/disaster-response-pipeline

Primary LanguageJupyter Notebook

Disaster Response Pipeline Project

Introduction

This tool designed to assist individuals and organizations during disaster events. The primary goal is to provide a practical solution that have a real-world impact, making a difference in times of crisis.

Files in the Repository

  • app/: Directory containing the web app files.

    • template/: Directory containing the HTML templates for the web app.
      • master.html: Main page of the web app.
      • go.html: Classification result page of the web app.
    • run.py: Flask file that runs the app.

  • data/: Directory containing the data files and processing scripts.

    • disaster_categories.csv: Data to process.
    • disaster_messages.csv: Data to process.
    • process_data.py: Script for processing the data.
    • DisasterResponse.db: Database to save clean data to.

  • models/: Directory containing the model training script and saved model.

    • train_classifier.py: Script for training the classifier.
    • classifier.pkl: Saved model.

  • README.md: Documentation for the project.

  • requirements.txt: List of Python packages required for this project.

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. Go to app directory: cd app

  3. Run your web app: python run.py

  4. Click the PREVIEW button to open the homepage