Where South Asia Is Most Urban
Make this example your own
Start with this working configuration
Keep the geography and setup, then replace the values or adjust the styling.
- Map
- Choropleth map
- Geography
- South Asia (SAARC)
- Dataset
- 8 mapped places · Numeric values
- Rendering
- Quantile color classes
Includes: map/table toggle · 3 summary stats · map labels
Data you need
- A place or boundary identifier that matches South Asia (SAARC).
- A comparable rate, percentage, category, or normalized value for each area.
- A meaningful color direction or midpoint that matches the subject of the data.
- A title, units, source, and short note explaining definitions or limitations.
How to make a similar map
- Prepare one row per mapped place and match it to South Asia (SAARC); use stable geographic codes when available.
- Upload the CSV and confirm the location and value fields in Data check. Remove duplicates or unmatched rows before continuing.
- Choose a choropleth and start with the quantile color treatment; adjust the palette only if its direction supports the meaning of the values.
- Add labels, stat cards, and source notes only where they aid interpretation. Use the map/table toggle when both views matter but space is limited.
Try this map style with
These datasets can use the same geography and visual setup.
- Access to electricity across SAARC countries
- Population growth by country
- Internet use or school enrollment rates
Source and limitations
World Bank, World Development Indicators: Urban population (% of total population), 2024.
World Bank and UN Population Division estimates rounded to whole percentages. National definitions of urban areas differ, so comparisons require care.