Python Mastery: Data Structures in Python Day-3

  1. Introduction to Data Structures in Python
  2. Lists in Python
    • Definition and Characteristics
    • Creating Lists
    • Accessing Elements
    • Modifying Lists
    • List Methods
  3. Tuples in Python
    • Definition and Characteristics
    • Creating Tuples
    • Accessing Elements
    • Immutable Nature
    • Tuple Methods
  4. Dictionaries in Python
    • Definition and Characteristics
    • Creating Dictionaries
    • Accessing and Modifying Elements
    • Dictionary Methods
  5. Sets in Python
    • Definition and Characteristics
    • Creating Sets
    • Accessing and Modifying Elements
    • Set Operations
    • Set Methods
  6. Conclusion
  1. Introduction to Data Structures in Python:
    Data structures are essential components of any programming language, including Python. They enable programmers to organize, store, and manipulate data efficiently. In Python, there are several built-in data structures, each with its unique characteristics and functionalities. In this article, we will explore four fundamental data structures in Python: lists, tuples, dictionaries, and sets.
  2. Lists in Python :
    A list in Python is a collection of elements that are ordered and mutable. Lists can contain elements of different data types and allow duplicates. They are denoted by square brackets[ ].

  • Creating Lists :

#Creating a list

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

  • Accessing Elements

Elements in a list can be accessed using indexing. Python uses zero-based indexing, meaning the first element has an index of 0.

#Accessing elements of a list

print(my_list[0])          # Output: 1

  • Modifying Lists

Lists are mutable, meaning their elements can be changed after creation. #Modifying elements of a list

my_list[0] = 10

print(my_list)              # Output: [10, 2, 3, 4, 5]

  • List Methods

Python provides various built-in methods for working with lists, such as append(), insert(), remove(), pop(), sort(), and reverse().

#Using list methods

my_list.append(6)       # Adds an element to the end of the list

my_list.insert(1, 20)     # Inserts an element at a specific index

my_list.remove(3)       # Removes the first occurrence of a value

my_list.pop()               # Removes and returns the last element

my_list.sort()               # Sorts the elements in ascending order

my_list.reverse()          # Reverses the order of elements

  1. Tuples in Python

A tuple in Python is a collection of elements that are ordered and immutable. Tuples can contain elements of different data types and allow duplicates. They are denoted by parentheses ( ).

  • Creating Tuples

#Creating a tuple

my_tuple = (1, 2, 3, 4, 5)

  • Accessing Elements

Elements in a tuple can be accessed using indexing, similar to lists. #Accessing elements of a tuple

print(my_tuple[0])                   # Output: 1

  • Immutable Nature

Unlike lists, tuples are immutable, meaning their elements cannot be changed after creation.

#Attempting to modify a tuple (will result in an error)

my_tuple[0] = 10

  • Tuple Methods

Although tuples are immutable, they have fewer built-in methods compared to lists. However, they still provide methods like count() and index() for basic operations.

 #Using tuple methods

print(my_tuple.count(3)) # Returns the number of occurrences of a value

print(my_tuple.index(4)) # Returns the index of the first occurrence of a value

  1. Dictionaries in Python

A dictionary in Python is a collection of key-value pairs that are unordered, mutable, and indexed. Dictionaries are denoted by curly braces { } and consist of keys and their corresponding values.

  • Creating Dictionaries

#Creating a dictionary

my_dict = {“name”: “Jhanvi”, “age”: 30, “city”: “Jamnagar”}

  • Accessing and Modifying Elements

Elements in a dictionary are accessed and modified using keys.

#Accessing elements of a dictionary

print(my_dict[“age”])              # Output: 30

#Modifying elements of a dictionary

my_dict[“city”] = “Rajkot”

  • Dictionary Methods

Python provides various built-in methods for working with dictionaries, such as keys(), values(), items(), get(), update(), and pop().

#Using dictionary methods

print(my_dict.keys())                          # Returns a list of keys

print(my_dict.values())                       # Returns a list of values

print(my_dict.items())                         # Returns a list of key-value pairs

 my_dict.get(“name”)                          # Returns the value for a specified key

my_dict.update({“age”: 35})              # Updates the value of a key

my_dict.pop(“city”)                            # Removes and returns the value of a key

  1. Sets in Python

 A set in Python is a collection of unique elements that are unordered and mutable. Sets do not allow duplicates and are denoted by curly braces { }.

  • Creating Sets

#Creating a set

my_set = {1, 2, 3, 4, 5}

  • Accessing and Modifying Elements

Elements in a set are accessed and modified using methods like add(), remove(), and discard().

#Adding elements to a set

my_set.add(6)

#Removing elements from a set

my_set.remove(3)

  • Set Operations

Python supports various set operations, including union, intersection, difference, and symmetric difference.

#Set operations

set1 = {1, 2, 3}

set2 = {3, 4, 5}

print(set1.union(set2))                         # Returns the union of two

sets print(set1.intersection(set2))               # Returns the intersection of two sets print(set1.difference(set2))                 # Returns the difference between two sets print(set1.symmetric_difference(set2))# Returns the symmetric difference

  • Set Methods Python provides built-in methods like union(), intersection(), difference(), clear(), and symmetric_difference() for working with sets.

#Using set methods

my_set.clear() # Removes all elements from the set

  1. Conclusion In this comprehensive guide, we have explored the fundamental data structures in Python: lists, tuples, dictionaries, and sets. Understanding these data structures is crucial for proficient Python programming as they form the backbone of many algorithms and data manipulation tasks. Whether you’re a beginner learning Python or an experienced developer looking to refresh your knowledge, mastering these data structures will undoubtedly enhance your programming skills and open up new possibilities for solving complex problems.

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