Udacity Data Visualization Nanodegree Capstone Project

https://vulcanotec.com/en/news/cereal-is-the-breakfast-food-of-our-childhoods-and-yes-of-our-future/

This story is the capstone project of Udacity Data Visualization Nanodegree. Its main goal is to describe how I’ve improved an existing data visualization from Makeover Monday by combining what I’ve learned throughout the program.

Step 1: Scope the Project and Gather Data

Consequently, the first task was to choose an existing dataset. As I was always very interested in economic fields, so I checked datasets used for MakeoverMonday data then I chosen the Personal Consumption Expenditures on Food and beverages purchased for off-premises consumption.

The original data visualization is here; the dataset with all background information and data dictionary is here.

Step 2: Explore and Assess the Data

The main variable/categories in the original dataset are:

• Alcoholic beverages
• Cereals and bakery products
• Fats and oils
• Coffee, tea, and other beverage materials
• Fish and seafood
• Fresh fruits and vegetables
• Meats and poultry
• Sugar and sweets
• Milk, dairy products, and eggs
• Mineral waters, soft drinks, and vegetable juices
• Processed fruits and vegetables

Under these main categories, there are many sub-categories:

• Beer
• Spirits
• Wine
• Bakery products
• Cereals
• Fats and oils
• Fish and seafood
• Fruit (fresh)
• Vegetables (fresh)
• Beef and veal
• Other meats
• Pork
• Poultry
• Eggs
• Fresh milk
• Processed dairy products
• Processed fruits and vegetables
• Sugar and sweets
• Coffee, tea, and other beverage materials
• Mineral waters, soft drinks, and vegetable juices

So we have 14901 combinations of all these parameters. Each of them is the dataset record that can be interpreted as follows: In January 1959 there are 3457 million dollars consumed on beer which is part of Alcoholic beverages.

The main goal of this step is to identify any limitations and biases in data collection, processing, and insights.

What is well with the initial visualization?

1. Data source is mentioned
2. The title is simple and clear so that everyone can understand

What could be improved with the initial visualization?

1. Compare the cereal with other categories.
2. Expenditures per category over years.
3. Expenditures per category in covid 19 period.

Pre-processing done on household income dataset:

1. Downloaded datset (Excel file) here.
2. Created Tableau file
3. create many sheets as follow:

a) Growth Rate to compare the cereal Vs other categories here

b) Growth Rate to compare the cereal Vs other categories by shown that the difference in millions of dolras. here

c) Pie char illustrate the expenditures per category in covid 19 period. here

d) dashboard the combine the charts. here

Thank you for reading.