This repository contains code for my talk at PyData Delhi Meetup #23.
Pranav Suri c51414ca9b Update README.md | 6 tahun lalu | |
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Identifying Fraud from Enron Email Dataset | 6 tahun lalu | |
Investigating Factors Affecting Red Wine Quality | 6 tahun lalu | |
.gitattributes | 6 tahun lalu | |
License.txt | 6 tahun lalu | |
Presenting.jpg | 6 tahun lalu | |
README.md | 6 tahun lalu |
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.