Data Analysis Project

KO | EN

This project performs CSV-based data analysis using Python and visualizes the results through a dashboard built with Next.js (React).

The backend is responsible for loading CSV data, preprocessing, computing statistical metrics, and generating structured JSON artifacts.
These artifacts are saved in the artifacts/ directory for direct use by the frontend.

The frontend loads the generated JSON files and renders a visual dashboard consisting of charts and tables.

Dataset Source

This project uses the following dataset sourced from Kaggle. 600+ programming questions with difficulty, description, examples, constraints, and test cases.

Coding Questions Dataset

License: MIT License
Original dataset author: Kartikeya Pandey

The original CSV dataset is included in this repository and is used as input for the Python analysis pipeline.
Redistribution and modification are permitted under the MIT License, and the dataset is processed to generate derived artifacts such as JSON files, charts, and Excel exports.

Repositories

frontend | backend

Project Structure

final-project-data-analysis/
│
├─ back/                  # Python data analysis pipeline
│   ├─ README.md          # Backend-specific documentation
│   ├─ requirements.txt   # Python dependencies
│   ├─ data/              # Input CSV files
│   ├─ artifacts/         # Analysis outputs (JSON, charts, Excel exports)
│   └─ src/               # Source code (app/domain/infrastructure/presentation)
│
├─ front/                 # Next.js dashboard
│   ├─ README.md          # Frontend-specific documentation
│   ├─ package.json
│   ├─ public/            # Static assets
│   └─ src/               # Feature-sliced React code + shared generated data
│
├─ docs/                  # Documentation set (KO/EN)
│   ├─ README.ko.md              # Korean overview
│   ├─ requirements-analysis/    # 요구사항 및 목표 분석
│   ├─ io-design/                # 입출력/데이터 계약 정리
│   └─ system-architecture/      # 시스템 & 계층 구조 설명
│
└─ video/                 # Demonstration video
    └─ demo.mp4

Backend Summary (back/)

• Entry: back/src/app/main.py

• Default dataset: back/data/coding-questions-dataset/questions_dataset.csv

• Outputs: back/artifacts/json (frontend-ready JSON), back/artifacts/charts, back/artifacts/xlsx (Excel splits), and front/src/shared/data (synced JSON for the UI).

• Run locally (from back):

  export PYTHONPATH="$(pwd)/src"
  python -m backend.app.main --data-file data/coding-questions-dataset/questions_dataset.csv

  Frontend Summary (front/)

• Next.js (App Router) dashboard with tabs for Overview, Difficulty, Tags, Structure, and Raw data.

• Uses generated JSON files in front/src/shared/data (e.g., overview.json, difficulty.json, summary-full.json).

• Start dev server (from front):

  npm install
  npm run dev
  # visit http://localhost:3000

License

This project is licensed under the MIT License. See the LICENSE file for the full text.