Lesson 12: Python Dictionary Methods & If / Elif / Else Conditions

Lesson Introduction

Welcome to Lesson 12! In this lesson, you will master two powerful areas of Python programming:

Part 1 — Dictionary Methods: Python gives you a built-in toolkit of methods (special actions) that let you do powerful things with dictionaries — like safely reading values, adding new data, removing items, copying, and viewing keys/values in loops. You will learn all 11 official dictionary methods with clear examples.

Part 2 — If / Elif / Else Conditions: Computers make decisions just like humans do. When you wake up and check if it is raining, you decide whether to carry an umbrella. Python does the same — using if, elif, and else to make decisions based on conditions. This section teaches you everything about decision-making in Python, from the simplest if check to multi-branch elif chains.

By the end of this lesson you will be able to:

  • Use all 11 dictionary methods confidently
  • Write if, elif, and else statements correctly
  • Combine dictionaries with conditions to build smart, real-world programs
  • Complete a mini student report card project

What You Need to Know First (Prerequisites)

Before continuing, make sure you are comfortable with these concepts. If any of them feel unfamiliar, here is a quick refresher:

What is a Dictionary?

A dictionary is a Python data structure that stores information in key-value pairs. Think of it like a real-world dictionary: you look up a word (the key) and get its meaning (the value).

# A simple dictionary
student = {
    "name": "Amara",
    "age": 17,
    "grade": "A"
}
  • "name", "age", "grade" are keys — they are labels for your data
  • "Amara", 17, "A" are values — they are the actual data

You access a value using its key:

print(student["name"])   # Output: Amara
print(student["age"])    # Output: 17

What is a Method?

A method is a built-in action that belongs to a data type. You call it using a dot (.) after the variable name. For example:

my_dict.keys()    # The keys() method belongs to dictionaries
my_list.append()  # The append() method belongs to lists

Think of methods as the dictionary’s own built-in tools.

What is a Boolean?

A Boolean is a value that is either True or False. This is the foundation of all conditions in Python.

is_raining = True
is_sunny = False

What is a Comparison Operator?

Comparison operators compare two values and produce a Boolean result (True or False):

Operator Meaning Example Result
== Equal to 5 == 5 True
!= Not equal to 5 != 3 True
> Greater than 10 > 3 True
< Less than 2 < 8 True
>= Greater than or equal to 5 >= 5 True
<= Less than or equal to 4 <= 6 True

PART 1: Python Dictionary Methods

Section 1 — What Are Dictionary Methods and Why Do They Exist?

Imagine you have a dictionary of student scores, and you want to:

  • Safely check if a student’s score exists without crashing your program
  • Get a list of all student names
  • Remove a student from the dictionary
  • Make a copy so you don’t accidentally change the original

Doing all of this manually (writing many lines of code from scratch) would be tedious and error-prone. Python’s dictionary methods are pre-built, ready-to-use tools that do all of this for you in one line.

Python has 11 built-in dictionary methods:

Method What It Does
clear() Removes all items from the dictionary (empties it)
copy() Makes a shallow copy of the dictionary
fromkeys() Creates a new dictionary from a list of keys, with a shared value
get() Safely returns the value for a key (no crash if key is missing)
items() Returns all key-value pairs as a list of tuples
keys() Returns all keys in the dictionary
pop() Removes a specific key and returns its value
popitem() Removes and returns the last inserted key-value pair
setdefault() Returns a key’s value; inserts the key with a default if it doesn’t exist
update() Adds or updates multiple key-value pairs at once
values() Returns all values in the dictionary

We will go through each one clearly with examples.

Method 1: keys() — Get All Keys

What Is It?

keys() returns a special view object that lists all the keys (labels) in your dictionary.

Why use it? When you want to see what keys exist, loop through them, or check if a key is in your dictionary.

Simple Example

person = {"name": "Chidi", "age": 25, "city": "Lagos"}

all_keys = person.keys()
print(all_keys)

Expected Output:

dict_keys(['name', 'age', 'city'])

💡 The output shows dict_keys([...]) — this is a special view object, not a regular list. But you can use it in loops just like a list!

Using keys() in a Loop

person = {"name": "Chidi", "age": 25, "city": "Lagos"}

for key in person.keys():
    print(key)

Expected Output:

name
age
city

Line-by-line explanation:

  • for key in person.keys(): — loop through every key in the dictionary
  • print(key) — print each key on its own line

Checking If a Key Exists Using in

person = {"name": "Chidi", "age": 25, "city": "Lagos"}

print("name" in person.keys())    # Output: True
print("salary" in person.keys())  # Output: False

🤔 Thinking prompt: What would happen if you tried person["salary"] directly? You would get a KeyError! That is why checking first (or using .get()) is so important.

