{"id":18351827,"url":"https://github.com/codeslash21/explore_weather_trend","last_synced_at":"2025-10-29T23:11:58.203Z","repository":{"id":171246264,"uuid":"257396628","full_name":"codeslash21/explore_weather_trend","owner":"codeslash21","description":"Weather trends analysis of the World and the Delhi (India) city over last 150 years.","archived":false,"fork":false,"pushed_at":"2021-05-21T20:58:16.000Z","size":1123,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-10T00:46:12.643Z","etag":null,"topics":["data-visualization","nanodegree-project","python3","sql"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"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/codeslash21.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}},"created_at":"2020-04-20T20:31:14.000Z","updated_at":"2023-05-31T07:26:52.000Z","dependencies_parsed_at":null,"dependency_job_id":"6779068c-b188-4a6b-bc13-da949c1c6c57","html_url":"https://github.com/codeslash21/explore_weather_trend","commit_stats":null,"previous_names":["codeslash21/explore_weather_trend"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/codeslash21/explore_weather_trend","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/codeslash21%2Fexplore_weather_trend","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/codeslash21%2Fexplore_weather_trend/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/codeslash21%2Fexplore_weather_trend/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/codeslash21%2Fexplore_weather_trend/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/codeslash21","download_url":"https://codeload.github.com/codeslash21/explore_weather_trend/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/codeslash21%2Fexplore_weather_trend/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":269201173,"owners_count":24377450,"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","status":"online","status_checked_at":"2025-08-07T02:00:09.698Z","response_time":73,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":["data-visualization","nanodegree-project","python3","sql"],"created_at":"2024-11-05T21:33:03.646Z","updated_at":"2025-10-29T23:11:58.108Z","avatar_url":"https://github.com/codeslash21.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Explore_weather_trend\nHere we explore weather trends of the World the Delhi city over last 150 years. And analyse the trends of these two. This analysis is based on the `results.csv` file which contains average temperature data of the World and Delhi(India) city along with years.\n\nThe details and findings of the analysis is in the `Explore_weather_trend.pdf` file.\n\n## Dataset\n- **data/city_data.csv** This file contains average temperatures(°C) of cities around the World by year. This file consists of `year`, `city`, `country` and `avg_temp` columns.\n- **data/global_data.csv** This file contains average global temperatures(°C) by year. This ffile consists of `year` and `avg_temp` columns.\n- **data/results.csv** This file is created by extracting necessary data from the above two files using SQL queries for our analysis. This has `Year`, `Global_Temp`, `City_Temp` columns.\n\n\n## Requirements\n\u003e * SQL\n\u003e * Python3\n\u003e * Google Spreadsheet\n\u003e * Jupyter Notebook\n\n\u003c/br\u003e\n\n\n\n\n\n### License:\nThis project is under _MIT License_ see more in [LICENSE](https://github.com/codeslash21/explore_weather_trend/blob/master/LICENSE)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcodeslash21%2Fexplore_weather_trend","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcodeslash21%2Fexplore_weather_trend","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcodeslash21%2Fexplore_weather_trend/lists"}