Project 9: Depressive Symptom Trends in the U.S. During COVID-19

This project analyzes survey-based estimates of depressive symptoms in the United States using the dataset: "Symptoms of Depressive Disorder Based on Reported Frequency of Symptoms During Last 7 Days."

Project goals

1. Explore how depressive symptom prevalence varies by state.
2. Compare prevalence across age groups and sex categories.
3. Summarize national trends over time.

Key observations

• National prevalence rose from 23.5% in early 2020 to 33.5% in the latest period, with a peak of 42.6%.
• States show noticeable variation, with higher averages in places like Louisiana and Mississippi and lower averages in states like South Dakota and Minnesota.
• The 18–29 age group has the highest average reported prevalence.
• Female respondents have a higher average reported prevalence than male respondents.

Repository structure

.
├── Project9.ipynb                    # Original notebook
├── src/
│   └── analyze.py                    # Scripted analysis pipeline
├── outputs/
│   ├── state_rankings.csv            # State-level averages
│   ├── age_rankings.csv              # Age-group averages
│   └── sex_rankings.csv              # Sex-based averages
├── reports/
│   └── portfolio_report.md             # Generated summary report
└── README.md

How to run

python src/analyze.py

Data source

U.S. Census / NCHS Household Pulse Survey indicator dataset (included in this repository as CSV).