Method 2: values() — Get All Values

What Is It?

values() returns a view of all the values in your dictionary.

Why use it? When you only care about the data, not the labels — for example, calculating the total of all scores.

Simple Example

scores = {"maths": 85, "english": 90, "science": 78}

print(scores.values())

Expected Output:

dict_values([85, 90, 78])

Looping Through Values

scores = {"maths": 85, "english": 90, "science": 78}

for score in scores.values():
    print(score)

Expected Output:

85
90
78

Practical Use — Calculating the Total

scores = {"maths": 85, "english": 90, "science": 78}

total = sum(scores.values())
print("Total score:", total)

Expected Output:

Total score: 253

Explanation:

  • sum(scores.values()) — Python’s built-in sum() function adds all the values together
  • The result is stored in total and printed

Method 3: items() — Get All Key-Value Pairs

What Is It?

items() returns a view of all key-value pairs. Each pair is wrapped in a tuple — a bracket () that holds two items: the key and the value.

Why use it? When you want to loop through a dictionary and need both the key AND the value at the same time.

Simple Example

student = {"name": "Fatima", "score": 92, "grade": "A"}

print(student.items())

Expected Output:

dict_items([('name', 'Fatima'), ('score', 92), ('grade', 'A')])

Each pair like ('name', 'Fatima') is a tuple — the key comes first, then the value.

Looping with items() — The Most Common Pattern

student = {"name": "Fatima", "score": 92, "grade": "A"}

for key, value in student.items():
    print(key, "->", value)

Expected Output:

name -> Fatima
score -> 92
grade -> A

Line-by-line explanation:

  • for key, value in student.items(): — for each pair, Python automatically unpacks it into two variables: key and value
  • print(key, "->", value) — print both the key and its value with an arrow between them

💡 This is one of the most commonly used patterns in all of Python programming! You will use it constantly.

Method 4: get() — Safely Read a Value

What Is It?

get(key) returns the value for the given key. But unlike dict[key], it does not crash if the key doesn’t exist — it returns None (or a default value you choose) instead.

Why use it? To safely read dictionary values without risking a KeyError crash.

The Problem Without get()

person = {"name": "Emeka", "age": 30}

# This CRASHES with a KeyError if 'salary' doesn't exist:
print(person["salary"])   # KeyError: 'salary'

The Safe Way with get()

person = {"name": "Emeka", "age": 30}

salary = person.get("salary")
print(salary)

Expected Output:

None

No crash! It returned None because "salary" doesn’t exist in the dictionary.

Using a Default Value with get()

You can provide a second argument — the value to return if the key is missing:

person = {"name": "Emeka", "age": 30}

salary = person.get("salary", 0)
print(salary)

Expected Output:

0

Explanation:

  • person.get("salary", 0) — look for "salary"; if not found, return 0 instead of None

Second Example

inventory = {"apples": 10, "oranges": 5}

# Key exists:
print(inventory.get("apples", 0))    # Output: 10

# Key doesn't exist:
print(inventory.get("bananas", 0))   # Output: 0

🤔 Thinking prompt: Why is get() safer than dict[key] in a real application? What would happen in a school database if you tried to access a student that doesn’t exist?

Method 5: update() — Add or Modify Multiple Items

What Is It?

update() lets you add new key-value pairs or change existing ones — all at once — by passing in another dictionary or keyword arguments.

Why use it? When you need to update many things in a dictionary at once, instead of doing it one by one.

Simple Example — Adding New Keys

profile = {"name": "Ngozi", "age": 22}

profile.update({"city": "Abuja", "job": "Engineer"})

print(profile)

Expected Output:

{'name': 'Ngozi', 'age': 22, 'city': 'Abuja', 'job': 'Engineer'}

Explanation:

  • profile.update({...}) — pass a dictionary with new pairs to add
  • Python merges the new dictionary into the existing one

Updating Existing Keys

product = {"name": "Laptop", "price": 500, "stock": 10}

product.update({"price": 450, "stock": 8})

print(product)

Expected Output:

{'name': 'Laptop', 'price': 450, 'stock': 8}

The price and stock were updated. The name stayed the same.

Update Using Keyword Arguments

car = {"brand": "Toyota", "year": 2018}

car.update(year=2023, color="Red")

print(car)

Expected Output:

{'brand': 'Toyota', 'year': 2023, 'color': 'Red'}

Method 6: pop() — Remove a Specific Key

What Is It?

pop(key) removes the item with the given key from the dictionary AND returns its value so you can use it.

Why use it? When you need to both remove a key and use the value it had.

