Jupyter Notebooks

Interactive data science notebooks showcasing analysis, cleaning, and visualization techniques. Explore the code, outputs, and methodologies behind my data projects.

Census Poverty: Data Acquisition

Data Acquisition

Data acquisition and collection from U.S. Census Bureau APIs for poverty analysis, including demographic and economic indicators.

Census Poverty: Data Pre-Processing

Data Cleaning

Data preprocessing and transformation of census poverty data, including feature engineering and data quality assessment.

Census Poverty: Data Visualization & Exploration

Data Analysis

Exploratory data analysis and visualization of U.S. census poverty data, revealing geographic and demographic patterns.

Chronic Drug Analysis: CDC PLACES Health Data Cleaning

Data Cleaning

Data cleaning and preprocessing of CDC PLACES health outcomes data for chronic conditions analysis.

Chronic Drug Analysis: CMS Medicare Part D Data Cleaning

Data Cleaning

Comprehensive data cleaning and preprocessing of Medicare prescription drug data from CMS.

Chronic Drug Analysis: Conditions & Prescription Drugs Analysis

Data Analysis

Statistical analysis exploring relationships between chronic health conditions and prescription drug usage patterns using Medicare and CDC data.

Interested in the full projects?

These notebooks are part of larger data science projects. Check out my complete demos and applications for the full experience.

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