Author: 슈퍼토미

Week 3: Data Structures (Continued)

• Day 5: List Comprehensions
• Introduction to List Comprehensions:
  • Explain list comprehensions as a concise way to create lists in Python.
  • Emphasize their readability and efficiency.
• Basic Syntax:
  • Show the basic syntax of a list comprehension:
  new_list = [expression for item in iterable]
• Examples:
  • Provide examples of list comprehensions for creating lists:
  squares = [x**2 for x in range(1, 6)] # [1, 4, 9, 16, 25] even_numbers = [x for x in range(1, 11) if x % 2 == 0] # [2, 4, 6, 8, 10]
• Nested List Comprehensions:
  • Explain how to use nested list comprehensions for more complex data transformations.
  matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] flattened = [num for row in matrix for num in row] # [1, 2, 3, 4, 5, 6, 7, 8, 9]
• Day 6: File Handling – Reading Files
• Introduction to File Handling:
  • Explain the importance of working with files in programming.
  • Discuss different file modes (read, write, append).
• Opening and Closing Files:
  • Show how to open and close files using the open() function:
  file = open("myfile.txt", "r") # Opens the file in read mode file.close() # Close the file when done
• Reading Text Files:
  • Demonstrate how to read the contents of a text file:
  with open("myfile.txt", "r") as file: content = file.read()
• Iterating Over Lines:
  • Explain how to iterate over lines in a text file:
  with open("myfile.txt", "r") as file: for line in file: print(line.strip()) # Strip removes newline characters
• Day 7: File Handling – Writing and Appending Files
• Writing to Text Files:
  • Show how to write data to a text file:
  with open("output.txt", "w") as file: file.write("Hello, World!\n")
• Appending to Text Files:
  • Explain how to append data to an existing text file:
  with open("output.txt", "a") as file: file.write("This is an appended line.\n")
• Error Handling in File Handling:
  • Discuss error handling when working with files, including exceptions like FileNotFoundError.
• Practice Exercises:
  • Provide exercises and challenges that involve list comprehensions and basic file handling operations.

By the end of Week 4, you’ll have a solid understanding of list comprehensions for concise list creation and basic file handling techniques for reading, writing, and appending text files. These skills are valuable for various data processing and file manipulation tasks in Python.

Week 3: Data Structures (Continued)

• Day 3: Tuples
• Introduction to Tuples:
  • Explain what tuples are and how they differ from lists.
  • Emphasize that tuples are immutable, meaning their elements cannot be changed after creation.
• Creating Tuples:
  • Show various ways to create tuples:
  my_tuple = (1, 2, 3) empty_tuple = () mixed_tuple = (1, "hello", 3.14)
• Accessing Tuple Elements:
  • Explain how to access elements in a tuple using indexing.
  my_tuple = (10, 20, 30) first_element = my_tuple[0] # Access the first element (10)
• Tuple Packing and Unpacking:
  • Introduce the concept of tuple packing and unpacking.
  coordinates = (3, 4) x, y = coordinates # Unpacks the tuple into variables x and y
• Day 4: Sets
• Introduction to Sets:
  • Explain sets as unordered collections of unique elements.
  • Emphasize the uniqueness property of sets—no duplicate elements.
• Creating Sets:
  • Show different ways to create sets:
  my_set = {1, 2, 3} empty_set = set()
• Operations on Sets:
  • Discuss common set operations:
  • Adding elements using add().
  • Removing elements using remove() and discard().
  • Union, intersection, and difference operations.
  • Checking for membership using in.
• Set Comprehensions:
  • Introduce set comprehensions for creating sets with a concise syntax.
    python squares = {x**2 for x in range(1, 6)} # Creates a set {1, 4, 9, 16, 25}

Week 4: Data Structures (Continued)

• Day 5: Dictionaries
• Introduction to Dictionaries:
  • Explain dictionaries as unordered collections of key-value pairs.
  • Emphasize the concept of keys being unique and immutable.
• Creating Dictionaries:
  • Show how to create dictionaries:
  my_dict = {"name": "Alice", "age": 30} empty_dict = {}
• Accessing Dictionary Values:
  • Explain how to access values using keys.
  my_dict = {"name": "Bob", "age": 25} name = my_dict["name"] # Access the value associated with the key "name"
• Dictionary Methods:
  • Introduce common dictionary methods:
  • keys(), values(), and items().
  • get() for safe key retrieval.
• Day 6-7: Advanced Dictionary Operations and Use Cases
• Dictionary Comprehensions:
  • Teach dictionary comprehensions for creating dictionaries with a concise syntax.
  squares_dict = {x: x**2 for x in range(1, 6)}
• Iterating Over Dictionaries:
  • Explain how to loop through dictionaries and work with keys and values.
  my_dict = {"name": "Charlie", "age": 35} for key, value in my_dict.items(): print(key, value)
• Nested Dictionaries:
  • Discuss the concept of nested dictionaries and their use cases.
  person = { "name": "David", "address": { "street": "123 Main St", "city": "Somewhere", }, }
• Practice Exercises:
  • Provide exercises and challenges related to tuples, sets, and dictionaries to reinforce learning.

By the end of Week 4, you’ll have a solid understanding of important Python data structures, including tuples, sets, and dictionaries, and how to work with them effectively. These data structures are essential for various programming tasks and are used extensively in Python applications.