{"id":32453511,"url":"https://github.com/js-konda/naturaldisasterseda","last_synced_at":"2026-05-08T06:39:24.626Z","repository":{"id":45628755,"uuid":"424764452","full_name":"js-konda/NaturalDisastersEDA","owner":"js-konda","description":"The project repository for the Exploratory Data analysis of natural disasters done as part of ECE143 course at UCSD","archived":false,"fork":false,"pushed_at":"2021-12-04T08:35:45.000Z","size":18651,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":3,"default_branch":"main","last_synced_at":"2023-11-20T23:23:13.971Z","etag":null,"topics":["data-science","data-visualization","pandas","python","visualization"],"latest_commit_sha":null,"homepage":"","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/js-konda.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}},"created_at":"2021-11-04T23:03:20.000Z","updated_at":"2023-11-20T23:23:13.972Z","dependencies_parsed_at":"2022-09-10T12:21:47.941Z","dependency_job_id":null,"html_url":"https://github.com/js-konda/NaturalDisastersEDA","commit_stats":null,"previous_names":[],"tags_count":0,"template":null,"template_full_name":null,"purl":"pkg:github/js-konda/NaturalDisastersEDA","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/js-konda%2FNaturalDisastersEDA","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/js-konda%2FNaturalDisastersEDA/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/js-konda%2FNaturalDisastersEDA/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/js-konda%2FNaturalDisastersEDA/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/js-konda","download_url":"https://codeload.github.com/js-konda/NaturalDisastersEDA/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/js-konda%2FNaturalDisastersEDA/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":281074208,"owners_count":26439421,"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":"2025-10-26T02:00:06.575Z","response_time":61,"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-science","data-visualization","pandas","python","visualization"],"created_at":"2025-10-26T07:43:12.984Z","updated_at":"2025-10-26T07:44:24.949Z","avatar_url":"https://github.com/js-konda.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003ch1\u003eExploratory Analysis of Natural Disasters\u003c/h1\u003e\n\n![alt text](image/bubble.png)\n\n\u003ch2\u003eTeam Members\u003c/h2\u003e\n\nBy Jaya Konda, Pujika Kumar, Gaopo Huang, Jiawei Zheng, Andy Liu\n\n\u003ch2\u003eProblem \u003c/h2\u003e\n\nCan natural disasters increase public awareness of climate change?\nIs there any trend in natural disaster incidents and casualties from natural disasters over the years? \nHow impactful is the media interest of climate change over the natural disaster incidents?\n\n\u003ch2\u003e Motivation \u003c/h2\u003e\nOur primary motivation was to analyse the natural disasters to find if their occurrence or the deaths caused by them have stirred up any awareness about the climate change. Along the way, we have tried to draw important insights about the trends of natural disasters, and their impact on human lives.\n\n\u003ch2\u003eDataset\u003c/h2\u003e\n\nNatural Disaster incident over years ( https://www.kaggle.com/brsdincer/all-natural-disasters-19002021-eosdis). This dataset contains 2 csv files, with each containing 45 columns having information about year, disaster type, country, etc. \n\nMedia (specifically TV news) interest in climate change over years: (https://blog.gdeltproject.org/a-new-dataset-for-exploring-climate-change-narratives-on-television-news-2009-2020/). This data contains 418 csv files, with each containing information about TV news reported on these natural disasters. \n\nCapital over gdp. This dataset contains columns and 19879 rows\n(https://data.worldbank.org/indicator/NY.GDP.PCAP.PP.CD)\n\n\u003ch2\u003eFile Structure\u003c/h2\u003e\n\n    .\n    ├── Code                                # .py files that contains our code to generate the graph\n    │   ├──__init__.py\n    │   ├──bubble.py\n    │   ├──major_disaster_analysis.py\n    │   ├──natural_disaster_climate_news_analysis.py\n    │   ├──pies.py  \n    │   ├──stacked_decadal.py\n    │   └──stacked_plots.py  \n    ├── dataset\t\t\t\t                # all the datasets we used\n    │   ├── TelevisionNews\n    |   |   └──*.CSV\n    │   ├──1900-2021_DISASTERS.xlsx - emdat data.csv\n    │   ├──1970-2021_DISASTERS.xlsx - emdat data.csv\n    │   └──gdp_per_capita.csv\n    ├── image                               # the graph we generated\n    │   └── bubble.png\n    │   \n    ├── Final presentation PPT.pdf          # pdf file for our presentation\n    ├── Final_project_code.ipynb\t\t    # notebook to display all our visualizations\n    ├── readme.md\t\t\t\t\t\t\t# readme file\n    └──.gitignore\n\n\u003ch2\u003eRequired Packages\u003c/h2\u003e\n\n* pandas\n\n```\npip install pandas\n```\n\n* numpy\n\n```\npip install numpy\n```\n\n* matplotlib\n\n```\npip install matplotlib\n```\n\n* geopandas\n\n```\npip install geopandas\n```\n\n* seaborn\n\n```\npip install seaborn\n```\n\n\u003ch2\u003e Visualization \u003c/h2\u003e\n[Visualization Notebook](https://github.com/js-konda/ece-143/blob/main/Final_project_code.ipynb)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjs-konda%2Fnaturaldisasterseda","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjs-konda%2Fnaturaldisasterseda","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjs-konda%2Fnaturaldisasterseda/lists"}