hxu296/leetcode-company-wise-problems-2022 — explained in plain English
Analysis updated 2026-06-24
Look up which LeetCode problems Google, Amazon, or Meta ask most often and practice those first before your interview.
Download the CSV for a specific company and track which problems you have already solved as you work through the list.
Build a study planner or flashcard app using the frequency and difficulty data from the 184 included companies.
| hxu296/leetcode-company-wise-problems-2022 | salesforce/lavis | aws/amazon-sagemaker-examples | |
|---|---|---|---|
| Stars | 11,179 | 11,221 | 10,922 |
| Language | Jupyter Notebook | Jupyter Notebook | Jupyter Notebook |
| Setup difficulty | easy | hard | moderate |
| Complexity | 1/5 | 4/5 | 3/5 |
| Audience | developer | researcher | data |
Figures from each repo's GitHub metadata at analysis time.
This repository is a reference tool for software engineers preparing for job interviews. LeetCode is a website that hosts programming puzzles used heavily in software engineering hiring processes at major technology companies. The site's paid tier tags certain problems as frequently asked at specific companies, and this repository collected and organized that data as of May 2022. The main content is a set of CSV files, one per company, each listing the coding problems that company has historically asked in technical interviews along with how often each problem appeared and its difficulty level (easy, medium, or hard). The repository covers 184 companies, ranging from large tech employers like Google, Amazon, Microsoft, and Meta to smaller firms, financial companies, and startups from around the world. Within the README itself, each company section shows the same information as a table, with links to the problem on LeetCode and links to community-contributed solutions in a companion GitHub repository. The occurrence count next to each problem indicates roughly how many times that question has appeared in reports from people who interviewed at that company. This kind of organized list helps job seekers focus their preparation time. Rather than working through problems at random, a person interviewing at a particular company can start with that company's most frequently seen questions. The data is a snapshot from May 2022, so it reflects question patterns from around that time and may not capture more recent interview trends. The full README is longer than what was shown.
A snapshot dataset of LeetCode interview questions organized by company, 184 companies with frequency counts and difficulty levels, so job seekers can focus their practice on what each company actually asks.
Mainly Jupyter Notebook. The stack also includes Jupyter Notebook, CSV.
No license information provided.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.