Understanding Python Float Literals
Python programs often work with decimal values such as prices, temperatures, measurements, and percentages. These values can be written directly in code as float literals or created during program execution through calculations and other operations.
In this guide, you’ll learn what Python float literals are, their syntax, and how they are used with simple examples.
🚀 Getting Started: Before exploring float literals in depth, take a look at the different types of Python literals available in Python.
💡 Tip: To understand how Python stores and works with floating-point values internally, you can explore our guide on Python float() function.
Introduction: What is a Float Literal?
Definition: A float literal is a numeric value written directly in Python code that contains a decimal point or an exponent part. It represents a floating-point number and can be positive, negative, or fractional.
Example: In the statement price = 99.99, the value 99.99 is a float literal because it is a decimal number written directly in the code.
Before exploring the different forms of Python float literals, let’s first understand their syntax.
Syntax of Python Float Literals
Python float literals can be written using either decimal notation or scientific notation.
| Form | Syntax | Description |
|---|---|---|
| Decimal Notation | variable_name = float_valueExample: 1.5 |
Represents a floating-point number containing a decimal point. |
| Scientific Notation | variable_name = <significant_number>e<exponent_value>Example: 1.5e3 |
Represents a floating-point number using scientific notation, where e (or E) indicates “× 10 raised to the power of.” |
Python float literals can appear in several forms. Let’s explore each of them in detail.
Forms of Python Float Literals
Python float literals can be written in different forms depending on how the numeric value is represented:
- Decimal Float Literals
- Scientific Notation Float Literals
- Float Literals with Multiple Decimal Places
- Float Literals Without a Leading Zero
Let’s explore each form of Python float literal in detail, including its syntax, explanation, and examples.
1. Decimal Float Literals
Decimal float literals are the most commonly used floating-point numbers in Python. They contain a whole part and a fractional part separated by a decimal point.
Example 1: Decimal Float Literal
# Decimal float literal
pi = 3.14159
print(pi)
# Output
3.14159
Explanation: The value 3.14159 is a decimal float literal because it contains a decimal point. Python stores it as a floating-point number.
Example 2: Negative Decimal Float Literal
# Negative decimal float literal
negative_float = -2.5
print(negative_float)
# Output
-2.5
Explanation: The value -2.5 is a negative decimal float literal. The minus sign indicates a negative floating-point number.
2. Scientific Notation Float Literals
Scientific notation is used to represent very large or very small floating-point numbers in a compact form. Python uses the letter e or E to represent “times ten raised to the power of.”
Example 1: Scientific Notation Float Literal
# Scientific notation float literal
large_number = 1.5e3
print(large_number)
# Output
1500.0
Explanation: The value 1.5e3 represents 1.5 × 10³. Python evaluates it as 1500.0.
Example 2: Scientific Notation with Negative Exponent
# Scientific notation with a negative exponent
small_number = 2e-3
print(small_number)
# Output
0.002
Explanation: The value 2e-3 represents 2 × 10⁻³, which is equal to 0.002.
3. Float Literals with Multiple Decimal Places
Python allows float literals to contain many digits after the decimal point. This is useful when working with measurements, scientific calculations, and other applications that require greater precision.
Example: Float Literal with Multiple Decimal Places
# Float literal with multiple decimal places
precise_value = 0.000123456789
print(precise_value)
# Output
0.000123456789
Explanation: The value 0.000123456789 is a float literal containing multiple decimal places. Python stores the value as a floating-point number.
4. Float Literals Without a Leading Zero
Python allows the leading zero before the decimal point to be omitted. Although writing 0.5 is generally recommended for better readability, values such as .5 and -.5 are valid float literals.
Example: Float Literal Without a Leading Zero
# Float literal without a leading zero
half_value = .5
print(half_value)
# Output
0.5
Explanation: The value .5 is a valid float literal and is interpreted by Python as 0.5.
Key Examples at a Glance: Float Literals
The following table summarizes the different types of Python float literals with their formats and examples:
| Type | Format | Example | Meaning |
|---|---|---|---|
| Decimal Float Literal | Whole number + decimal part | 3.14159, -2.5 |
Standard floating-point numbers |
| Scientific Notation | number e exponent |
1.5e3 |
Represents 1.5 × 10³ = 1500.0 |
| Scientific Notation with Negative Exponent | number e -exponent |
2e-3 |
Represents 2 × 10⁻³ = 0.002 |
| Float Literal with Multiple Decimal Places | Multiple decimal places | 0.000123456789 |
Floating-point value with multiple decimal digits |
| Shorthand Float | No leading zero | .5, -.5 |
Equivalent to 0.5 and -0.5 |
Key Takeaways: Float Literals
Here are the key points to remember about Python float literals:
- A float literal is a floating-point number written directly in Python code.
- Float literals contain a decimal point or an exponent part.
- Python supports decimal notation and scientific notation for representing floating-point values.
- Float literals can represent positive, negative, and fractional numbers.
- Float literals are widely used in scientific, financial, engineering, and everyday calculations.