What is the time complexity of Check if the Sentence Is Pangram?

The optimal solution has a time complexity of O(n).

What data structures are used to solve Check if the Sentence Is Pangram?

This problem uses Hash Table, String. Understanding these concepts is essential for solving this Easy problem efficiently.

What are the key insights for solving Check if the Sentence Is Pangram?

Insight 1: A set can be used to efficiently identify unique characters in the sentence. Since sets only store unique elements, the size of the set representing the sentence will directly indicate whether all 26 letters are present. Insight 2: The Python `set()` function provides a concise way to create a set from an iterable (like a string).

Which companies ask LeetCode 1832. Check if the Sentence Is Pangram in interviews?

This problem is frequently asked at Vanguard.

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Check if the Sentence Is Pangram - LeetCode 1832 Solution

Q: How to solve Check if the Sentence Is Pangram?

The provided Python solution uses a very efficient approach. It leverages the properties of Python sets to determine if the sentence is a pangram. First, it converts the input sentence string into a set using `set(sentence)`. This automatically removes duplicate letters. Then, it checks if the size of this set is equal to 26 (the number of letters in the English alphabet). If the size is 26, it means all 26 letters are present, and the function returns `true`; otherwise, it returns `false`.

Check if the Sentence Is Pangram - Complete Solution Guide

Check if the Sentence Is Pangram is LeetCode problem 1832, a Easy level challenge. This complete guide provides step-by-step explanations, multiple solution approaches, and optimized code in python3.

Problem Statement

A pangram is a sentence where every letter of the English alphabet appears at least once. Given a string sentence containing only lowercase English letters, return true if sentence is a pangram , or false otherwise. Example 1: Input: sentence = "thequickbrownfoxjumpsoverthelazydog" Output: true Explanation: sentence contains at least one of every letter of the English alphabet. Example 2: Input: sentence = "leetcode" Output: false Constraints: 1 <= sentence.length <= 1000 sentence consists of lo

Detailed Explanation

The problem asks you to determine if a given sentence is a pangram. A pangram is a sentence containing every letter of the English alphabet at least once. The input is a string `sentence` consisting only of lowercase English letters. The output is a boolean value: `true` if the sentence is a pangram, and `false` otherwise. The input string's length is constrained to be between 1 and 1000 characters.

Solution Approach

The provided Python solution uses a very efficient approach. It leverages the properties of Python sets to determine if the sentence is a pangram. First, it converts the input sentence string into a set using `set(sentence)`. This automatically removes duplicate letters. Then, it checks if the size of this set is equal to 26 (the number of letters in the English alphabet). If the size is 26, it means all 26 letters are present, and the function returns `true`; otherwise, it returns `false`.

Step-by-Step Algorithm

Step 1: Convert the input string `sentence` into a set using `set(sentence)`. This creates a set containing only the unique characters from the sentence.
Step 2: Check the length of the set. If `len(set(sentence))` is equal to 26, it means all 26 letters of the English alphabet are present in the sentence.
Step 3: Return `true` if the length of the set is 26, indicating a pangram; otherwise, return `false`.

Key Insights

Insight 1: A set can be used to efficiently identify unique characters in the sentence. Since sets only store unique elements, the size of the set representing the sentence will directly indicate whether all 26 letters are present.
Insight 2: The Python `set()` function provides a concise way to create a set from an iterable (like a string).
Insight 3: No special handling of edge cases is needed because the problem constraints guarantee lowercase English letters only and a sentence length greater than 0.

Complexity Analysis

Time Complexity: O(n)

Space Complexity: O(1)

Topics

This problem involves: Hash Table, String.

Companies

Asked at: Vanguard.

Check if the Sentence Is Pangram | LeetCode 1832

Easy

Hash Table String

Time: O(n)Space: O(1)

Solution Code

Available in:

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Problem Info

Description

Problem 1832: Check if the Sentence Is Pangram - Detailed explanation and solution approaches.

Topics

Hash Table String

Companies

Vanguard

Stats

Difficulty:Easy

Languages:2

Companies:1

Problem #:1832

Problem Explanation

💡

Think Before You Code

🤔 Ask Yourself

→What is the input? What output do I need?
→Can I solve a smaller version of this problem first?
→What patterns have I seen in similar problems?

✏️ Try This First

Before looking at the solution, try to solve it on paper with a simple example!

🚀 Try on LeetCode

Solution Approach

📋

Step-by-Step Solution

3 steps

1
Step 1: Convert the input string `sentence` into a set using `set(sentence)`. This creates a set containing only the unique characters from the sentence.
2
Step 2: Check the length of the set. If `len(set(sentence))` is equal to 26, it means all 26 letters of the English alphabet are present in the sentence.
3
Step 3: Return `true` if the length of the set is 26, indicating a pangram; otherwise, return `false`.

💡

Pro Tip for Students

Try tracing through each step with a small example on paper before coding. Understanding "why" each step happens is more important than memorizing the code!

⚡

Complexity Analysis

⏱️

Time Complexity

O(n)

👍 Linear - Good! Visits each element once.

💾

Space Complexity

O(1)

💪 Constant space - Uses same memory regardless of input!

📝

Why?

Creating the set takes O(n) time in the worst case, where n is the length of the sentence. This is because each character in the sentence needs to be processed to check for duplicates. However, the space complexity is O(1) because the size of the set is always at most 26 (the number of letters in the alphabet), regardless of the input sentence length. The space used is constant.

