PyData-EDA/Investigating Factors Affecting Red Wine Quality

P4: Exploratory Data Analysis

In this project, exploratory data analysis is conducted to explore the variables, structure, patterns, oddities, and underlying relationships of factors that affect red wine quality.

When I worked on this project, it helped me learn a great deal about EDA i.e., to use plots to understand the distribution of a variable and to check for patterns and their relationships with other variables. Moreover, I learned to create a logical flow when building up from single-variable analysis to multivariate analysis.

Files

• wineQualityReds.csv – This dataset is publicly available for research in the UCI Machine Learning Repository.

• Red_Wine_Quality.rmd – Main RMD project file containing the analysis.

• Red_Wine_Quality.html – HTML file knitted from the project file.

• Red_Wine_Quality.R - R code extract (with documentation).

• References.txt – List of references.

Requirements

This project was developed using RStudio Version 1.0.153 – © 2009-2017 RStudio, Inc (R Version 3.4.2).

The required packages are ggplot2, gridExtra, GGally, ggthemes, dplyr, knitr and memisc.

License

Modified MIT License © Pranav Suri