u/Economy-Concert-641

Dataset: 2,000 records from a Kaggle mental health survey.

Main finding: symptoms don’t appear in isolation. Stress acts as a cluster trigger.

•	65.8% of high-stress individuals also report anxiety (vs. 40.6% in the low-stress group)

•	62.8% of the high-stress group reports burnout

•	Young employed people show the highest stress rate: 49.3%

The implication is that interventions targeting single factors (sleep, routine) likely have diminishing returns if the underlying symptom accumulation isn’t addressed as a whole.

Notebook + figures on GitHub: https://github.com/matheusmarquezinhub/mental-health-kaggle

Open to feedback on methodology and visualization.

Hey r/datascience,

I’ve been building my data portfolio and just wrapped up an EDA project on mental health using a Kaggle dataset with 2,000 records.

The finding that surprised me most: mental health risk isn’t driven by single factors — it’s driven by overlap.

A few numbers that stuck with me:

•	65.8% of high-stress individuals also have anxiety (vs. 40.6% in the low-stress group)

•	62.8% of that same group reports burnout

•	Young employed people hit 49.3% high-stress rate — the highest of any group

The real insight is that stress acts more like a cluster trigger than an isolated symptom. Treating sleep or routine in isolation probably won’t move the needle much if the underlying accumulation isn’t addressed.

GitHub: https://github.com/matheusmarquezinhub/mental-health-kaggle