Operators & Expressions

So far, you have learned how to store values in variables, how to name them clearly, and how Python distinguishes between different data types.

In this section, we focus on how values interact. We start with simple calculations, then build up to comparisons, logic, and module-based mathematical expressions.

1. Expressions as Calculations¶

An expression is a combination of values (operands) and operators that produces a result.

Think of an expression as a question you ask Python: “What is the result of this calculation right now?”

An important idea is that expressions are evaluated when you run the cell, not when you type them. If you change a variable and run the cell again, Python recalculates the result using the newest values in memory.

2. Arithmetic Operators¶

Arithmetic operators allow you to perform calculations with numeric values. They are used inside expressions to combine values and produce new results.

At this stage, we focus only on numeric operations.

Basic Arithmetic¶

Python supports the common arithmetic operators you already know.

Each expression is evaluated when the cell is executed and returns a numeric result.

Using Variables as Operands¶

Arithmetic operators do not only work with literal numbers. They also work with variables that store numbers.

Here, x and y are operands. An operand is simply a value or a variable that an operator acts on.

Exponentiation¶

Python uses ** to raise a value to a power.

This means two to the power of three.

Optional but Useful Operators¶

Some additional arithmetic operators are useful in practice.

The modulus operator returns the remainder of a division.

Floor division returns the number of whole divisions.

You will encounter these operators later in loops, indexing, and data processing.

Overview of Arithmetic Operators¶

3. Assignment and Update Operators¶

So far, we have used expressions to compute values. Now we look at how those results are stored and updated using assignment operators.

This section connects operators back to variables.

Assignment with =¶

The assignment operator = stores the result of an expression in a variable.

Here, Python:

1. evaluates the expression on the right

2. stores the resulting value

3. assigns it to the variable name on the left

Assignment itself does not produce output. It only changes what value a variable refers to.

Assignment Stores Results¶

You can assign the result of any expression.

The expression 2 + 3 is evaluated first. Only the resulting value is stored.

Python does not remember how the value was computed.

Update Operators as Shorthand¶

Python provides update operators that combine calculation and assignment.

This is a shorter way of writing:

Other common update operators follow the same pattern.

Each update:

• evaluates the expression

• replaces the old value

• stores the new value in the variable

What Actually Changes¶

An important mental model is this:

Variables do not remember previous values.

After reassignment, the old value is gone.

After the second line, speed refers only to 80. The value 50 is no longer stored anywhere.

4. Comparison Operators¶

Comparison operators allow you to compare values. Instead of producing numbers, comparisons produce logical boolean results: True or False.

These operators are essential for filtering spatial data (e.g., “find all cities with a population greater than 100,000”).

Data Types Matter: Comparisons depend heavily on data types. 5 == "5" will evaluate to False because an integer is never equal to a string!

Comparison operators are used to control program flow, filter data and make decisions based on conditions.

5. Logical Operators¶

Logical operators allow you to combine multiple comparison results into a single True or False answer.

Python provides three logical operators:

• and: Returns True only if both conditions are true.

• or: Returns True if at least one condition is true.

• not: Reverses the boolean value.

Logical operators allow you to express complex reasoning in code. Instead of asking one question, you can combine several and get a single, definitive answer.

6. Operator Behaviour & Data Types¶

Operators do not behave the same way for all data types. What an operator does depends entirely on what kind of values it is applied to.

When applied to numbers (int, float), the + and * operators perform standard arithmetic. But look what happens when we apply them to strings (str):

If you try to mix incompatible data types, the operation will fail:

This is not a bug; it is Python protecting you from an undefined operation. If an operation fails, check your data types!

7. Using Functions in Expressions¶

Expressions can also include functions. Functions take an input, perform a complex calculation behind the scenes, and return a value that you can use mathematically.

To access advanced mathematical functions, we must import the math module (a built-in library of extra Python tools).

Modules also provide useful constants, which do not require parentheses because they are stored values, not functions:

8. Inspecting Expression Results¶

When expressions become complex, it is helpful to inspect intermediate results to ensure your logic is correct.

You can use the print() function to combine text and expression results for highly readable debugging output:

Well-formatted output makes checking your work significantly easier and is a fundamental debugging habit.

9. Short Exercises¶

Exercise 1: Expressions as Calculations¶

Focus: Understanding expressions and execution

Task:

1. Write three different arithmetic expressions (one addition, one multiplication, one exponentiation).

2. Run each expression in its own code cell.

3. Change one number in the code and do not re-run the cell yet. Does the output change automatically?

2 + 3        # addition
4 * 5        # multiplication
2 ** 3       # exponentiation

Exercise 2: Operators, Variables, and Data Types¶

Focus: Variables, arithmetic, comparisons

Task: Given the following variables:

1. Compute the average speed in km/h and store it in a new variable.

2. Create a boolean variable that checks whether the speed is greater than 70 km/h.

3. Print a readable message that includes both the speed and the boolean result.

# Compute average speed
speed_kmh = distance_km / time_hours

# Comparison produces a boolean
speed_above_70 = speed_kmh > 70

# Print a readable message
print("The average speed is", speed_kmh, "km/h. Speed above 70 km/h:", speed_above_70)

Exercise 3: Combining Comparisons, Logic, and Functions¶

Focus: Logical operators, modules, nested expressions

Task:

1. Import the math module.

2. Define a variable angle_deg = 30.

3. Convert the angle to radians (Formula: angle * math.pi / 180).

4. Compute the sine of the angle using math.sin().

5. Use logical operators to check if the sine value is both greater than 0 and less than 1.

import math

angle_deg = 30
angle_rad = angle_deg * math.pi / 180

sin_value = math.sin(angle_rad)

# Combine conditions using 'and'
valid_range = (sin_value > 0) and (sin_value < 1)

print("Sine value:", sin_value, "| Is valid:", valid_range)

10. Summary¶

After completing this section, you should understand that:

• Expressions combine values and operators to produce a single result.

• Expressions are evaluated when code is executed.

• Arithmetic operators (+, -, *, /, **, %, //) act as a calculator.

• Comparison operators (==, >, <=) always produce boolean values (True or False).

• Logical operators (and, or, not) combine boolean conditions to build complex reasoning.

• Operator behavior changes depending on data types (e.g., + adds numbers but joins strings).

Looking Ahead¶

Expressions are the foundation for making decisions in code. In the next section, we will take a deeper dive into Strings. Strings behave uniquely, especially when combined, sliced, or formatted. Isolating these behaviors early helps keep numeric reasoning clear while building your confidence with text handling.