Simple Example

cart = {"apple": 3, "banana": 5, "mango": 2}

removed_value = cart.pop("banana")

print("Removed:", removed_value)
print("Cart after:", cart)

Expected Output:

Removed: 5
Cart after: {'apple': 3, 'mango': 2}

Explanation:

  • cart.pop("banana") — removes "banana" from the dictionary and returns 5 (the value)
  • We store that returned value in removed_value

Using a Default Value to Avoid KeyError

If the key doesn’t exist and you don’t provide a default, pop() crashes:

cart = {"apple": 3, "mango": 2}

# Safe pop with default:
result = cart.pop("banana", "Not in cart")
print(result)

Expected Output:

Not in cart

🤔 Thinking prompt: What happens if you call pop() on a key that doesn’t exist, without providing a default? Try it and see!

Method 7: popitem() — Remove the Last Item

What Is It?

popitem() removes and returns the last inserted key-value pair as a tuple.

Why use it? Useful when you want to process and remove items one at a time from the end, like a stack.

Simple Example

data = {"a": 1, "b": 2, "c": 3}

last_item = data.popitem()

print("Removed:", last_item)
print("Dictionary after:", data)

Expected Output:

Removed: ('c', 3)
Dictionary after: {'a': 1, 'b': 2}

Explanation:

  • data.popitem() removes ('c', 3) because "c" was inserted last
  • It returns the pair as a tuple

⚠️ Common Mistake: In Python versions before 3.7, popitem() removed a random item. In Python 3.7+, it always removes the LAST inserted item. Always check your Python version.

Method 8: clear() — Empty the Dictionary

What Is It?

clear() removes ALL items from the dictionary, leaving it completely empty.

Why use it? When you want to reset a dictionary and start fresh without deleting the variable itself.

Simple Example

user_data = {"name": "Kola", "score": 95, "level": 3}

print("Before:", user_data)

user_data.clear()

print("After:", user_data)

Expected Output:

Before: {'name': 'Kola', 'score': 95, 'level': 3}
After: {}

The {} means the dictionary is now empty.

⚠️ Common Mistake: Don’t confuse clear() with reassigning: user_data = {} also empties it, but clear() is the “correct” method because it modifies the existing dictionary in place. If another variable points to the same dictionary, clear() affects both; reassignment only affects the one variable.

Method 9: copy() — Make a Duplicate

What Is It?

copy() creates a shallow copy of the dictionary — a new independent dictionary with the same keys and values.

Why use it? To work with a duplicate so you don’t accidentally change the original.

The Problem Without copy()

original = {"name": "Ada", "score": 80}

# This does NOT create a new dict — it just creates another name for the same dict:
alias = original

alias["score"] = 99   # This also changes original!

print("Original:", original)
print("Alias:", alias)

Expected Output:

Original: {'name': 'Ada', 'score': 99}
Alias: {'name': 'Ada', 'score': 99}

Both changed! That’s because alias and original point to the same dictionary in memory.

The Safe Way with copy()

original = {"name": "Ada", "score": 80}

backup = original.copy()   # A truly separate copy

backup["score"] = 99       # Only changes backup

print("Original:", original)
print("Backup:", backup)

Expected Output:

Original: {'name': 'Ada', 'score': 80}
Backup: {'name': 'Ada', 'score': 99}

Now the original is safe!

Method 10: fromkeys() — Create a New Dictionary from Keys

What Is It?

fromkeys(keys, value) creates a brand new dictionary using a list of keys, all set to the same value.

Why use it? When you want to initialize a dictionary quickly with many keys all set to the same starting value — like all scores starting at 0.

Simple Example

subjects = ["maths", "english", "science"]

scores = dict.fromkeys(subjects, 0)

print(scores)

Expected Output:

{'maths': 0, 'english': 0, 'science': 0}

Explanation:

  • dict.fromkeys(subjects, 0) — creates a new dict using subjects as keys, all set to 0
  • Notice: we call it on dict (the class), not on an existing dictionary

Without a Default Value

keys = ["a", "b", "c"]

new_dict = dict.fromkeys(keys)

print(new_dict)

Expected Output:

{'a': None, 'b': None, 'c': None}

When no value is specified, all keys default to None.

Method 11: setdefault() — Get Value or Insert Default

What Is It?

setdefault(key, default) is like get(), but with an extra superpower: if the key doesn’t exist, it inserts the key with the default value into the dictionary.

Why use it? When you want to ensure a key exists with a starting value, but don’t want to overwrite it if it already has a value.

