tommygiang.com
June 2023 - Creating a URL Shortener Using Python and FastAPI
This project allowed me to explore an intermediate-level Python project that was outside my usual comfort zone of Data Analytics. It's a API-driven web app that allows users to input URLs (typically long ones), and the web app will generate a unique shortened URL to share with other people.
I was able to familiarize myself with modeling SQLite databases and setting up a localized Uvicorn server. I've always wondered how those worked. Thankfully the programmers behind the Uvicorn package have made it easy to set up.
May 2023 - Financial Analysis of the Top 50 Fast Food Chains Using Python and Tableau
I came across this article when researching projects to add to my resume.Â
It summarized 6 key financial concepts (U.S. systemwide sales, Average Sales per Unit, Number of Franchised Stores and Company Stores, Total Units, and Change of Units Since the Previous Year) from the Top 50 Fast Food chains in the U.S.
This calls for a webscrapping project. I used the Python and its packages BeautifulSoup and Pandas to scrap the data from the article. You can read the code on my Github here
Then, it was time to visualize it. I used Tableau Public and you can find it publicly published here.
April 2023 - Visualizing Citibike Trips with Tableau
Combined all the Data Visualizations into a Interactive Dashboard via Tableau Public. You can check it out by clicking the image!
November 2021 - Using Linear Regression in Microsoft Excel
By taking advantage of Congressional Budget Office (CBO)'s Budget and Economic Data, we were looking for relationships between variables in 3 sectors: Labor, Business, and Government.
In the Labor sector, we found that (with a very small p-value) an increase in an employee's wages is correlated with an increase in the nation's gross domestic product (GDP). Cheers to the workers!
In the Business sector, we tried a Multiple Regression on the Top 50 Companies and wanted to see if a company's {Revenue, Revenue Change, Profit, Profit Change, and Employee Size} will affect the company's {Asset Value}. With all those variables, we were not able to find evidence for our intended conclusion, BUT a subset of variables were great predictors. In particular, a company's Revenue, Profit, and Employee Size are related to an increase in a company's Assets. At least in the Top 50 company's case...
In the Government sector, we were 99% confident that an increase in Individual Increased Tax Revenue is correlated with an increase in the Corporate Income Tax Revenue for the Federal Government.
June 2019 - My Introduction to Data Visualization at Cal Poly's Frost Research Program
A simple bar graph made in Google Sheets. Data Analytics doesn't have to be complicated.