{"id":22429869,"url":"https://github.com/alienobserver/datengeist","last_synced_at":"2026-02-03T08:31:24.338Z","repository":{"id":265229663,"uuid":"895527794","full_name":"alienobserver/datengeist","owner":"alienobserver","description":"Application for easy understanding of unstructured data","archived":false,"fork":false,"pushed_at":"2024-11-30T05:37:30.000Z","size":586,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-09-25T08:57:30.420Z","etag":null,"topics":["feature-engineering","machine-learning","streamlit"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/alienobserver.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}},"created_at":"2024-11-28T11:29:00.000Z","updated_at":"2024-11-30T05:37:34.000Z","dependencies_parsed_at":"2025-07-10T05:41:12.286Z","dependency_job_id":"68710d2b-d92d-4326-84f0-ee5cc3f5bc2d","html_url":"https://github.com/alienobserver/datengeist","commit_stats":null,"previous_names":["alienobserver/geist"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/alienobserver/datengeist","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alienobserver%2Fdatengeist","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alienobserver%2Fdatengeist/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alienobserver%2Fdatengeist/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alienobserver%2Fdatengeist/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/alienobserver","download_url":"https://codeload.github.com/alienobserver/datengeist/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alienobserver%2Fdatengeist/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29038509,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-03T06:39:36.383Z","status":"ssl_error","status_checked_at":"2026-02-03T06:39:32.787Z","response_time":96,"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":["feature-engineering","machine-learning","streamlit"],"created_at":"2024-12-05T21:06:00.218Z","updated_at":"2026-02-03T08:31:24.323Z","avatar_url":"https://github.com/alienobserver.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Datengeist\n## Application for easy understanding of unstructured data\n\nDatengeist is a streamlit built application which is made to understand unstructured data through visualization \nof its components. Datengeist is working with **.csv** files. Datengeist has this key functionalities:\n\n1. Categorization of features\n2. Visualization of distributions\n3. Convenient handling of missing data\n4. Tools for feature comparison\n\nTo run datengeist you can install via pip\n\n```\n$ pip install datengeist\n$ datengeist start\n```\n\nOr you can create a virtual environment and then run it (recommended)\n\n```\n$ python3 -m venv datengeist_env\n$ source datengeist_env/bin/activate\n\n$ pip install datengeist\n```\n\n### 1. Sample the Dataset\nSample the Dataset is where you can sample data, load it and have your first overview of the data\n\u003cimg src=\"https://raw.githubusercontent.com/alienobserver/geist/refs/heads/main/datengeist/assets/git_images/Screenshot%20from%202024-11-13%2013-02-23.png\" alt=\"screenshot\" width=\"600\" /\u003e\n\n### 2. General Info\nGeneral Info is where you can divide your features into corresponding categories and view your\nmissing values in each feature\n\n\u003cimg src=\"https://raw.githubusercontent.com/alienobserver/geist/refs/heads/main/datengeist/assets/git_images/Screenshot%20from%202024-11-13%2013-02-35.png\" alt=\"screenshot\" width=\"600\" /\u003e\n\n### 3. Feature Info\nFeature Info is where you can view your features more closely, the distributions and missing value percentage\n\u003cimg src=\"https://raw.githubusercontent.com/alienobserver/geist/refs/heads/main/datengeist/assets/git_images/Screenshot%20from%202024-11-13%2013-02-46.png\" alt=\"screenshot\" width=\"600\" /\u003e\n\u003cimg src=\"https://raw.githubusercontent.com/alienobserver/geist/refs/heads/main/datengeist/assets/git_images/Screenshot%20from%202024-11-13%2013-03-58.png\" alt=\"screenshot\" width=\"600\" /\u003e\n\n### 4. Relate Features\nRelate Features is where you can view the correlation between your features and relate them via box plotting\n\u003cimg src=\"https://raw.githubusercontent.com/alienobserver/geist/refs/heads/main/datengeist/assets/git_images/Screenshot%20from%202024-11-13%2013-04-22.png\" alt=\"screenshot\" width=\"600\" /\u003e\n\n### License \n\nApache 2.0\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falienobserver%2Fdatengeist","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falienobserver%2Fdatengeist","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falienobserver%2Fdatengeist/lists"}