Simple Example

data = {"name": "Bola"}

# Key doesn't exist — it gets inserted with default value:
result = data.setdefault("score", 0)

print("Result:", result)
print("Dictionary:", data)

Expected Output:

Result: 0
Dictionary: {'name': 'Bola', 'score': 0}

Key Already Exists — No Overwrite

data = {"name": "Bola", "score": 95}

# Key already exists — returns existing value without changing it:
result = data.setdefault("score", 0)

print("Result:", result)
print("Dictionary:", data)

Expected Output:

Result: 95
Dictionary: {'name': 'Bola', 'score': 95}

The score stayed 95 — setdefault() never overwrites an existing value.

💡 Real-world use: setdefault() is widely used when counting things. For example, counting how many times each word appears in a text.

text = ["apple", "banana", "apple", "cherry", "banana", "apple"]
counts = {}

for word in text:
    counts.setdefault(word, 0)   # Make sure the key exists with 0
    counts[word] += 1             # Increment the count

print(counts)

Expected Output:

{'apple': 3, 'banana': 2, 'cherry': 1}

Guided Practice — Dictionary Methods

Exercise 1: Student Report System

Objective: Use dictionary methods to manage a student’s data safely and efficiently.

Scenario: You are building a school database tool. You have a student’s record and need to perform several operations on it.

Setup:

student = {
    "name": "Tunde",
    "age": 16,
    "maths": 72,
    "english": 88
}

Steps:

Step 1 — Add new subjects using update():

student.update({"science": 91, "history": 65})
print(student)

Expected Output:

{'name': 'Tunde', 'age': 16, 'maths': 72, 'english': 88, 'science': 91, 'history': 65}

Step 2 — Safely get a subject that might not exist using get():

art_score = student.get("art", "Not enrolled")
print("Art:", art_score)

Expected Output:

Art: Not enrolled

Step 3 — Print all subjects and scores using items():

for subject, value in student.items():
    print(f"{subject}: {value}")

Expected Output:

name: Tunde
age: 16
maths: 72
english: 88
science: 91
history: 65

Step 4 — Calculate average score using values():

# Only average the actual scores (not name or age)
score_subjects = {"maths": 72, "english": 88, "science": 91, "history": 65}
scores_only = list(score_subjects.values())
average = sum(scores_only) / len(scores_only)
print("Average score:", average)

Expected Output:

Average score: 79.0

Step 5 — Remove a subject using pop():

removed = student.pop("history")
print("Removed history score:", removed)
print("Updated student:", student)

Expected Output:

Removed history score: 65
Updated student: {'name': 'Tunde', 'age': 16, 'maths': 72, 'english': 88, 'science': 91}

Self-check Questions:

  1. What would get() return if we searched for a key that doesn’t exist and gave no default?
  2. What is the difference between pop() and popitem()?
  3. Why is copy() important when sharing dictionaries?

PART 2: Python If / Elif / Else Conditions

Section 2 — What Are Conditions and Why Do We Need Them?

Every program needs to make decisions. Think about these real-world situations:

  • ATM machine: “If the PIN is correct, allow withdrawal. Otherwise, deny access.”
  • Weather app: “If temperature > 35°C, show ‘Hot’. If 20–35°C, show ‘Warm’. If below 20°C, show ‘Cool’.”
  • Video game: “If health = 0, display Game Over.”
  • School system: “If score >= 70, display ‘Pass’. Otherwise, display ‘Fail’.”

In Python, we express decisions using three keywords: if, elif, and else.

Section 3 — Python Comparison Operators (Refresher + More)

These operators evaluate to True or False and are the building blocks of all conditions:

a = 10
b = 20

print(a == b)   # Equal? → False
print(a != b)   # Not equal? → True
print(a < b)    # Less than? → True
print(a > b)    # Greater than? → False
print(a <= 10)  # Less than or equal? → True
print(b >= 20)  # Greater than or equal? → True

Expected Output:

False
True
True
False
True
True

Section 4 — The if Statement

What Is It?

The if statement checks a condition. If the condition is True, Python runs the code block inside the if. If the condition is False, Python skips that block.

The Structure

if condition:
    code to run when condition is True

⚠️ Critical Rule — Indentation: The code inside the if block MUST be indented (moved right) with spaces or a tab. Python uses indentation to know what belongs inside the if. Other languages use {} brackets, but Python uses indentation.

Very Simple Example

temperature = 38

if temperature > 35:
    print("It is very hot outside!")

Expected Output:

It is very hot outside!

Line-by-line explanation:

  • temperature = 38 — we store the value 38 in a variable called temperature
  • if temperature > 35: — Python checks: is 38 > 35? Yes! So it is True
  • The colon : at the end of the if line is required — it signals that a code block follows
  • ` print(“It is very hot outside!”) — this line is indented (4 spaces), so it is inside the if block. Since the condition was True`, this line runs

Example Where Condition is False

temperature = 20

if temperature > 35:
    print("It is very hot outside!")

print("Program continues...")

