🔢 R Numbers – Complete Tutorial

In R, numbers are the foundation of data analysis, statistics, and scientific computing.
R supports multiple numeric data types, automatic type conversion, and vectorized operations.

1️⃣ What are Numbers in R?

R mainly works with numeric values, which can be:

• Integers

• Decimals (double / numeric)

📌 By default, R treats numbers as double (numeric).

2️⃣ Types of Numbers in R ⭐

1. Numeric (Double)

✔ Can store decimals
✔ Default number type

2. Integer

📌 L suffix makes number integer

3. Complex Numbers

✔ Used in advanced mathematics

4. Logical as Numbers

3️⃣ Checking Number Type ⭐

4️⃣ Numeric Constants in R

5️⃣ Creating Numeric Vectors ⭐

6️⃣ Operations on Numbers ⭐

7️⃣ Integer Division & Modulus

8️⃣ Type Conversion (Coercion) ⭐

📌 R performs implicit coercion when needed.

9️⃣ NA, NaN, Inf – Important Concepts ⚠️

🔟 Handling NA in Numbers ⭐

1️⃣1️⃣ Rounding Numbers ⭐

1️⃣2️⃣ Common Mistakes ❌

❌ Forgetting L for integers
❌ Confusing NA with NaN
❌ Ignoring missing values
❌ Expecting integer output without coercion

📌 Interview Questions & MCQs

Q1. Default numeric type in R?

A) Integer
B) Double
C) Float
D) Logical

✅ Answer: B

Q2. How to create an integer in R?

A) 10
B) int(10)
C) 10L
D) as.int(10)

✅ Answer: C

Q3. Output of as.numeric(TRUE)?

A) 0
B) 1
C) TRUE
D) Error

✅ Answer: B

Q4. Which value represents missing data?

A) NaN
B) NULL
C) NA
D) Inf

✅ Answer: C

Q5. Output of 1/0?

A) Error
B) NA
C) NaN
D) Inf

✅ Answer: D

🔥 Real-Life Use Cases

✔ Statistical calculations
✔ Financial modeling
✔ Scientific computing
✔ Data science projects
✔ Machine learning

✅ Summary

• R supports numeric, integer, complex numbers

• Default numeric type is double

• R is vectorized for numeric operations

• Handle NA, NaN, Inf carefully

• Essential topic for R exams, interviews & data analysis