This repository contains the supplementary material to my talk delivered at PyData Delhi MeetUp #23.
The idea behind the talk was to explain the ideology behind Exploratory Data Analysis and why it is essential for any Data Science project.
The talk included a lot of content from the following projects:
Investigating Factors Affecting Wine Quality: This project investigates a dataset using EDA to find chemical properties that affect red wine quality. You can follow this project on my blog as well.
Identifying Fraud from Enron Email Dataset: This project includes a section which uses EDA to remove outliers.
The meet-up was a great experience as I met some amazing people. I certainly look forward to collaborating on new projects. One of the ideas I have is to explore datasets on different beverages (such as white wine) or maybe some food items.