Expected Output:

Program continues...

Since 20 > 35 is False, the print inside the if block is skipped. Execution jumps to the next unindented line.

Multiple Statements Inside an if Block

All statements inside the block must be at the same indentation level:

age = 20

if age >= 18:
    print("You are an adult.")
    print("You can vote.")
    print("You can drive.")

Expected Output:

You are an adult.
You can vote.
You can drive.

All three print statements are at the same indentation level, so they are all inside the if block. All three run because the condition is True.

Common Beginner Mistake — Missing Colon

# WRONG - Missing colon after condition:
if age >= 18
    print("Adult")
# SyntaxError: invalid syntax

# CORRECT:
if age >= 18:
    print("Adult")

Common Beginner Mistake — Wrong Indentation

# WRONG - print is not indented:
if age >= 18:
print("Adult")   # IndentationError

# CORRECT - print is indented:
if age >= 18:
    print("Adult")

Using Boolean Variables in if

You can use a variable that is already True or False directly in an if statement:

is_logged_in = True

if is_logged_in:
    print("Welcome back!")

Expected Output:

Welcome back!

Truthy and Falsy Values

Python treats some values as “truthy” (behaves like True) and others as “falsy” (behaves like False):

Falsy (acts like False) Truthy (acts like True)
0 (zero) Any non-zero number (5, -3)
"" (empty string) Any non-empty string
[] (empty list) Any non-empty list
{} (empty dict) Any non-empty dict
None Everything else 
name = ""

if name:
    print("Name exists:", name)

# Since name is an empty string (falsy), nothing is printed
print("Done")

Expected Output:

Done

name = "Chidi"

if name:
    print("Name exists:", name)

Expected Output:

Name exists: Chidi

Section 5 — The else Statement

What Is It?

else is added after an if block. It runs when the if condition is False. Think of it as “otherwise, do this instead.”

The Structure

if condition:
    code runs when condition is True
else:
    code runs when condition is False

Simple Example

score = 55

if score >= 70:
    print("You passed!")
else:
    print("You did not pass. Try again!")

Expected Output:

You did not pass. Try again!

Explanation:

  • score >= 70 → 55 >= 70 → False
  • The if block is skipped
  • Python runs the else block instead

Another Example

age = 15

if age >= 18:
    print("You can vote.")
else:
    print("You are too young to vote.")

Expected Output:

You are too young to vote.

💡 else never has a condition of its own — it is simply the “everything else” case. It catches whatever the if didn’t catch.

Common Beginner Mistake — else with a condition

# WRONG - else cannot have a condition:
if score >= 70:
    print("Pass")
else score < 70:     # SyntaxError!
    print("Fail")

# CORRECT:
if score >= 70:
    print("Pass")
else:
    print("Fail")

Section 6 — The elif Statement (Else If)

What Is It?

elif stands for “else if.” It lets you check multiple conditions in sequence. Python checks each condition from top to bottom and runs the first block whose condition is True. Once a match is found, the rest are skipped.

The Structure

if condition_1:
    code for condition_1
elif condition_2:
    code for condition_2
elif condition_3:
    code for condition_3
else:
    code when nothing matched

Why Do We Need elif?

Without elif, you would need multiple separate if statements, and ALL of them would be checked even after a match is found. elif stops checking once a match is found — this is both more efficient and produces correct results.

Simple Example — Grade Calculator

score = 82

if score >= 90:
    print("Grade: A")
elif score >= 80:
    print("Grade: B")
elif score >= 70:
    print("Grade: C")
elif score >= 60:
    print("Grade: D")
else:
    print("Grade: F")

Expected Output:

Grade: B

Step-by-step trace:

  1. score >= 90 → 82 >= 90 → False → skip
  2. score >= 80 → 82 >= 80 → True ✅ → print "Grade: B" → stop checking

Another Example — Time of Day Greeting

hour = 14   # 2:00 PM in 24-hour format

if hour < 12:
    print("Good morning!")
elif hour < 17:
    print("Good afternoon!")
elif hour < 21:
    print("Good evening!")
else:
    print("Good night!")

Expected Output:

Good afternoon!

Trace:

  1. hour < 12 → 14 < 12 → False → skip
  2. hour < 17 → 14 < 17 → True ✅ → print "Good afternoon!" → stop

Example — Traffic Light System

light = "red"

if light == "green":
    print("Go!")
elif light == "yellow":
    print("Slow down!")
elif light == "red":
    print("Stop!")
else:
    print("Unknown light color")

Expected Output:

Stop!

