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ericfayhuynh/README.md

🤗Welcome to my GitHub Portfolio!

🙋‍♂️About

Welcome to my portfolio! Here, I am excited to showcase the skills and knowledge I have acquired so far in the data field, with a lot more to come. As a passionate learner, I have delved into various tools like SQL, Python, and R, which have enabled me to work on intriguing data projects. This portfolio serves as a testament to my journey in data analytics and the application of these tools to real-world scenarios.

A little about me: My name is Eric, and I currently reside in the greater Los Angeles area. I am making a career change from biology to pursue my passion for data science and biostatistics. Currently enrolled in the University of Berkeley Data Analytics Bootcamp, I am eager to explore the many opportunities and challenges that the data field has to offer. I view data analytics as a perfect stepping stone into a fulfilling career, where I can foster a learning culture, encourage optimization, and continuously upskill.

Feel free to explore my GitHub portfolio! I am excited to showcase the skills I have acquired and the projects I have diligently worked on.

📁Overview

Languages/Data Tools I am familiar with:

  • Excel
    • Spreadsheet
    • PivotTable
    • Power Pivot
    • VBA (Visual Basic for Application)
  • Python
    • Pandas
    • API keys (Application Programming Interface)
    • Matplotlib
    • SQLalchemy
    • SQLite3
  • SQL (Structured Query Language)
    • MySQL
    • PostgreSQL
    • Microsoft SQL Server
  • Web Development
    • HTML (Hypertext Markup Language)
    • CSS (Cascading Style Sheets)
    • JavaScript (working on it)

Pinned

  1. EDA-Project EDA-Project Public

    EDA project on US public transportation: Analyzing ridership correlations with socio-economic factors like population density, GDP, education levels, and unemployment. Using Python for data analysis.

    Jupyter Notebook 1 1

  2. Shridhik/Crowdfunding_ETL Shridhik/Crowdfunding_ETL Public

    In this Crowdfunding ETL project, we used Python, Pandas, and regex to clean the Excel data file, enhance its quality, and then transform it into a usable CSV.

    Jupyter Notebook