Python Training , study and exam guide
1 Introduction to Python
1.1 What is Python?
1.2 History of Python
1.3 Features of Python
1.4 Python Applications
1.5 Setting up the Python Environment
1.6 Running Your First Python Program
2 Python Basics
2.1 Python Syntax and Indentation
2.2 Variables and Data Types
2.2 1 Numbers
2.2 2 Strings
2.2 3 Lists
2.2 4 Tuples
2.2 5 Sets
2.2 6 Dictionaries
2.3 Operators
2.3 1 Arithmetic Operators
2.3 2 Comparison Operators
2.3 3 Logical Operators
2.3 4 Assignment Operators
2.3 5 Membership Operators
2.3 6 Identity Operators
2.4 Input and Output
2.4 1 Input Function
2.4 2 Output Function
2.5 Comments
2.5 1 Single-line Comments
2.5 2 Multi-line Comments
3 Control Flow
3.1 Conditional Statements
3.1 1 If Statement
3.1 2 If-Else Statement
3.1 3 Elif Statement
3.1 4 Nested If Statements
3.2 Loops
3.2 1 For Loop
3.2 2 While Loop
3.2 3 Nested Loops
3.3 Loop Control Statements
3.3 1 Break Statement
3.3 2 Continue Statement
3.3 3 Pass Statement
4 Functions
4.1 Defining Functions
4.2 Function Arguments
4.2 1 Positional Arguments
4.2 2 Keyword Arguments
4.2 3 Default Arguments
4.2 4 Variable-length Arguments
4.3 Return Statement
4.4 Lambda Functions
4.5 Scope of Variables
4.5 1 Local Variables
4.5 2 Global Variables
4.6 Recursion
5 Data Structures
5.1 Lists
5.1 1 List Operations
5.1 2 List Methods
5.1 3 List Comprehensions
5.2 Tuples
5.2 1 Tuple Operations
5.2 2 Tuple Methods
5.3 Sets
5.3 1 Set Operations
5.3 2 Set Methods
5.4 Dictionaries
5.4 1 Dictionary Operations
5.4 2 Dictionary Methods
5.5 Advanced Data Structures
5.5 1 Stacks
5.5 2 Queues
5.5 3 Linked Lists
6 Modules and Packages
6.1 Importing Modules
6.2 Creating Modules
6.3 Standard Library Modules
6.3 1 Math Module
6.3 2 Random Module
6.3 3 DateTime Module
6.4 Creating Packages
6.5 Installing External Packages
7 File Handling
7.1 Opening and Closing Files
7.2 Reading from Files
7.2 1 read()
7.2 2 readline()
7.2 3 readlines()
7.3 Writing to Files
7.3 1 write()
7.3 2 writelines()
7.4 File Modes
7.5 Working with CSV Files
7.6 Working with JSON Files
8 Exception Handling
8.1 Try and Except Blocks
8.2 Handling Multiple Exceptions
8.3 Finally Block
8.4 Raising Exceptions
8.5 Custom Exceptions
9 Object-Oriented Programming (OOP)
9.1 Classes and Objects
9.2 Attributes and Methods
9.3 Constructors and Destructors
9.4 Inheritance
9.4 1 Single Inheritance
9.4 2 Multiple Inheritance
9.4 3 Multilevel Inheritance
9.5 Polymorphism
9.6 Encapsulation
9.7 Abstraction
10 Working with Libraries
10.1 NumPy
10.1 1 Introduction to NumPy
10.1 2 Creating NumPy Arrays
10.1 3 Array Operations
10.2 Pandas
10.2 1 Introduction to Pandas
10.2 2 DataFrames and Series
10.2 3 Data Manipulation
10.3 Matplotlib
10.3 1 Introduction to Matplotlib
10.3 2 Plotting Graphs
10.3 3 Customizing Plots
10.4 Scikit-learn
10.4 1 Introduction to Scikit-learn
10.4 2 Machine Learning Basics
10.4 3 Model Training and Evaluation
11 Web Development with Python
11.1 Introduction to Web Development
11.2 Flask Framework
11.2 1 Setting Up Flask
11.2 2 Routing
11.2 3 Templates
11.2 4 Forms and Validation
11.3 Django Framework
11.3 1 Setting Up Django
11.3 2 Models and Databases
11.3 3 Views and Templates
11.3 4 Forms and Authentication
12 Final Exam Preparation
12.1 Review of Key Concepts
12.2 Practice Questions
12.3 Mock Exams
12.4 Exam Tips and Strategies
5 4 2 Dictionary Methods Explained

5 4 2 Dictionary Methods Explained

Key Concepts

Dictionary methods in Python allow you to manipulate dictionaries, which are collections of key-value pairs. The key concepts include:

1. Adding and Updating Elements

You can add new key-value pairs to a dictionary using assignment. If the key already exists, its value will be updated.

Example:

student = {"name": "Alice", "age": 25}
student["major"] = "Computer Science"
print(student)  # Output: {'name': 'Alice', 'age': 25, 'major': 'Computer Science'}

student["age"] = 26
print(student)  # Output: {'name': 'Alice', 'age': 26, 'major': 'Computer Science'}
    

2. Removing Elements

Elements can be removed from a dictionary using the pop() method, which removes the item with the specified key, or the clear() method, which removes all items.

Example:

student = {"name": "Alice", "age": 25, "major": "Computer Science"}
age = student.pop("age")
print(age)  # Output: 25
print(student)  # Output: {'name': 'Alice', 'major': 'Computer Science'}

student.clear()
print(student)  # Output: {}
    

3. Accessing Elements

You can access the value associated with a specific key using square brackets [] or the get() method. The get() method allows you to provide a default value if the key does not exist.

Example:

student = {"name": "Alice", "age": 25, "major": "Computer Science"}
name = student["name"]
print(name)  # Output: Alice

age = student.get("age", "Unknown")
print(age)  # Output: 25

gpa = student.get("gpa", "Unknown")
print(gpa)  # Output: Unknown
    

4. Dictionary Methods

Python provides several built-in methods to manipulate dictionaries. Some common methods include keys(), values(), items(), and update().

Example:

student = {"name": "Alice", "age": 25, "major": "Computer Science"}

keys = student.keys()
print(keys)  # Output: dict_keys(['name', 'age', 'major'])

values = student.values()
print(values)  # Output: dict_values(['Alice', 25, 'Computer Science'])

items = student.items()
print(items)  # Output: dict_items([('name', 'Alice'), ('age', 25), ('major', 'Computer Science')])

student.update({"gpa": 3.8})
print(student)  # Output: {'name': 'Alice', 'age': 25, 'major': 'Computer Science', 'gpa': 3.8}
    

Putting It All Together

By understanding and using dictionary methods effectively, you can efficiently manage and manipulate key-value pairs in Python.

Example:

student = {"name": "Alice", "age": 25}
student["major"] = "Computer Science"
student["age"] = 26

age = student.pop("age")
print(age)  # Output: 26

name = student["name"]
print(name)  # Output: Alice

gpa = student.get("gpa", "Unknown")
print(gpa)  # Output: Unknown

student.update({"gpa": 3.8})
print(student)  # Output: {'name': 'Alice', 'major': 'Computer Science', 'gpa': 3.8}