Data Analysis Project

Summary

This project demonstrates the socioeconomic status and fast food consumption for obesity rate by states of US and analyzes its impact on the obesity rate. The analysis is visualized using Tableau. In order to analyze this, we use the adult obesity rate, youth obesity rate, average household income, education attainment (bachelor’s degree attainment) rate and the pizza consumption data. By using Tableau, we visualized our analysis and demonstrated it using graphs and maps. After that, we built a linear regression model to explore the correlation between obesity rate and other factors. We started the project with an assumption that obesity rates would vary based on socioeconomic status and fast food consumption. Another assumption is that the fast food consumption may have a different influence on adults and youth. Through different processes that start with downloading datasets and ends with visualization, we were able to provide sufficient examples that prove the assumption.

Role

Setting a Goal, Gathering adult obesity rate/youth obesity rate/average household income/education attainment data, Creating database designs, Applying VLookup function to arrange data file, Uploading CSV file to a server, Building Python scripts to make relationships among obesity rate, education rate, and pizza consumption, Building a linear regression model, Writing a final report

Contents

Figure 2.1.4 Education Attainment by State and Age Range

Figure 2.1.5.5 Pizzerias Per Capua Ranked by State (2012)

Figure 2.1.5.2 Pizzerias Per Capua Ranked by State (2015)

Figure 3.2.2 Python Codes Splitting Year Range

Figure 4.3.1 Sample Tables

Figure 5.6.1 Structure of youth_nonregular_exercises Table

Figure 8.1 Average Adult Rae by State and Region in Tableau

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