🤔 Thinking prompt: What if you changed light = "red" to light = "purple"? What would print?

Section 7 — Combining Conditions: and, or, not

Sometimes a single comparison isn’t enough. You can combine conditions using logical operators:

Operator Meaning Example
and Both conditions must be True age >= 18 and age <= 65
or At least one condition must be True day == "Sat" or day == "Sun"
not Reverses True to False and vice versa not is_banned

Using and

age = 25
has_id = True

if age >= 18 and has_id:
    print("Entry allowed.")
else:
    print("Entry denied.")

Expected Output:

Entry allowed.

Both conditions must be True. age >= 18 → True, has_id → True → overall True.

Using or

day = "Saturday"

if day == "Saturday" or day == "Sunday":
    print("It's the weekend!")
else:
    print("It's a weekday.")

Expected Output:

It's the weekend!

Only one condition needs to be True. day == "Saturday" → True → done!

Using not

is_banned = False

if not is_banned:
    print("User is allowed.")
else:
    print("User is banned.")

Expected Output:

User is allowed.

not is_banned → not False → True → run the if block.

Section 8 — if Statements with Dictionaries

This is where everything comes together! You can use if statements with dictionaries to make smart, data-driven decisions.

Example 1 — Check if a Key Exists

student = {"name": "Amaka", "score": 88}

if "score" in student:
    print("Score found:", student["score"])
else:
    print("No score recorded.")

Expected Output:

Score found: 88

Example 2 — Grade Based on Dictionary Score

student = {"name": "Emeka", "score": 74}

score = student["score"]

if score >= 90:
    grade = "A"
elif score >= 80:
    grade = "B"
elif score >= 70:
    grade = "C"
elif score >= 60:
    grade = "D"
else:
    grade = "F"

print(f"{student['name']} scored {score} → Grade: {grade}")

Expected Output:

Emeka scored 74 → Grade: C

Example 3 — Check Multiple Students

students = {
    "Ada": 92,
    "Bisi": 58,
    "Chike": 75,
    "Dayo": 45
}

for name, score in students.items():
    if score >= 70:
        status = "PASS"
    else:
        status = "FAIL"
    print(f"{name}: {score} → {status}")

Expected Output:

Ada: 92 → PASS
Bisi: 58 → FAIL
Chike: 75 → PASS
Dayo: 45 → FAIL

Section 9 — Nested if Statements

An if statement inside another if statement is called a nested if. Use this when a second decision only matters if the first condition is already True.

Example — Age and Membership Check

age = 25
is_member = True

if age >= 18:
    print("Age check passed.")
    if is_member:
        print("Member discount applied!")
    else:
        print("No member discount.")
else:
    print("Must be 18 or older.")

Expected Output:

Age check passed.
Member discount applied!

Explanation:

  • First, Python checks if age >= 18 → True → enter outer if
  • Inside the outer if, it checks is_member → True → print discount message

⚠️ Warning: Deeply nested if statements (3+ levels deep) make code hard to read. Try to keep nesting to a maximum of 2 levels when possible.

Section 10 — The pass Statement

Sometimes you want to write an if block but not fill in the code yet (maybe as a placeholder). But Python doesn’t allow an empty block. Use pass to create an empty placeholder:

score = 85

if score >= 70:
    pass   # TODO: Add passing logic later

print("End of check")

Expected Output:

End of check

pass does nothing — it simply tells Python “this block is intentionally empty for now.”

Guided Practice — If / Elif / Else

Exercise 1: Temperature Classifier

Objective: Use elif to classify a temperature reading.

Scenario: You are building a weather monitoring app. Write code that classifies temperature into categories.

Steps:

temperature = 28   # Try changing this value

if temperature >= 40:
    print("Extreme heat! Stay indoors.")
elif temperature >= 30:
    print("Very hot. Stay hydrated.")
elif temperature >= 20:
    print("Warm and comfortable.")
elif temperature >= 10:
    print("Cool. Bring a jacket.")
else:
    print("Cold. Dress warmly!")

Expected Output (temperature = 28):

Warm and comfortable.

What-if challenges:

  • Change temperature = 28 to 42. What prints?
  • Change it to 5. What prints?
  • What is the minimum temperature that would trigger “Very hot”?

Exercise 2: Login System with Dictionary

Objective: Use a dictionary to store user credentials and if/else to validate login.

users = {
    "admin": "password123",
    "ngozi": "securepass",
    "emeka": "mypass456"
}

# Simulated login attempt:
username = "ngozi"
password = "securepass"

if username in users:
    if users[username] == password:
        print(f"Welcome, {username}! Login successful.")
    else:
        print("Incorrect password.")
else:
    print("Username not found.")

