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Here some Recourses to start Data Structures and Algorithm
| Videos | Links |
|---|---|
| CS50x 2023 - Lecture 5 - Data Structures | Youtube Video |
| CS50x 2023 - Lecture 3 - Algorithms | Youtube Video |
| Learn Data Structures and Algorithms for free | Youtube Video |
| Big O: How Code Slows as Data Grows | Youtube Video |
| Big-O Notation - For Coding Interviews | Youtube Video |
| The Complete Guide to Big O Notation & Complexity Analysis for Algorithms: Part 1 of 2 | Youtube Video |
| Videos | Links |
|---|---|
| Recursion in Programming - Full Course | Youtube Video |
| Linked Lists for Technical Interviews - Full Course | Youtube Video |
| Binary Tree Algorithms for Technical Interviews - Full Course | Youtube Video |
| Graph Algorithms for Technical Interviews - Full Course | Youtube Video |
| Dynamic Programming - Learn to Solve Algorithmic Problems & Coding Challenges | Youtube Video |
| Websites | Description | Links |
|---|---|---|
| neetcode.io | This website covers wide range problem with Video Solution + Roadmap for Beginners | Website |
| seanprashad.com/leetcode-patterns | Company wise DSA Problems | Website |
| bigocheatsheet.com | This webpage covers the space and time Big-O complexities of common algorithms used in Computer Science. | Website |
| igotanoffer.com | All in one DSA Refresh with Great Time & Space PDF | Website |
| metacareers.com | DSA from Meta Careers | Website |
| techinterviewhandbook.org | Blind 75 + Grind 169 | Website |
A data structure is a way of organizing and managing data so that it can be accessed and processed efficiently. There are many different data structures, each with its own strengths and weaknesses. Some common data structures include s
| Data Structure | Description | Learning Resources |
|---|---|---|
| Array | Array Data Type Description | Array Resources |
| Dictionaries | Dictionaries Data Type Description | |
| Hashing | Hashing Data Type Description | |
| Hash Table | Hash Table Data Type Description | |
| Heap | Heap Data Type Description | |
| Stacks | Stacks Data Type Description | |
| Queues | Queues Data Type Description | |
| Linked Lists | Linked Lists Data Type Description | |
| Trees | Trees Data Type Description | |
| Binary Tree | Binary Tree Data Type Description | |
| Graph | Graph Data Type Description |
An algorithm is a procedure used for solving a problem or performing a computation
| Algorithm | Description | Learning Resources |
|---|---|---|
| Sliding Widow | - | Resources |
| Two Pointer | - |
this
| Method | Description | Time Complexity | Space Complexity |
|---|---|---|---|
list() |
Creates a new empty list. | O(1) | O(1) |
list(iterable) |
Creates a list from an iterable. | O(len(iterable)) | O(len(iterable)) |
append(element) |
Adds an element to the end of the list. | O(1) | O(1) |
extend(iterable) |
Extends the list by appending elements from the iterable. | O(len(iterable)) | O(len(iterable)) |
insert(index, element) |
Inserts an element at the specified index. | O(n) where n is the length of the list | O(1) |
remove(element) |
Removes the first occurrence of the specified element. | O(n) where n is the length of the list | O(1) |
pop(index) |
Removes and returns the element at the specified index. | O(n) where n is the length of the list | O(1) |
index(element) |
Returns the index of the first occurrence of the specified element. | O(n) where n is the length of the list | O(1) |
count(element) |
Returns the number of occurrences of the specified element. | O(n) where n is the length of the list | O(1) |
sort() |
Sorts the elements of the list in ascending order. | O(n*log(n)) where n is the length of the list | O(log(n)) |
reverse() |
Reverses the elements of the list in-place. | O(n) where n is the length of the list | O(1) |
copy() |
Returns a shallow copy of the list. | O(n) where n is the length of the list | O(n) where n is the length of the list |
clear() |
Removes all elements from the list. | O(1) | O(1) |
len(list) |
Returns the number of elements in the list. | O(1) | O(1) |
list.remove() with a loop |
Removes elements from the list based on a condition using a loop. | O(n) where n is the length of the list | O(1) |
list comprehension |
Creates a new list with the specified expression for each item in the iterable. | O(len(iterable)) | O(len(iterable)) |
map(function, iterable) |
Applies a function to all the items in the input iterable and returns a new list. | O(n) where n is the length of the iterable | O(n) where n is the length of the iterable |
Just so you know, these complexities are average-case complexities, and actual performance may vary based on specific Python implementations and hardware considerations. Use this information as a general guideline. If you have any more questions or need further clarification, feel free to ask!
