Project #4: Frequency Distribution on FMCG

I believe that one of the most data-rich industries in today's world is Fast Moving Consumer Goods or FMCG. Endless commodities with variegated categories are currently available in the market. Among the numerous products barraging our grocery options these days is the variety of cereals.

For this exercise, I was tasked to examine 77 cereal brands currently available in the market. Further, I had to probe into the nutritional content of these brands as consumers are more health-conscious in this particular grocery store, according to recent market research.

Focusing on the numerical variables, I generated individual histogram for each of these. I was able to conclude that the variables with the top 3 largest variability are Calories, Carbohydrates, and Sugars. These identified nutritional contents prove to have less consistent amounts compared to other variables. As a premature conclusion, the grocery store has sufficient offerings of brands that serve different consumer categories (ie. sugar-rich and non-sugar consumers and calorie-counting customers).

In-depth analysis can be further performed on the given cereals dataset. However, looking into the frequency distribution of the numerical variables serves as a fundamental step in moving on with the entire analytical process.