{"payload":{"pageCount":1,"repositories":[{"type":"Public","name":"drilsdown","owner":"Unidata","isFork":false,"description":"Drawing Rich Integrated Lat-lon- time Samples from Datasets Online into Working Notebooks","topicNames":[],"topicsNotShown":0,"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":4,"starsCount":3,"forksCount":7,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-05-10T15:34:03.610Z"}},{"type":"Public","name":"users-workshop-2023","owner":"Unidata","isFork":false,"description":"Repo covering Jupyter Notebook resources for Unidata's 2023 triennial meeting held in Boulder, Colorado","topicNames":["python","machine-learning","climate","pandas","data-visualization","atmosphere","xarray"],"topicsNotShown":0,"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":0,"starsCount":6,"forksCount":5,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-06-12T15:18:09.589Z"}},{"type":"Public","name":"python-training","owner":"Unidata","isFork":false,"description":"Notebooks teaching Python for use meteorology and atmospheric and climate sciences.","topicNames":["hacktoberfest","meteorology"],"topicsNotShown":0,"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":3,"issueCount":62,"starsCount":123,"forksCount":68,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-02-07T19:15:08.799Z"}}],"repositoryCount":3,"userInfo":null,"searchable":true,"definitions":[],"typeFilters":[{"id":"all","text":"All"},{"id":"public","text":"Public"},{"id":"source","text":"Sources"},{"id":"fork","text":"Forks"},{"id":"archived","text":"Archived"},{"id":"mirror","text":"Mirrors"},{"id":"template","text":"Templates"}],"compactMode":false},"title":"Repositories"}