{"id":20162715,"url":"https://github.com/airscholar/japan-visa-data-engineering","last_synced_at":"2025-10-11T01:13:02.093Z","repository":{"id":234048233,"uuid":"703431343","full_name":"airscholar/Japan-visa-data-engineering","owner":"airscholar","description":"This project provides an end-to-end data processing and visualization of visa numbers in Japan using PySpark and Plotly. The spark clusters are set up within a Docker container on Azure.","archived":false,"fork":false,"pushed_at":"2023-10-11T08:34:06.000Z","size":1530,"stargazers_count":11,"open_issues_count":0,"forks_count":12,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-04-10T00:36:49.164Z","etag":null,"topics":["azure","docker","japan","master-worker-architecture","pyspark","python","spark-clusters"],"latest_commit_sha":null,"homepage":"https://www.youtube.com/watch?v=f-IcM8mFmDc","language":"HTML","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/airscholar.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-10-11T08:28:53.000Z","updated_at":"2025-03-23T10:42:03.000Z","dependencies_parsed_at":null,"dependency_job_id":"d7c7835e-05ab-49d7-a8e4-1f5b96e15cb6","html_url":"https://github.com/airscholar/Japan-visa-data-engineering","commit_stats":null,"previous_names":["airscholar/japan-visa-data-engineering"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/airscholar/Japan-visa-data-engineering","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/airscholar%2FJapan-visa-data-engineering","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/airscholar%2FJapan-visa-data-engineering/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/airscholar%2FJapan-visa-data-engineering/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/airscholar%2FJapan-visa-data-engineering/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/airscholar","download_url":"https://codeload.github.com/airscholar/Japan-visa-data-engineering/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/airscholar%2FJapan-visa-data-engineering/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":279005929,"owners_count":26083983,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-10T02:00:06.843Z","response_time":62,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["azure","docker","japan","master-worker-architecture","pyspark","python","spark-clusters"],"created_at":"2024-11-14T00:26:34.237Z","updated_at":"2025-10-11T01:13:02.034Z","avatar_url":"https://github.com/airscholar.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Japan Visa Analysis: Azure End to End Data Engineering 🌐\nThis project provides an end-to-end data processing and visualization of visa numbers in Japan using PySpark and Plotly. The spark clusters are set up within a Docker container on Azure.\n\n## 📝 Table of Contents\n- [System Architecture](#system-architecture)\n- [Setup \u0026 Requirements](#-setup--requirements)\n- [Usage](#-usage)\n- [Features](#-features)\n- [Notes](#-notes)\n- [Video](#-video)\n\n## System Architecture\n![System Architecture](assets/Sparkcluster_architecture.png)\n\n## 🛠 Setup \u0026 Requirements\n1. **Azure Account**: Ensure you have an active Azure account.\n2. **Docker**: The Spark master-worker architecture is set up in a Docker container on Azure.\n3. **Python Libraries**: Install the required Python libraries:\n   - PySpark\n   - Plotly Express\n   - pycountry\n   - pycountry_convert\n   - fuzzywuzzy\n\n## 🚀 Usage\n1. **Data Input**: Place your CSV file named `visa_number_in_japan.csv` in the `input` directory.\n2. **Run the Script**: Execute the provided Python script.\n3. **Visualizations**: After execution, you'll find the visualizations saved as HTML files in the `output` directory.\n4. **Cleaned Data**: The cleaned data will also be saved as a CSV file in the `output` directory.\n\n## 📈 Features\n- **System Architecture**: The Spark master-worker architecture is set up in a Docker container on Azure.\n- **Data Ingestion**: The script ingests the CSV file containing the visa numbers in Japan.\n- **Data Cleaning**: The script standardizes column names, drops null columns, and corrects country names using fuzzy matching.\n- **Data Transformation**: The data is further enriched by adding continent information for each country.\n- **Data Visualization**: The cleaned and transformed data is visualized using Plotly Express to provide insights into visa trends in Japan.\n\n## 📝 Notes\n- Ensure that your Azure and Docker setups are correctly configured to allow the Spark master-worker architecture to function seamlessly.\n- The country name corrections and continent mapping are based on the `pycountry` and `pycountry_convert` libraries. Ensure that these libraries are up-to-date to get accurate results.\n- You can adjust the manual mappings in the `country_mapping` dictionary in the `main.py` file to correct any country names that are not correctly matched.\n\n## 🎥 Video\n[![Japan Visa Analysis: Azure Data End to End Data Engineering](https://img.youtube.com/vi/f-IcM8mFmDc/0.jpg)](https://youtu.be/f-IcM8mFmDc)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fairscholar%2Fjapan-visa-data-engineering","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fairscholar%2Fjapan-visa-data-engineering","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fairscholar%2Fjapan-visa-data-engineering/lists"}