Web application

World Bank Data Dashboard of top 10 World Economies. Created a web-application hosted on Heroku that extracts, transforms and load data into a Dashboard.

https://example-worldbank-app.herokuapp.com/

Contents

The repository contains an example of a web application installed on Heroku

Libraries

• flask
• pandas
• plotly
• gunicorn

Heroku installation (in case interested to install it yourself from scratch)

Before doing the steps create a free account to Heroku.

1. Update conda and create a virtual environment (in case Anaconda installed, if not, skip that step)

conda update python

python3 -m venv worldbankvenv

source worldbankenv/bin/activate

2. Install the necessary libraries

pip install flask pandas plotly gunicorn

3. Go to the app folder

cd "app folder"

4. Install heroku

curl https://cli-assets.heroku.com/install-ubuntu.sh | sh https://devcenter.heroku.com/articles/heroku-cli#standalone-installation

5. Check verison to confirm installation.

heroku --version

6. Login to heroku (it should open your browser, click ok)

heroku login

7. Create Procfile

touch Procfile

8. Write the below in the Procfile

web gunicorn myapp:app

9. Create requirements file (be carefull as errors appear if python/numpy/pandas versions are not supported)

pip freeze > requirements.txt

10. Add initialize repository and commit

git init

git add .

git commit -m ‘first commit’

11. Create app in heroku

heroku create my-app-name

12. Check if remote repository was added

git remote -v

13. Push to remote repository

git push heroku master

Acknowledgements

This web-app is part of Udacity Data Science Nanodegree program. Code templates and data were provided by Udacity.