Learn Code Quiz: Data Science | Lists, Dictionaries, and Tuples | Learn Python in a Week

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Are you ready to test your coding skills and deepen your knowledge of data science concepts and Python ? Join our exciting Learn Code Quiz series, where we explore the fascinating world of Data Science while mastering Lists, Dictionaries, and Tuples in Python—all of Python in just one week!

Title: Differences between Lists, Dictionaries, and Tuples
Lists: Lists are ordered, mutable (can be changed), and can contain duplicate elements. Elements in a list are enclosed in square brackets [ ] and separated by commas.

Example of a list
fruits_list = ['apple', 'banana', 'orange', 'kiwi']
Accessing an element in a list:
print("Accessing an element in a list:")
print(fruits_list[1])

Output: Accessing an element in a list:
Output: banana

Deleting an element from a list:
print("\nDeleting an element from a list:")
del fruits_list[2] # Removes 'orange' from the list
print(fruits_list) # Output: ['apple', 'banana', 'kiwi']

Output: Deleting an element from a list:
Output: ['apple', 'banana', 'kiwi']

Adding an element to a list:
print("\nAdding an element to a list:")
print(fruits_list) # Output: ['apple', 'banana', 'kiwi', 'grapes']

Output: Adding an element to a list:
Output: ['apple', 'banana', 'kiwi', 'grapes']

Dictionaries:
Dictionaries are unordered, mutable (can be changed), and consist of key-value pairs. Each key-value pair is enclosed in curly braces { } and separated by commas. Dictionaries are accessed using keys instead of indices.

Example of a Dictionary:
person_info = {'name': 'John', 'age': 30, 'occupation': 'engineer'}
Accessing an element in a dictionary:
print("\nAccessing an element in a dictionary:")
print(person_info['name']) # Output: 'John'

Output: Accessing an element in a dictionary:
Output: John

Deleting an element from a dictionary:
print("\nDeleting an element from a dictionary:")
del person_info['age'] # Removes 'age' key and its value from the dictionary
print(person_info) # Output: {'name': 'John', 'occupation': 'engineer'}

Output: Deleting an element from a dictionary:
{'name': 'John', 'occupation': 'engineer'}

Adding an element to a dictionary:
print("\nAdding an element to a dictionary:")
person_info['location'] = 'New York' # Add a new key-value pair
print(person_info) # Output: {'name': 'John', 'occupation': 'engineer', 'location': 'New York'}

Tuples:
Tuples are ordered, immutable (cannot be changed after creation), and can contain duplicate elements. Elements in a tuple are enclosed in parentheses ( ) and separated by commas.

Example of a Tuple:
coordinates_tuple = (10, 20)
Accessing an element in a tuple:
print("\nAccessing an element in a tuple:")
print(coordinates_tuple[0]) # Output: 10

Output: Accessing an element in a tuple:
Output: 10

Tuples are immutable, so there is no direct way to delete an element from a tuple.
To "delete" an element, you need to create a new tuple without the element you want to remove.

Adding an element to a tuple (not directly possible due to immutability):

print("\nAdding an element to a tuple:")

Output: Adding an element to a tuple:

To add an element, you need to create a new tuple with the additional element

new_coordinates_tuple = coordinates_tuple + (30,)
print(new_coordinates_tuple) # Output: (10, 20, 30)

Output: (10, 20, 30)
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🔥 What's in store for you:

📚 Data Science Essentials: Get a solid foundation in key Data Science principles and techniques.

📋 Lists, Dictionaries, and Tuples: Discover the power of Python's essential data structures for efficient data handling.

🎯 Code Quiz Challenges: Test yourself with fun and interactive coding challenges throughout the course.

💻 Hands-on Practice: Apply your skills in real-world projects and exercises to reinforce your learning.

🏆 Weekly Progress: Watch your Python skills grow as you learn and practice each day.

📅 One Week, One Goal: Embrace the challenge of mastering Python in just one week!

👉 Whether you're a beginner or an experienced programmer, this Learn Code Quiz series is designed to level up your Python proficiency and Data Science prowess. Let's dive into the world of Data Science and embark on an exciting Python journey together!

🎓 Prerequisites: Basic understanding of Python syntax is recommended, but not required. Passion for learning and eagerness to dive into the world of Data Science is a must!

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