{"id":20461479,"url":"https://github.com/pythonbyte/disaster-response-project","last_synced_at":"2026-06-07T15:32:06.491Z","repository":{"id":181433493,"uuid":"415382209","full_name":"pythonbyte/disaster-response-project","owner":"pythonbyte","description":"A web application that applies ML to disaster response data and classifies it","archived":false,"fork":false,"pushed_at":"2021-10-13T22:46:57.000Z","size":6839,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-01-16T00:37:41.395Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","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/pythonbyte.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}},"created_at":"2021-10-09T17:51:09.000Z","updated_at":"2021-10-13T22:46:59.000Z","dependencies_parsed_at":"2023-07-15T16:06:37.143Z","dependency_job_id":null,"html_url":"https://github.com/pythonbyte/disaster-response-project","commit_stats":null,"previous_names":["pythonbyte/disaster-response-project"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pythonbyte%2Fdisaster-response-project","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pythonbyte%2Fdisaster-response-project/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pythonbyte%2Fdisaster-response-project/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pythonbyte%2Fdisaster-response-project/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pythonbyte","download_url":"https://codeload.github.com/pythonbyte/disaster-response-project/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":242017832,"owners_count":20058504,"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":[],"created_at":"2024-11-15T12:25:48.630Z","updated_at":"2025-12-02T15:11:38.732Z","avatar_url":"https://github.com/pythonbyte.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Disaster Response Pipeline Project\n\n### Table of Contents\n\n1. [Installation](#installation)\n2. [Instructions](#instruction)\n3. [Project Steps and Motivation](#steps)\n4. [Data](#data)\n5. [Results](#results)\n6. [Licensing, Authors, and Acknowledgements](#licensing)\n\n\n## Installation \u003ca name=\"installation\"\u003e\u003c/a\u003e\n\nFor this project make sure that you have the Poetry library installed so everything works as expected.\n\nIf you don't have it just use this command:\n\n`pip install poetry`\n\nAfter installing poetry you just need to use this command to install the necessary libraries for the project:\n\n`poetry install`\n\nThese are the libraries used for this project:\n\n* python = \"^3.7.9\"\n* Flask = \"^2.0.2\"\n* nltk = \"^3.6.4\"\n* pandas = \"^1.3.3\"\n* plotly = \"^5.3.1\"\n* scikit-learn = \"^1.0\"\n* SQLAlchemy = \"^1.4.25\"\n\n\n### Instructions \u003ca name=\"instruction\"\u003e\u003c/a\u003e\n1. Run the following commands in the project's root directory to set up your database and model.\n\n    - To run ETL pipeline that cleans data and stores in database\n        `python data/process_data.py data/disaster_messages.csv data/disaster_categories.csv data/DisasterResponse.db`\n    - To run ML pipeline that trains classifier and saves\n        `python models/train_classifier.py data/DisasterResponse.db models/classifier.pkl`\n\n2. Run the following command in the root directory to run your web app.\n    `cd app/ \u0026\u0026 python run.py`\n\n3. Go to http://0.0.0.0:3001/\n\n4. Try to enter messages such as \"We need food and shelter\" and click on Classify Message to understand and what category the message will be classified.\n\n### Project Steps and Motivation \u003ca name=\"steps\"\u003e\u003c/a\u003e\n\nThis is a project focused on classifying tweets that are labeled according to real world disasters. Beyond that it has a real-time classifier for those that want to test messages.\n\nThis project consists of three steps:\n\n1. ETL Pipeline\n2. ML Pipeline\n3. Run Web Application\n\nThe ETL pipeline will process the .csv files and save the processes data into a database.\nThe ML pipline will connect to the sqlite database created on the previous step and run a Pipeline with transformers and a classifier to create the pickle file for the trained model.\nThe Web Application will provide the interface to run the model trained on the ML pipeline step.\n\nWeb Application consists of:\n\n![input](img/DisasterHome.png)\nFigure 1. Web Application Home page with Input field\n\n![most used](img/most_used_words.png)\nFigure 2. Distribution of the most used words on the dataset\n\n![genre plot](img/genre_plot.png)\nFigure 3. Distribution of the message genres\n\n![categories plot](img/categories_plot.png)\nFigure 4. Distribution of the categories on the dataset\n\n![result](img/result_page.png)\nFigure 5. Result of a query into the input field. \"We need food and shelter\"\n\n\n\n## Data \u003ca name=\"data\"\u003e\u003c/a\u003e\n\nThe data for this project was provided by Figure8 in partnership with Udacity. And is a compiled of Tweets and its categories from real world disasters.\n\n\n\n## Licensing, Authors, Acknowledgements\u003ca name=\"licensing\"\u003e\u003c/a\u003e\n\nFigure Eight provided the dataset and the challenge for this project.\nUdacity for the course project.\nIf you want to chat about this analysis or other approaches you can find me on [Twitter](https://twitter.com/python_byte).\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpythonbyte%2Fdisaster-response-project","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpythonbyte%2Fdisaster-response-project","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpythonbyte%2Fdisaster-response-project/lists"}