create a numeric vector called temps with these exact values: 23, NA, 25, 22, NA, 24, 26

R Programming

# Create the temps vector with missing values
# Your code here

Need a hint?

Use the c() function to create a vector. Use NA to represent missing values.

2

Set the helper variable to remove missing values

Create a logical variable called remove_na and set it to TRUE

R Programming

temps <- c(23, NA, 25, 22, NA, 24, 26)
# Create remove_na variable and set it to TRUE
# Your code here

Need a hint?

Use <- to assign TRUE to remove_na.

3

Calculate the average temperature ignoring missing values

Calculate the average temperature using the mean() function with the argument na.rm = remove_na and store it in a variable called avg_temp

R Programming

temps <- c(23, NA, 25, 22, NA, 24, 26)
remove_na <- TRUE
# Calculate average temperature ignoring missing values
# Your code here

Need a hint?

Use mean(temps, na.rm = remove_na) to calculate the average ignoring missing values.

4

Print the average temperature

Print the variable avg_temp using the print() function

R Programming

temps <- c(23, NA, 25, 22, NA, 24, 26)
remove_na <- TRUE
avg_temp <- mean(temps, na.rm = remove_na)
# Print the average temperature
# Your code here

Need a hint?

Use print(avg_temp) to display the average temperature.