Whisky Discography

Project #2 - Group 6

An in-depth analysis to the global whisky market using the Whisky Hunter API to source the answers to the following questions;

Where in the world has most highly rated whisky?
Which country has the most distilleries?
Is there a visible relationship between the number of whiskies produced by a distillery and their average ratings?
What are the top-rated distilleries in both the world, and within a specific country?

Assignment structure

Whisky_Discography
| 
|__ code/
|__ |__ app.py
|__ |__ whisky_data.ipynb
|__ |__ whisky_dist.db
|   |__ static/
|      |__ css/
|         |__ style.css
|      |__ image/
|         |__ alysha.png
|         |__ craig.jpg
|         |__ distilleries.PNG
|         |__ explore.PNG
|         |__ extract01.PNG
|         |__ extract02.PNG
|         |__ heriawan.jpg
|         |__ index.PNG
|         |__ matt.png
|         |__ ms2.jpg
|         |__ oban.jpg
|         |__ ourpicks.png
|         |__ sqlitedb01.PNG
|         |__ sqlitedb02.PNG
|         |__ statistics.PNG
|         |__ steph.jpg
|         |__ transform01.PNG
|         |__ transform02.PNG
|         |__ WD1.PNG
|         |__ WD2.PNG
|         |__ WD3.PNG
|         |__ WD4.PNG
|         |__ WD5.PNG
|         |__ WD6.PNG
|         |__ whisky01.png
|         |__ whisky02.png
|         |__ whisky03.png
|         |__ whisky04.png
|         |__ whisky05.png
|         |__ whisky06.png
|         |__ whisky07.png
|         |__ whisky08.png
|         |__ whisky09.png
|         |__ whisky10.png
|         |__ whisky11.png
|         |__ whisky12.png
|         |__ whisky13.png
|         |__ ym1.jpg
|      |__ js/
|         |__ app.js
|         |__ data.js
|         |__ explore.js
|      |__ scripts/
|         |__ world.js
|   |__ templates/
|      |__ about_us.html
|      |__ data.html
|      |__ explore.html
|      |__ index.html
|      |__ stats.html
|
|__ data/
|   |__ whisky_hunter_data.csv
|   |__ whisky_hunter_data.json
|
|__ Project Proposal/
|   |__ Project 2.docx
|   |__ Wireframe Toolkit.pptx
|
|__ .gitignore
|__ Presentation.pptx
|__ Procfile
|__ README.md
|__ requirements.txt
|

Usage

# Dependencies and Setup

## JUPYTER NOTEBOOK
* import pandas as pd
* import json
* from sqlalchemy import create_engine

## JAVASCRIPT
* <!-- install lodash -->
* <!-- https://www.newline.co/@morfsys/you-should-start-using-lodash-in-2020-and-heres-why--792500b0 -->
* <script src="https://cdn.jsdelivr.net/npm/lodash@4.17.15/lodash.min.js"></script>

## HTML
* <!DOCTYPE html>
* <html lang="en">
* <script src="https://cdn.jsdelivr.net/npm/bootstrap@5.0.2/dist/js/bootstrap.bundle.min.js" integrity="sha384-MrcW6ZMFYlzcLA8Nl+NtUVF0sA7MsXsP1UyJoMp4YLEuNSfAP+JcXn/tWtIaxVXM" crossorigin="anonymous"></script>

### HIGHCHARTS - MAP
* <script src="https://code.highcharts.com/maps/highmaps.js"></script>
* <script src="https://code.highcharts.com/maps/modules/data.js"></script>
* <script src="https://code.highcharts.com/maps/modules/exporting.js"></script>
* <script src="https://code.highcharts.com/maps/modules/offline-exporting.js"></script>
* <script src="https://code.highcharts.com/mapdata/custom/world.js"></script>

### STATISTICS - PLOTLY
* <script src="https://cdn.plot.ly/plotly-latest.min.js"></script>

### DISTILLERIES DATA TABLE - JQUERY & DATATABLES
* <script src="https://code.jquery.com/jquery-3.5.1.js"></script>
* <script src="https://cdnjs.cloudflare.com/ajax/libs/d3/5.5.0/d3.js"></script>
* <script src="https://cdn.datatables.net/1.10.25/js/jquery.dataTables.min.js"></script>

## HEROKU
* pip install gunicorn
* pip install flask
* pip install flask-sqlalchemy

Data Sources:

No	Source	Link
1	Public APIs Whisky Hunter	https://whiskyhunter.net/api/
2	Whisky Base	https://www.whiskybase.com/whiskies/distilleries

Datasets

No	Source	Link
1	whisky_hunter_data.csv	https://github.com/EpicTomatoSauce/Whisky_Discography/blob/main/data/whisky_hunter_data.csv
2	whisky_hunter_data.json	https://github.com/EpicTomatoSauce/Whisky_Discography/blob/main/data/whisky_hunter_data.json

Extract:

Using the Whisky Hunter API we fetched the json file from a Whisky Hunter API and extracted the Whisky distillery information from the Whisky Base distillery table.

Whisky Hunter

Whisky Base

Transform:

In jupyter notebook applying the pandas library we read in the files, transformed the data and created dataframes sorted in ascending order based on the top rated whiskies, top voted and top whiskies in the world in preparation for pushing to a data base.

Load - SQLite Database:

Using the dataframes created in the jupyter notebook we applied the df.to_SQL to push the tables to the SQLite Database to store the raw data.

Visualisations:

All visualisations were created and displayed on the html pages by using plotly, jquery and highchart via fetching the data from the Whisky Database raw_data, top_rated and the unique_countries tables.

Below is an overview of each html page for our Whisky Discography webpage;

Index

Statistics

Explore

Distilleries

Our Picks

Analysis:

After diving into the world of Whisky we noted the following observations from our dataset.

The highest rated whisky was in Italy, however it only had one vote. Perhaps its distiller was a bit biased?
United States had the most distilleries.
Scotland had the most reviewed distilleries.

Deployment to Heroku:

Our webpage has been successfully deployed in Heroku via the following Whisky Discography link.

Final Note:

The Whisky Discography website can be used by Whisky beginners to connoisseurs to find their next whisky to sample, plan their next Whisky road trip, gift a bottle of whisky or to simply enjoy.

helenamin/Whisky_Discography