Project 2
Wine Quality Analysis Project
Introduction
This project aims to analyze and compare the characteristics and quality ratings of red and white wines. By leveraging a dataset containing various chemical properties and quality ratings of wines, we intend to explore multiple aspects such as the influence of alcohol content on quality, the correlation between citric acid and pH levels, and the impact of acidity levels on wine quality. This analysis not only provides insights into the factors affecting wine quality but also highlights statistical methods and data processing techniques.
1.Display the data of white wine and red wine
2.Get the size of both white wine and red wine.
3.Get the number of null in both type of wines
4.Check for duplicates and remove them in both type of wine data
5.Get the number of uniques values in all Feature and print them
6.Print the mean density of both the sets
7.Combine both the datasets with color of the wine in column
8.Remove the null values if any
9.Remove the outliers if any
10.Do wines with higher alcohol content receive better ratings?
11.Find correlation between citric acid content and PH.
12.Find regression of PH on citric acid
13.Find how many variables are independent.
14.Create a new column as the acidity level. Divide the existing data into 5 groups based on the acidity level. The levels are to be named ['High', 'Moderately_High', 'Medium', 'Low']. Acidity may be obtained from the PH.
15.Find the mean quality of each acidity level with groupby. Use groupby
16.Is a certain type of wine (red or white) associated with higher quality?
17.Select samples with alcohol content less than the median
18.Get the quality rating for the low alcohol and high alcohol groups.
19.Do sweeter wines get more ratings?
20.Get the number of counts based on ratings and color of wine.
21.Is the density of red wine and white wine similar?
22.Is the confidence interval for the differences of the proportion of white wine with rating 3 and the proportion of red wine with rating 3.
Conclusion
we explored the characteristics and quality ratings of red and white wines. We found correlations between various chemical properties and quality ratings, determined how alcohol content and acidity levels impact wine quality, and compared the quality ratings of red and white wines. The insights obtained from this analysis can help winemakers focus on the key factors that enhance wine quality.