Distribution of pH levels of the red wine

Introduction:
In this particular research data analysis techniques are used to find information of chemical
properties of red wine and how those properties express the quality of the red wine is
attempted to be explored. Red wine is one of the most popular wine which is consumed by a
large proportion of people around the world. Sometimes it is also prescribed by doctors to take
red wine in day for a suitable proportion as it helps to maintain good heart health, prevents
brain damage after stroke, prevents breast and colon cancer and has many more health
benefits. Thus in this research a specific red wine sample is collected from UCI machine
learning website that was originally collected from the brand Vinho Verde in the north side of
Portugal and then important findings about red wine is explored by means of data analysis.

Dataset information
The dataset contains a total of 12 attributes with 1599 instances with no missing values as given by the
following variable names.
1. fixed acidity
2. volatile acidity
3. citric acid
4. residual sugar
5. chlorides
6. free sulphur dioxide
7. total sulphur dioxide
8. density
9. pH
10.sulphates
11.alcohol
12.quality (score between 0 and 10)
All the attributes have real values obtained by physiochemical testing of the red wines as done by Cortez and
others. A detail description of the variables can be found in UCI website (Archive.ics.uci.edu. 2020).

Research questions
The research questions are formed to understand the
distribution of selective attributes of red wines as given
below.
1) Distribution of quality scores of the red wine sample
2) Distribution of pH levels of the red wine sample
3) Distribution of alcohol in red wine sample
4) Distribution of sulphates in red wine sample

Research questions
In addition to the research questions relating to
distribution of different attributes of wine, further, two
research questions are formed as
1) Relationship between fixed acidity percentage and the
pH value of the red wines
2) Significant factors or variables that express wine
quality.