How tandah-marcelle/africa-population-pulse-streamlit-analytical-dashboard works
Africa Population Pulse is a Streamlit dashboard for exploring African population trends. Users select regions, countries, and a year range; the app filters the prepared dataset, then presents KPIs and temporal, geographic, correlation, and regional-distribution analyses. The README also describes a World Bank ETL process that produces the cleaned CSV, but no ETL implementation is present in the tree. Dashboard behavior is sampled from app.py; chart nodes below represent its distinct analytical views.
Main entry points: app.py Streamlit Dashboard · africa_population_cleaned.csv Cleaned Population Data
Components 10
Population Data
- Cleaned Population Data
africa_population_cleaned.csv - Filtered Population Data
app.py
Dashboard Interaction
- Streamlit Dashboard
app.py - Region, Country, Year Filters
app.py
Analytical Views
- Population KPIs
app.py - Temporal Trends
app.py - Geographic Choropleth
app.py - Correlation Matrix
app.py - Regional Distribution
app.py
Other components
- Dashboard User
Connections 15
- Dashboard User → Streamlit Dashboard: uses
- Streamlit Dashboard → Cleaned Population Data: loads CSV
- Streamlit Dashboard → Region, Country, Year Filters: renders
- Region, Country, Year Filters → Filtered Population Data: filters
- Cleaned Population Data → Filtered Population Data: supplies rows
- Streamlit Dashboard → Population KPIs: calculates
- Filtered Population Data → Population KPIs: provides data
- Streamlit Dashboard → Temporal Trends: builds chart
- Filtered Population Data → Temporal Trends: provides data
- Streamlit Dashboard → Geographic Choropleth: builds map
- Filtered Population Data → Geographic Choropleth: provides data
- Streamlit Dashboard → Correlation Matrix: computes matrix
- Filtered Population Data → Correlation Matrix: provides data
- Streamlit Dashboard → Regional Distribution: builds boxplot
- Filtered Population Data → Regional Distribution: provides data