Python Dictionary Time Complexity
| Method | Description | Time Complexity | Space Complexity |
|---|---|---|---|
dict() |
Creates a new empty dictionary. | O(1) | O(1) |
dict(mapping, **kwargs) |
Creates a dictionary from a mapping or keyword arguments. | O(len(mapping) + len(kwargs)) | O(len(mapping) + len(kwargs)) |
clear() |
Removes all items from the dictionary. | O(1) | O(1) |
copy() |
Returns a shallow copy of the dictionary. | O(len(dict)) | O(len(dict)) |
fromkeys(iterable, value) |
Creates a new dictionary with keys from the iterable and values set to the specified value. | O(len(iterable)) | O(len(iterable)) |
get(key, default=None) |
Returns the value for the specified key, or a default value if the key is not found. | O(1) | O(1) |
items() |
Returns a view of the dictionary's key-value pairs. | O(1) (for view creation), O(n) to access elements | O(1) (for view creation), O(n) to store elements |
keys() |
Returns a view of the dictionary's keys. | O(1) (for view creation), O(n) to access elements | O(1) (for view creation), O(n) to store elements |
values() |
Returns a view of the dictionary's values. | O(1) (for view creation), O(n) to access elements | O(1) (for view creation), O(n) to store elements |
pop(key, default=None) |
Removes and returns the value for the specified key, or a default value if the key is not found. | O(1) if the key is present, O(1) for default case | O(1) |
popitem() |
Removes and returns an arbitrary key-value pair. Raises KeyError if the dictionary is empty. | O(1) | O(1) |
setdefault(key, default=None) |
Returns the value for the specified key, or inserts the key with a default value if the key is not found. | O(1) if the key is present, O(1) for default case | O(1) |
update(iterable) |
Updates the dictionary with key-value pairs from another iterable or dictionary. | O(len(iterable)) | O(len(iterable)) |
pop(key) |
Removes and returns the value for the specified key. Raises KeyError if the key is not found. | O(1) | O(1) |
keys() |
Returns a view of the dictionary's keys. | O(1) (for view creation), O(n) to access elements | O(1) (for view creation), O(n) to store elements |
values() |
Returns a view of the dictionary's values. | O(1) (for view creation), O(n) to access elements | O(1) (for view creation), O(n) to store elements |
items() |
Returns a view of the dictionary's key-value pairs. | O(1) (for view creation), O(n) to access elements | O(1) (for view creation), O(n) to store elements |
clear() |
Removes all items from the dictionary. | O(1) | O(1) |
len(dict) |
Returns the number of items in the dictionary. | O(1) | O(1) |
in and not in operators |
Checks if a key is present in the dictionary. | O(1) | O(1) |
dict comprehension |
Creates a new dictionary with the specified expression for each key-value pair in the iterable. | O(len(iterable)) | O(len(iterable)) |
Just so you know, these complexities are average-case complexities, and actual performance may vary based on specific Python implementations and hardware considerations. Use this information as a general guideline. If you have any more questions or need further clarification, feel free to ask!
Python Set Time Complexity
| Operation | Time Complexity |
|---|---|
set() |
O(1) |
set(iterable) |
O(len(iterable)) |
add(element) |
O(1) |
remove(element) |
O(1) if present, KeyError if not |
discard(element) |
O(1) if present, no action if not |
pop() |
O(1) - removes and returns an arbitrary element (KeyError if set is empty) |
clear() |
O(1) - removes all elements from the set |
element in set |
O(1) |
element not in set |
O(1) |
union(other_set) |
O(len(set) + len(other_set)) |
intersection(other_set) |
O(min(len(set), len(other_set))) |
difference(other_set) |
O(len(set)) |
symmetric_difference(other_set) |
O(len(set)) |
issubset(other_set) |
O(len(set)) |
issuperset(other_set) |
O(len(other_set)) |
len(set) |
O(1) |
copy() |
O(len(set)) |
{expression for item in iterable} |
O(len(iterable)) |
set.remove() with a loop |
O(n) where n is the number of elements to remove |