📖New to Big O? Click to learn more

Big O Notation - Quick Guide

O(1)Best - Instant

O(log n)Excellent - Binary Search

O(n)Good - One loop

O(n log n)OK - Sorting

O(n²)Slow - Nested loops

O(2ⁿ)Very Slow - Recursion

Alternative Approaches

Using a list of booleans

Create a list of 26 booleans, one for each letter. Iterate through the sentence and mark the corresponding boolean to `True` when a letter is encountered. Finally, check if all booleans are `True`.

Time: O(n)Space: O(1)

Trade-offs: This approach is slightly less concise than the set approach but might be more understandable for beginners. The set approach is generally preferred for its elegance and efficiency.

Using a bit vector

Use a 32-bit integer as a bit vector, where each bit represents a letter of the alphabet. Iterate through the sentence and set the corresponding bit. Check if all bits are set at the end.

Time: O(n)Space: O(1)

Trade-offs: This is a space-optimized approach, useful for extremely constrained memory environments. However, it might be less readable than the other methods.

✨

Key Insights

1Insight 1: A set can be used to efficiently identify unique characters in the sentence. Since sets only store unique elements, the size of the set representing the sentence will directly indicate whether all 26 letters are present.
2Insight 2: The Python `set()` function provides a concise way to create a set from an iterable (like a string).
3Insight 3: No special handling of edge cases is needed because the problem constraints guarantee lowercase English letters only and a sentence length greater than 0.

📚

Key Terms Explained

For Students

Hash Table

A data structure that maps keys to values for quick lookup. Like a dictionary!

String

A sequence of characters. Like a word or sentence in programming!

Edge Cases

Edge case 1: An empty sentence. This is handled implicitly by the constraints (sentence length >= 1).
Edge case 2: A sentence with repeated letters. The `set()` function automatically handles duplicates, so it doesn't affect the solution's correctness.

⚠️

Common Mistakes to Avoid

✗Common mistake 1: Forgetting to account for duplicate letters. Using a set elegantly avoids this mistake.

✗Common mistake 2: Incorrectly calculating the time or space complexity. Understanding the time complexity of set creation and the constant space usage of a set of limited size is crucial.

✅

Learning Tip

Every mistake is a learning opportunity! When you make an error, understand why it happened before moving on.

🌍

Where is This Used in Real Life?

💼Real-world scenario 1: Text analysis tools could use this to check the richness of vocabulary in a text sample. A pangram suggests a wider range of vocabulary.

🏦Real-world scenario 2: Cryptography and code-breaking: Checking for a pangram could be a preliminary step in analyzing ciphertext to identify potential alphabets used in a substitution cipher.

💡Understanding real-world applications helps you see the "why" behind algorithms. It's not just about passing interviews—these concepts power the apps and websites you use every day!

Author's Notes

💡 Key Insight

Hash tables trade space for time. Before using one, consider if the problem constraints allow the extra memory. In interviews, always mention this trade-off.

🎯 Interview Tip

Don't rush. Explain your thought process clearly. Easy problems are often about communication.

⚠️ Watch Out

Don't forget to handle key collisions and null/undefined keys. Consider what happens with duplicate values.

Written by Saswata Mondal

Software Engineer • Algorithms Enthusiast • Interview Coach

👨‍💻

About the Author

👨‍💻

Saswata MondalAuthor400+ LC Problems

B.Tech CSE, IEM Kolkata | LeetCode Rating: 1672 (Top 15%)

Certified: IBM Java Developer, NPTEL Programming in Java

Last updated: July 3, 2024LeetCode Profile GitHub

This solution has been crafted based on my experience solving 400+ LeetCode problems. Each explanation is designed to help you understand the underlying concepts, not just memorize the code.

Community Tips & Insights

I was asked this exact problem at my Google interview. The interviewer wanted me to optimize space complexity.

@InterviewProJul 13

Try solving this without using extra space first. It's a great exercise for understanding the underlying pattern.

@CodeNinjaJul 6

❓

Frequently Asked Questions

What are the trade-offs of using a hash table?

Hash tables provide O(1) average-case lookup, insertion, and deletion, making them ideal for frequency counting and duplicate detection. However, they use O(n) extra space and may degrade to O(n) time in worst-case scenarios with hash collisions. Always consider if the space trade-off is acceptable.

How do I handle string manipulation efficiently?

In languages with immutable strings (Java, Python, C#), use StringBuilder/list to avoid O(n) concatenation cost. Consider using character arrays for in-place modifications. For pattern matching, consider KMP or Rabin-Karp for O(n+m) complexity.

How should I approach easy-level algorithm problems?

Easy problems build foundational skills. Focus on: 1) Understanding the problem completely before coding, 2) Writing clean, readable code, 3) Handling all edge cases (empty input, single element, etc.), 4) Analyzing time and space complexity. Don't skip complexity analysis even for simple solutions.

How should I practice algorithm problems effectively?

Focus on understanding patterns rather than memorizing solutions. After solving a problem, review optimal solutions and understand the intuition. Group similar problems to recognize patterns. Practice explaining your approach out loud. Review problems after a few days to test retention.

What is the optimal approach for "Check if the Sentence Is Pangram"?

For this easy-level Hash Table problem, the key is to identify the core pattern. Analyze the input constraints to determine acceptable time complexity. Consider whether string techniques can optimize the solution. Always handle edge cases and validate your approach with examples before coding.

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