CS5010-Final-Project

Final project for CS 5010: Python for Data Analysis Bev Dobrenz (bgd5de), Joseph Wysocki (jw6mw), Amanda West (acw9gs), Nikki Aaron (na5zn)

• Paper: 1. Write-Up
• Powerpoint: 2. Powerpoint Slides

File List

Original dataset: winemag-data-130k-v2.csv Original grape Variety list (Wikipedia): grape_list.csv

Data Processing

Step 1: Parsing the grape list

• Parser script: grape_list_parser.py
• Output: grape_list_parsed.csv
• Unit test: grape_list_parser_test.py

Step 2: Match wines with wine type (Red, White, Rosé, Sparkling, Blend)

• Matching script: grape_id.py
• Unit test: grape_id_test.py
• Output: wine.csv

Step 3: Add Flavor Profile Tags

• NLP Practice: Text_Mining_Suite.ipynb
• Definitions: 3. NLP Definitions.pdf
• Test with One Paragraph Box: Desc_Test_1_Box.ipynb
• Original Categorizer Script: Add_Categories.ipynb
• Chunked Processing Categorizer Script: Add_Categories.py
• Output: wine2.csv

Step 4: Wine Recommender Terminal Application

• Application Script: filters.py
• Sample Output: recommendations.txt

Step 5: Tableau Dashboard

• Dashboard: https://public.tableau.com/profile/b.dobrenz#!/vizhome/CS5010FinalProject-AnalysisofWineEnthusiastReviews/WineVarietyEDA