Disaster Response Pipeline Project

Project Overview

This project develops a data pipeline to analyze a dataset containing real messages that were sent during disaster events and build a model for an API that classifies messages. The project includes a web app where an emergency worker can input a new message and get classification results in several categories. The web app also display visualizations of the data.

Instructions:

1. Run the following commands in the project's root directory to set up your database and model.

   • To run ETL pipeline that cleans data and stores in database python data/process_data.py data/disaster_messages.csv data/disaster_categories.csv data/DisasterResponse.db
   • To run ML pipeline that trains classifier and saves python models/train_classifier.py data/DisasterResponse.db models/classifier.pkl

2. Run the following command in the app's directory to run your web app. python run.py

3. Go to http://0.0.0.0:3001/

Project Files

Here's the file structure of the project:

- app
| - template
| |- master.html  # main page of web app
| |- go.html  # classification result page of web app
|- run.py  # Flask file that runs app

- data
|- disaster_categories.csv  # data to process 
|- disaster_messages.csv  # data to process
|- process_data.py
|- DisasterResponse.db   # database to save clean data to

- models
|- train_classifier.py
|- classifier.pkl  # saved model 

- README.md