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hxu296/leetcode-company-wise-problems-2022

★ 11,179Jupyter NotebookAudience · developerComplexity · 1/5Setup · easy

TLDR

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.

Mindmap

mindmap
  root((leetcode-company-wise))
    What it is
      Interview question dataset
      184 companies
      May 2022 snapshot
    Data Fields
      Problem name
      Frequency count
      Difficulty level
    Format
      CSV files per company
      README tables
      LeetCode links
    Use Cases
      Targeted practice
      Study planner
      Data analysis
    Audience
      Job seekers
      Software engineers
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Code map

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Things people build with this

USE CASE 1

Look up which LeetCode problems Google, Amazon, or Meta ask most often and practice those first before your interview.

USE CASE 2

Download the CSV for a specific company and track which problems you have already solved as you work through the list.

USE CASE 3

Build a study planner or flashcard app using the frequency and difficulty data from the 184 included companies.

Tech stack

Jupyter NotebookCSV

Getting it running

Difficulty · easy Time to first run · 5min
No license information provided.

In plain English

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.

Copy-paste prompts

Prompt 1
I have an interview at [company name] in two weeks. Using the hxu296/leetcode-company-wise-problems-2022 data, give me the top 20 most frequently asked problems sorted by occurrence count.
Prompt 2
From the leetcode-company-wise-problems-2022 CSV files, find all medium-difficulty problems that appear at both Google and Meta so I can prioritize overlap questions.
Prompt 3
Using the CSV data from this repo, build me a Python script that reads a company name from the command line and prints the top 10 problems with their difficulty and LeetCode links.
Prompt 4
Which companies in this dataset ask the most dynamic programming problems? Analyze the CSV files and give me a ranked list.
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