Learn With Frahim

Day 6: Python Data Structures – Lists, Tuples, Sets, Dictionaries

Step 1: Python Lists

Lists are ordered, mutable collections.

# Creating a list

fruits = ["Apple", "Banana", "Cherry"]  # list of strings

print(fruits[0])  # Access first element

fruits.append("Orange")  # Add element at end

print(fruits)

fruits.remove("Banana")  # Remove element

print(fruits)

print(len(fruits))  # Length of list

Explanation: Lists can be modified (mutable). Indexing starts from 0. Use append() to add, remove() to delete.

Removing Duplicates from Lists

Example list with duplicates:

numbers = [1, 2, 3, 2, 4, 1, 5]
    

Method 1: Using set()

unique_numbers = list(set(numbers))  # removes duplicates

print(unique_numbers)

Method 2: Using loop (preserves order)

unique_numbers = []

for num in numbers:

  if num not in unique_numbers:

    unique_numbers.append(num)

print(unique_numbers)

Method 3: Using dict.fromkeys() (Python ≥3.7, preserves order)

unique_numbers = list(dict.fromkeys(numbers))

print(unique_numbers)

Step 2: Python Tuples

Tuples are ordered, immutable collections.

colors = ("Red", "Green", "Blue")

print(colors[1])  # Access second element

# colors.append("Yellow")  # ❌ This will raise an error

print(len(colors))

Explanation: Tuples cannot be changed after creation. Use tuples when data should not be modified.

Step 3: Python Sets

Sets are unordered collections of unique elements.

numbers_set = {1, 2, 3, 4}

numbers_set.add(5)  # Add element

numbers_set.add(3)  # Duplicate ignored

print(numbers_set)

numbers_set.remove(2)

print(numbers_set)

Explanation: Sets are useful for removing duplicates or performing union/intersection operations.

Step 4: Python Dictionaries

Dictionaries store key-value pairs.

student = {"name": "Alisha", "age": 30, "grade": "A"}

print(student["name"])  # Access value by key

student["age"] = 31  # Update value

student["city"] = "Dallas"  # Add new key-value

print(student.keys())

print(student.values())

Explanation: Dictionaries are mutable. Keys must be unique. Values can be any data type.

Full-fledged Example: Counting Occurrences

Use a dictionary to count the frequency of items in a list:

items = ["apple", "banana", "apple", "orange", "banana", "apple"]

count_dict = {}

for item in items:

  if item in count_dict:

    count_dict[item] += 1  # increment count

  else:

    count_dict[item] = 1  # initialize count

print(count_dict)

Output: {'apple': 3, 'banana': 2, 'orange': 1}

Explanation: Dictionaries are perfect for counting, mapping, or storing relationships between data.

Step 5: PyCharm Project Layout

        DataStructuresProject

        ├── lists_demo.py

        ├── tuples_demo.py

        ├── sets_demo.py

        └── dicts_demo.py

# Example: lists_demo.py
fruits = ["Apple", "Banana", "Cherry", "Banana"]

# Remove duplicates using dict

unique_fruits = list(dict.fromkeys(fruits))

print(unique_fruits)

Step 6: Tips & Best Practices

Use lists when order matters and data is mutable.
Use tuples for fixed collections that shouldn’t change.
Use sets to remove duplicates and perform set operations.
Use dictionaries for counting, mapping keys to values efficiently.
Combine data structures if needed, e.g., list of dictionaries.
Use meaningful variable names to improve readability.

✔ End of Day 6 – You now understand Lists, Tuples, Sets, Dictionaries, removing duplicates, and can use them in projects efficiently!

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