How kryp71cgh057/hdvs works
This repository is a Streamlit healthcare-insights dashboard with separate script-based analyses. The primary user workflow is to upload a CSV (or use a default dataset), clean and validate records, then choose dashboard analyses and inspect visualizations. The README highlights demographic, timeline, and treatment insights; sampled code also shows overview, medical-condition, and length-of-stay views. Several dashboard entry points overlap, so they are represented as distinct app variants. Edges are limited to relationships shown in excerpts or documented in the README; unsampled app wiring is not inferred.
Main entry points: app_2.py Dashboard app · healthcare_dataset.csv Healthcare CSV · Data_Clening.py CSV cleaning script · Demographic_Analysis.py Demographics
Components 16
Interactive dashboard
- Dashboard app
app_2.py - Styled dashboard
app.py - Extended dashboard
main.py - Backup dashboard
backup_app_2.py - Data validation
app_2.py
Analysis views
- Demographics
Demographic_Analysis.py - Timeline trends
Timeline_Analysis.py - Treatment patterns
Treatment_Analysis.py - Overview metrics
app_2.py - Condition analysis
app_2.py - Length of stay
app_2.py
Dataset preparation
- Healthcare CSV
healthcare_dataset.csv - Cleaned CSV
cleaned_healthcare_data.csv - CSV cleaning script
Data_Clening.py - Dataset inspection
analyze_healthcare_data.py
Other components
- Dashboard user
Connections 16
- Dashboard user → Dashboard app: uses
Readme.md - Dashboard user → Dashboard app: uploads CSV
Readme.md - Dashboard app → Data validation: validates and cleans
app_2.py - Dashboard app → Cleaned CSV: loads default
app_2.py - Dashboard app → Overview metrics: renders
app_2.py - Dashboard app → Demographics: renders view
Readme.md - Dashboard app → Timeline trends: renders view
Readme.md - Dashboard app → Treatment patterns: renders view
Readme.md - Dashboard app → Condition analysis: renders
app_2.py - Dashboard app → Length of stay: renders
app_2.py - Healthcare CSV → CSV cleaning script: reads
Data_Clening.py - CSV cleaning script → Cleaned CSV: writes
Data_Clening.py - Healthcare CSV → Dataset inspection: reads
analyze_healthcare_data.py - Healthcare CSV → Demographics: reads
Demographic_Analysis.py - Healthcare CSV → Timeline trends: reads
Timeline_Analysis.py - Healthcare CSV → Treatment patterns: reads
Treatment_Analysis.py