SOLVING ALL Arrays & Hashmap | Blind75 LeetCode Problems

Today I solve and explain all 8 Blind75 Arrays & Hashing problems live in one sitting.

If you found this helpful Like and Subscribe! I solve LeetCode Algorithms (Python/ Java) and SQL Problems daily!

#leetcode #python #python3 #tutorial #coding #programming

[codewithcarter]

How is your LeetCode grind going? Comment below a Leetcode question you need help with!! 🙏

[beanwillis]

Watching people doing these problems differently is really helpful to learn tricks to think and write code efficiently. Thanks for doing this Carter

[bharanidharansundar]

🎯 Key Takeaways for quick navigation:

00:00 📚 *Introduction to problem-solving approach*
- Explanation of the Blind75 LeetCode Problems list created by Fang Engineers.
- Overview of the first problem "Contains Duplicates" and the use of a set to detect duplicates efficiently.
02:56 🔄 *Problem-solving approach for "Contains Duplicates"*
- Iterating through the array to check for duplicates.
- Using a set for quick lookup.
- Returning true if a duplicate is found, false otherwise.
05:52 🔄 *Problem-solving approach for "Valid Anagrams"*
- Using a hash map (counter) for letter occurrences.
- Checking if both strings have the same letter occurrences.
- Returning true if anagrams, false otherwise.
08:36 🔄 *Problem-solving approach for "Two Sums"*
- Utilizing a hash map for quick value-index lookup.
- Finding pairs of numbers that sum to the target.
11:31 🔄 *Problem-solving approach for "Group Anagrams"*
- Sorting letters to create a hash function.
- Using a defaultdict to group anagrams.
- Returning the grouped anagrams.
14:59 📊 *Problem-solving approach for "Top K Frequent Elements"*
- Counting occurrences and grouping numbers.
- Using a Max Heap to efficiently retrieve top K elements.
18:00 📊 *Problem-solving approach continued for "Top K Frequent Elements"*
- Using a Max Heap to efficiently retrieve top K elements.
- Iterating through occurrences and updating the result.
19:49 🔄 *Problem-solving approach for "Product of Array Except Self"*
- Handling cases with multiple zeros.
- Calculating the product with and without zeros.
23:51 🔄 *Problem-solving approach continued for "Product of Array Except Self"*
- Calculating the product with and without zeros.
- Constructing the final result array.
25:20 🧩 *Problem-solving approach for "Encode and Decode Strings"*
- Implementing encode and decode methods for a list of strings.
- Concatenating strings with special delimiters for encoding and decoding.
25:34 🧩 *Strings and Delimiters*
- Explains the challenge of converting a list of strings to a single string and back without a clear delimiter.
- Describes a practical solution by specifying the length of the string and using a hash to indicate the delimiter.
- Demonstrates encoding and decoding using the specified approach.
33:10 📈 *Longest Consecutive Sequence*
- Discusses the problem of finding the longest consecutive sequence in an array.
- Proposes an algorithm with O(n) time complexity, avoidingsorting, and using space complexity for optimization.
- Details the approach of iterating through the array, adding numbers to a set, and checking consecutive lengths while avoiding repeated work.

Made with HARPA AI

[alison-in]

Great Video,
Also, want to say that in problem "238. Product of Array Except Self" you used a division operator, but in the problem description is said: "You must write an algorithm that runs in O(n) time and without using the division operation."

[omarllama]

I just want to salute your for solving these problems yourself without looking to their solutions or making use of LLMs.

I know this because for some of these problems you didn't give the most efficient solution, which is completely fine given the limited amount of time.

[SAURABHKUMAR-ukgg]

FYI - the code used is not directed towards the most efficient time and space complexity, it's more so to understand the data structures in Python and the methods/functions applied on top of it. If you really want the time space complexity, refer to the original NeetCode videos. Thank you Carter, the videos are a good way of refresher for DE interviews

[mohammad-javadd.b.]

for 242. Valid Anagram if we are allowed to use Counter, why not just ` return Counter(s)==Counter(t)'

[messiisthebest]

in Q no 2, you can easily sort them, and compare them to check if they are anagrams or not

[thegreatestcomesfromthewor]

Thank you for the video. Could you do 953. Verifying an Alien Dictionary? I couldn't come up with a solution, and I am lost :(

[armandotaveras]

Hey, what extension are you using to draw on top of your scree?

[cherylto]

for goptKFrequent, i did something like this ....
def topKFrequent(nums: List[int], k: int) -> List[int]:
hmap = {}
for num in nums:
hmap[num] = 1 + hmap.get(num, 0)
sorted_hmap = dict(sorted(hmap.items(), key=lambda x: x[1], reverse=True)[:k])
return sorted_hmap.keys()
What is the benefit of doing it using heapify - I've never come across that before