Expected Output:

Welcome, ngozi! Login successful.

Self-check Questions:

  1. What prints if password = "wrongpass"?
  2. What prints if username = "unknown"?
  3. Why do we check username in users first, before checking the password?

Mini Project: Student Report Card Generator

Project Overview

You will build a Student Report Card Generator that:

  1. Stores multiple students and their subject scores in a dictionary
  2. Calculates the average score for each student
  3. Assigns a grade using if/elif/else
  4. Prints a formatted report card for each student

This project combines ALL the skills from this lesson: dictionary methods, loops, and conditions.

Stage 1 — Setup: Create the Student Data

# Stage 1: Student database
students = {
    "Amara": {"maths": 85, "english": 78, "science": 92},
    "Bola":  {"maths": 60, "english": 55, "science": 58},
    "Chike": {"maths": 95, "english": 88, "science": 91},
    "Dayo":  {"maths": 40, "english": 45, "science": 50},
}

print("Student database loaded successfully.")
print("Number of students:", len(students))

Expected Output:

Student database loaded successfully.
Number of students: 4

Stage 2 — Grade Assignment Function Logic

Before building the full project, let’s write the grade logic separately:

def get_grade(average):
    if average >= 90:
        return "A"
    elif average >= 80:
        return "B"
    elif average >= 70:
        return "C"
    elif average >= 60:
        return "D"
    else:
        return "F"

# Quick test:
print(get_grade(92))   # Expected: A
print(get_grade(75))   # Expected: C
print(get_grade(45))   # Expected: F

Expected Output:

A
C
F

Stage 3 — Build the Full Report Card

students = {
    "Amara": {"maths": 85, "english": 78, "science": 92},
    "Bola":  {"maths": 60, "english": 55, "science": 58},
    "Chike": {"maths": 95, "english": 88, "science": 91},
    "Dayo":  {"maths": 40, "english": 45, "science": 50},
}

def get_grade(average):
    if average >= 90:
        return "A"
    elif average >= 80:
        return "B"
    elif average >= 70:
        return "C"
    elif average >= 60:
        return "D"
    else:
        return "F"

# Print report card for each student
print("=" * 40)
print("       STUDENT REPORT CARDS")
print("=" * 40)

for student_name, subjects in students.items():
    # Calculate average using values()
    scores = list(subjects.values())
    average = sum(scores) / len(scores)
    grade = get_grade(average)

    # Determine pass/fail
    if grade in ["A", "B", "C"]:
        status = "PASS"
    else:
        status = "FAIL"

    # Print the report for this student
    print(f"\nStudent: {student_name}")
    print("-" * 30)

    for subject, score in subjects.items():
        print(f"  {subject.capitalize():<12}: {score}")

    print(f"  {'Average':<12}: {average:.1f}")
    print(f"  {'Grade':<12}: {grade}")
    print(f"  {'Status':<12}: {status}")

print("\n" + "=" * 40)
print("End of Report")

Expected Output:

========================================
       STUDENT REPORT CARDS
========================================

Student: Amara
------------------------------
  Maths       : 85
  English      : 78
  Science      : 92
  Average      : 85.0
  Grade        : B
  Status       : PASS

Student: Bola
------------------------------
  Maths       : 60
  English      : 55
  Science      : 58
  Average      : 57.7
  Grade        : F
  Status       : FAIL

Student: Chike
------------------------------
  Maths       : 95
  English      : 88
  Science      : 91
  Average      : 91.3
  Grade        : A
  Status       : PASS

Student: Dayo
------------------------------
  Maths       : 40
  English      : 45
  Science      : 50
  Average      : 45.0
  Grade        : F
  Status       : FAIL

========================================
End of Report

Stage 4 — Enhancement: Find Top Student

# Add this to the end of the Stage 3 code:

best_student = None
best_average = 0

for student_name, subjects in students.items():
    scores = list(subjects.values())
    average = sum(scores) / len(scores)

    if average > best_average:
        best_average = average
        best_student = student_name

print(f"\n🏆 Top Student: {best_student} with an average of {best_average:.1f}")

Expected Output:

🏆 Top Student: Chike with an average of 91.3

Reflection Questions for the Mini Project

  1. What dictionary method did you use to loop through each student’s subjects and scores?
  2. Why was values() useful when calculating the average?
  3. In the grade function, why does the order of elif conditions matter?
  4. What would happen if you put elif average >= 60 before elif average >= 90?
  5. How could you modify the project to also show which subject each student scored highest in?

