🔹 Problem: 3403 Find The Lexicographically Largest String From The Box I
Difficulty: #Medium
Tags: #Greedy #TwoPointer
📝 Problem Summary (in your own words)
I hate anything that has the word "lexicographically" in it. It alwasy makes me feel like I have no Idea what I'm doing. But here we are. The problem is asking us to find the [[theories/lexicographically_largest_string]] from a given string
s
if we split it intonumFriends
parts. Confused yet?
🧠 My Thought Process
-
Optimized Strategy:
This problem has nothing to do with lexicography. We just need to find the largest possible substring with the largestorder
of characters. A charecter with a higherorder
is considered lexicographically larger. So,b
is larger thana
,c
is larger thanb
, and so on.- This of it like this:
- If we have a string with 6 charecters and we need to split it into 2 parts, The maximum possible substring length we can have is 5 and minimum is 1.
- But here's is the catch, even if the smaller substring is smaller than the larger one, It can still be lexicographically larger if it has a higher order character.
- So, we just need to find the largest character in the string and try to take the largest possible substring that starts with that character.
Algorithm Used:
[[two_pointer]]
⚙️ Code Implementation (Python)
class Solution:
def answerString(self, word: str, numFriends: int) -> str:
if numFriends == 1:
return word
n = len(word)
r = n-numFriends+1
max_char = max(word)
ans = ''
for l in range(n):
if word[l] == max_char:
sub = word[l:l+r]
ans = max(ans, sub)
return ans
⏱️ Time & Space Complexity
-
Time: O(n^2)
- We iterate through the string and for each character, we check the substring of length
r
starting from that character. But average case is O(n) because we only check the substring if the character is the maximum character in the string.
- We iterate through the string and for each character, we check the substring of length
-
Space: O(n)
- The space complexity is O(n) because we store the maximum substring in the
ans
variable.
- The space complexity is O(n) because we store the maximum substring in the
🧩 Key Takeaways
-
✅ What concept or trick did I learn?
- Greedy approach is not that bad after all.
-
💡 What made this problem tricky?
- The word "lexicographically" made it sound more complex than it is. It's just about finding the largest substring starting with the largest character.
-
💭 How will I recognize a similar problem in the future?
- Look for problems that wants me to split a string into parts and find the largest substring with constraints.
🔁 Reflection (Self-Check)
- [🫰] Could I solve this without help?
- [😐] Did I write code from scratch?
- [✅] Did I understand why it works?
- [😊] Will I be able to recall this in a week?
📚 Related Problems
- [[notes/1163 Last Substring in Lexicographical Order]]
- [[notes/1718 Construct the Lexicographically Largest Valid Sequence]]
🚀 Progress Tracker
Metric | Value |
---|---|
Day | 9 |
Total Problems Solved | 344 |
Confidence Today | 😃 |
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