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Data Types in Python

bookUnderstanding Numeric Types

Numbers are everywhere in Python. You'll use two core numeric types most of the time: integers (int) for whole numbers and floating-point numbers (float) for decimals (including scientific notation like 1e-3).

Integer and Float Essentials

  • Integers (int): whole numbers such as -2, 0, 7, 456566. Python supports arbitrarily large integers;
  • Floats (float): decimal values such as 2.5, 3.14159, 2.71828, or scientific notation like 6.02e23;
  • Truthiness: 0 and 0.0 are False; any other int/float is True in boolean contexts.

              
123456

            
# Basic numeric literals (no type checks or conversions here)
n_int = 42
n_float = 3.14
n_sci = 1e-3   # 0.001

print(n_int, n_float, n_sci)
copy

Writing Large Numbers Readably

Humans often write 1,000,000 or 1 000 000. Python doesn't allow commas or spaces inside numeric literals; use underscores for readability.


              
12

            
million = 1_000_000
print(million == 1000000)   # True
copy
Note
Note

Floats are stored as binary fractions; tiny rounding differences are normal (e.g., 0.1 + 0.2 may not be exactly 0.3). You'll handle rounding and formatting later.

1. What is the type of 1e2?

2. Which literal is valid in Python code for one million?

3. Pick the true statement about int and float.

question mark

What is the type of 1e2?

Select the correct answer

question mark

Which literal is valid in Python code for one million?

Select the correct answer

question mark

Pick the true statement about int and float.

Select the correct answer

Tout était clair ?

Comment pouvons-nous l'améliorer ?

Merci pour vos commentaires !

Section 1. Chapitre 1

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bookUnderstanding Numeric Types

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Numbers are everywhere in Python. You'll use two core numeric types most of the time: integers (int) for whole numbers and floating-point numbers (float) for decimals (including scientific notation like 1e-3).

Integer and Float Essentials

  • Integers (int): whole numbers such as -2, 0, 7, 456566. Python supports arbitrarily large integers;
  • Floats (float): decimal values such as 2.5, 3.14159, 2.71828, or scientific notation like 6.02e23;
  • Truthiness: 0 and 0.0 are False; any other int/float is True in boolean contexts.

              
123456

            
# Basic numeric literals (no type checks or conversions here)
n_int = 42
n_float = 3.14
n_sci = 1e-3   # 0.001

print(n_int, n_float, n_sci)
copy

Writing Large Numbers Readably

Humans often write 1,000,000 or 1 000 000. Python doesn't allow commas or spaces inside numeric literals; use underscores for readability.


              
12

            
million = 1_000_000
print(million == 1000000)   # True
copy
Note
Note

Floats are stored as binary fractions; tiny rounding differences are normal (e.g., 0.1 + 0.2 may not be exactly 0.3). You'll handle rounding and formatting later.

1. What is the type of 1e2?

2. Which literal is valid in Python code for one million?

3. Pick the true statement about int and float.

question mark

What is the type of 1e2?

Select the correct answer

question mark

Which literal is valid in Python code for one million?

Select the correct answer

question mark

Pick the true statement about int and float.

Select the correct answer

Tout était clair ?

Comment pouvons-nous l'améliorer ?

Merci pour vos commentaires !

Section 1. Chapitre 1
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