{"id":17331439,"url":"https://github.com/eliasdabbas/word_frequency","last_synced_at":"2025-04-14T18:05:02.611Z","repository":{"id":93446798,"uuid":"118538650","full_name":"eliasdabbas/word_frequency","owner":"eliasdabbas","description":"Absolute and Weighted Word Frequency","archived":false,"fork":false,"pushed_at":"2018-04-24T14:06:24.000Z","size":694,"stargazers_count":7,"open_issues_count":1,"forks_count":9,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-04-14T18:03:38.363Z","etag":null,"topics":["defaultdict","keyword-extraction","keywords","python","text-mining"],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","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/eliasdabbas.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,"zenodo":null}},"created_at":"2018-01-23T01:19:40.000Z","updated_at":"2021-05-15T02:29:48.000Z","dependencies_parsed_at":"2023-03-13T17:18:18.587Z","dependency_job_id":null,"html_url":"https://github.com/eliasdabbas/word_frequency","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/eliasdabbas%2Fword_frequency","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/eliasdabbas%2Fword_frequency/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/eliasdabbas%2Fword_frequency/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/eliasdabbas%2Fword_frequency/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/eliasdabbas","download_url":"https://codeload.github.com/eliasdabbas/word_frequency/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248933339,"owners_count":21185460,"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","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":["defaultdict","keyword-extraction","keywords","python","text-mining"],"created_at":"2024-10-15T14:54:25.003Z","updated_at":"2025-04-14T18:05:02.590Z","avatar_url":"https://github.com/eliasdabbas.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Word Frequency in a Collection of Documents (absolute and weighted)\n\n\nInteresting insights can be gained when text documents (tweets, keywords, web pages, etc) have associated numeric metrics with them.\n\nThis is a description of how this can be done through a Python function.\n\nThe notebook describes the process starting from a collection of two one-word 'documents' up to analyzing a list of 15,000 \nmovie titles together with their lifetime gross revenue. \n\nAdditional data sets are provided for illustration and practice. \n\n[Explore the notebook](abs_weighted_frequency.ipynb)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Feliasdabbas%2Fword_frequency","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Feliasdabbas%2Fword_frequency","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Feliasdabbas%2Fword_frequency/lists"}