Disaster Response Pipeline Project

Classify Disaster Response Messages

Udacity Data Scientist Nanodegree Project

Project Motivation

This project analyzes social networking site messages collected after natural disasters. Its major goal is to build up data processing and classification pipeline to facilitate resource allocation process.

Installation

Initial Setup

1. Install Anaconda if you have not installed it. Otherwise, skip this step.

2. Update Anaconda by typing conda update -all in Anaconda Prompt.

3. Clone this repository to your local machine using:

   $ git clone https://github.com/YueminLi/Disaster_Response_Pipeline.git

4. Delete these two files:

   data/DisasterResponse.db and models/classifier.pkl

Running Steps

1. Run the followihng 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/

File Descriptions

• 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, from Figure Eight
  • disaster_messages.csv: data to process, from Figure Eight
  • process_data.py: process text data
  • DisasterResponse.db: database to save clean data to

• models

  • train_classifier.py: train machine learning models
  • classifier.pkl: saved model

• LICENSE

• README.md

Author

Yuemin Li

Github: https://github.com/YueminLi

LinkedIn: https://www.linkedin.com/in/yuemin-li-89166333/

License

Usage is provided under the MIT License. See LICENSE for the full details.