Red-Wine-Quality-Analysis

Basic descriptive and predictive analysis of Red wine quality data using Python.

Welcome, and thank you for opening this Project. This project contains a jupyter notebook which will provide knowledge to novice Data Scientists with basic Data Analysis/Machine Learning concepts like:

• Data Extraction

• Downloading a publicly available dataset
• Describing the dataset
• Describing the research question

• Data Pre-processing

• Cleaning/removing invalid values from rows
• Cleaning up columns
• Removing/filling missing data
• Creating new columns
• Modifying exsting columns

• Data Visualization
• Data Exploratory Analysis
• Descriptive Analytics
• Prediction and Model Selection
• Classification
• Deriving Conclusion/Insights from the data

Dataset:

Name: Red Wine Quality Data Set
Source: UCI Machine Learning Repository
Input variables:

• fixed acidity
• volatile acidity
• citric acid
• residual sugar
• chlorides
• free sulfur dioxide
• total sulfur dioxide
• density
• pH
• sulphates
• alcohol
  

Output variable: quality (score between 0 and 10)
Data Set Characteristics: Multivariate
Number of Observations: 1599
Number of Attributes/Variables: 12
Missing Values: N/A

Kaggle Link for the Notebook and Data: Red Wine Data Analysis: Descriptive & Predictive