Common Beginner Mistakes — Full Summary

Dictionary Method Mistakes

Mistake 1 — Accessing a missing key directly:

data = {"name": "Ada"}

# WRONG - crashes with KeyError:
print(data["score"])

# CORRECT - use get():
print(data.get("score", "No score"))

Mistake 2 — Forgetting copy() before editing:

original = {"x": 10}
copy1 = original        # NOT a copy! Both point to same dict
copy2 = original.copy() # TRUE copy

copy1["x"] = 99         # This also changes original!
copy2["x"] = 50         # This only changes copy2

print(original)   # {'x': 99}  ← original was modified!

Mistake 3 — pop() on a missing key without a default:

data = {"a": 1}

# WRONG - crashes:
data.pop("b")

# CORRECT - use default:
data.pop("b", None)

Mistake 4 — Confusing pop() and popitem():

  • pop("key") — removes a specific key you name
  • popitem() — removes the last inserted key (you don’t get to choose which)

If/Elif/Else Mistakes

Mistake 1 — Missing colon:

# WRONG:
if score > 90
    print("A")

# CORRECT:
if score > 90:
    print("A")

Mistake 2 — Wrong indentation:

# WRONG:
if score > 90:
print("A")    # IndentationError

# CORRECT:
if score > 90:
    print("A")

Mistake 3 — Using = instead of == in a condition:

# WRONG (this assigns, not compares):
if score = 90:
    print("A")

# CORRECT (double == for comparison):
if score == 90:
    print("A")

Mistake 4 — Wrong order in elif chains:

# WRONG - Grade A will never be reached because >= 60 catches everything first:
if score >= 60:
    grade = "D"
elif score >= 90:   # Never reached!
    grade = "A"

# CORRECT - Put the most specific (largest) condition first:
if score >= 90:
    grade = "A"
elif score >= 60:
    grade = "D"

Mistake 5 — Using else when you need elif:

score = 75

# WRONG - 'else' doesn't check a condition:
if score >= 90:
    print("A")
else score >= 80:   # SyntaxError!
    print("B")

# CORRECT:
if score >= 90:
    print("A")
elif score >= 80:
    print("B")

Lesson Reflection Questions

  1. What is the difference between get() and accessing a key with dict[key]?
  2. When would you use setdefault() instead of get()?
  3. What does items() return, and why is it useful in a loop?
  4. What does the colon : at the end of an if line tell Python?
  5. What is the role of indentation in if statements?
  6. Can you have an elif without a preceding if? Why or why not?
  7. What is the difference between and and or in conditions?
  8. What would happen if you have two if statements checking the same variable instead of if/elif? Give an example.
  9. Why is the order of elif conditions important when checking number ranges?
  10. How would you combine items() and if/elif/else to filter a dictionary and print only students who passed?

Lesson Completion Checklist

Use this checklist to confirm you have mastered this lesson:

  • I can name all 11 Python dictionary methods and describe what each one does
  • I can use keys(), values(), and items() in loops
  • I understand the difference between get() and direct key access dict[key]
  • I can use update() to add and modify multiple items at once
  • I can use pop() and popitem() to remove items safely
  • I can use copy() to create an independent duplicate of a dictionary
  • I can use fromkeys() to create a new dictionary from a list of keys
  • I understand setdefault() and when it inserts vs. retrieves
  • I can write a correct if statement with proper colon and indentation
  • I can write if/else for two-path decisions
  • I can write if/elif/elif/else for multi-path decisions
  • I can combine conditions using and, or, and not
  • I can use if inside dictionary loops to filter or classify data
  • I completed the Student Report Card mini project
  • I understand and can fix all common mistakes listed

Lesson Summary

This lesson covered two major topics that work beautifully together in Python:

Dictionary Methods give you a complete toolkit for managing your data:

  • keys(), values(), items() — for viewing and looping through dictionary contents
  • get() — the safe way to read values without crashing
  • update() — for adding or changing multiple items at once
  • pop() / popitem() — for removing items
  • clear() — for emptying a dictionary
  • copy() — for making true duplicates
  • fromkeys() — for creating dictionaries from key lists
  • setdefault() — for reading with an automatic insert-if-missing feature

If / Elif / Else Conditions give Python the ability to make decisions:

  • if checks a condition; if True, runs the block
  • else runs when the if condition is False
  • elif lets you check multiple conditions in sequence
  • and, or, not combine conditions for more complex logic
  • Proper indentation is mandatory — it defines what belongs inside each block
  • Order matters in elif chains — put the most specific condition first

Combined, these two concepts let you build programs that store structured data AND respond intelligently to it — which is the foundation of virtually every real-world application: school systems, banking software, e-commerce platforms, weather apps, and much more.

End of Lesson 12