{"id":26396284,"url":"https://github.com/vipulbunny/book-data-analysis","last_synced_at":"2026-04-15T16:03:47.143Z","repository":{"id":277200721,"uuid":"931665140","full_name":"VIPULbunny/Book-Data-Analysis","owner":"VIPULbunny","description":"A Python-based data analysis project for cleaning, processing, and visualizing book data from a JSON dataset.","archived":false,"fork":false,"pushed_at":"2025-02-24T11:44:09.000Z","size":11,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-10-26T01:49:48.806Z","etag":null,"topics":["booksdataset","data-science","datacleaning","json","matplotlib","matplotlib-pyplot","pandas","python","seaborn","visualization"],"latest_commit_sha":null,"homepage":"","language":"Python","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/VIPULbunny.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":"2025-02-12T16:51:46.000Z","updated_at":"2025-02-24T11:44:12.000Z","dependencies_parsed_at":"2025-02-20T23:31:45.486Z","dependency_job_id":null,"html_url":"https://github.com/VIPULbunny/Book-Data-Analysis","commit_stats":null,"previous_names":["vipulbunny/book-data-analysis-cleaning","vipulbunny/book-data-analysis"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/VIPULbunny/Book-Data-Analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VIPULbunny%2FBook-Data-Analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VIPULbunny%2FBook-Data-Analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VIPULbunny%2FBook-Data-Analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VIPULbunny%2FBook-Data-Analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/VIPULbunny","download_url":"https://codeload.github.com/VIPULbunny/Book-Data-Analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VIPULbunny%2FBook-Data-Analysis/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31848664,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-15T15:24:51.572Z","status":"ssl_error","status_checked_at":"2026-04-15T15:24:39.138Z","response_time":63,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["booksdataset","data-science","datacleaning","json","matplotlib","matplotlib-pyplot","pandas","python","seaborn","visualization"],"created_at":"2025-03-17T11:28:07.525Z","updated_at":"2026-04-15T16:03:47.115Z","avatar_url":"https://github.com/VIPULbunny.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 📚 Book Data Cleaning and Analysis\n\n## 📝 Description\nThis project focuses on **cleaning, transforming, and analyzing book-related data** from a JSON dataset. It includes preprocessing techniques to handle missing values, incorrect formats, and unnecessary columns. The final cleaned dataset is used for **data visualization and exploratory data analysis (EDA)** using **Pandas, Matplotlib, and Seaborn**.\n\n## 🔍 Detailed Description\nThis repository contains a **Python script** that loads book data from an online JSON file, processes it, and performs various data-cleaning operations such as:\n\n- Handling **missing values** and incorrect formats.\n- Cleaning **ISBN** numbers and **publication dates**.\n- Removing **duplicates** and irrelevant columns.\n- Renaming columns for better readability.\n- Performing **data visualization** to analyze book publishing trends and status distributions.\n\n## 🚀 Features\n- **Data Cleaning**: Prepares raw JSON data into structured Pandas DataFrame.\n- **Exploratory Data Analysis (EDA)**: Uses visualizations to extract insights.\n- **Automated Preprocessing**: Handles missing values and formatting inconsistencies.\n- **Simple and Efficient Code**: Well-commented and easy to understand.\n\n## 🏗️ Technologies Used\n- **Python**\n- **Pandas**\n- **NumPy**\n- **Matplotlib**\n- **Seaborn**\n- **Requests**\n- **Regular Expressions (re)**\n\n## 📂 Project Structure\n```\n📦 Book-Data-Analysis\n ┣ 📜 book_analysis.py  # Main Python script for data cleaning and visualization\n ┣ 📜 README.md         # Project documentation\n ┗ 📜 requirements.txt  # List of dependencies\n```\n\n## 🛠️ Setup \u0026 Installation\n### 1️⃣ Install Required Libraries\nEnsure you have **Python 3.7+** installed. Install dependencies using:\n```bash\npip install -r requirements.txt\n```\n\n### 2️⃣ Run the Script\nExecute the script with:\n```bash\npython book_analysis.py\n```\n\n## 📊 Sample Visualizations\n![image](https://github.com/user-attachments/assets/34f22f54-8e80-4c82-92d2-0c17e3d42fcb)\n![image](https://github.com/user-attachments/assets/690113e0-02d2-4548-8d80-bd6f38a9b533)\n![image](https://github.com/user-attachments/assets/ec32001b-11b8-4b17-b3a0-8e608af0d371)\n\n## 🏆 Results \u0026 Insights\n- The dataset contains books published between **1993 and 2013**.\n- Most books have a **status of Published**, while some are **Unpublished**.\n- The **top 10 books with the highest page count** were identified and visualized.\n\n## 📌 Tags\n`Data Cleaning` `Pandas` `Python` `Data Analysis` `Visualization` `Book Dataset` `Seaborn` `Matplotlib`\n\n## 📜 License\nThis project is **open-source** and available for use and modification.\n\n---\n\n**👨‍💻 Developed by [VIPULbunny]**\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvipulbunny%2Fbook-data-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvipulbunny%2Fbook-data-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvipulbunny%2Fbook-data-analysis/lists"}