Official Belgian data, explained
Tertiary education among known 25+ by municipality in Belgium (2017)
This page maps Tertiary education among known 25+ for one nationally comparable 2017 slice. Every figure below uses the same disclosed definition, unit, geography and source.
Education
What this indicator measures
Tertiary education among known 25+
Indicator dossier
Data passport
- Selected reference period
- 2017
- Geography
- municipalities
- Boundary set
- Statistical sectors 2011-2017
- Measure
- Tertiary education among known 25+
- Unit
- %
- Comparable areas
- 589
- Coverage
- 100%
Latest published slice
How to read the pattern
- Median
- 30.5%
- Unweighted area mean
- 31.8%
- Minimum
- 11.7%
- Maximum
- 60.7%
Across the valid national comparison set, the median is 30.5 %. Values extend from 11.7 to 60.7 %. This describes geographic variation; it is not a score of local quality.
Geography
Map of Belgium

- 11.7–25.5119 areas
- 25.5–28.9117 areas
- 28.9–32.2115 areas
- 32.2–37.5121 areas
- 37.5–60.7117 areas
Areas
Value distribution
| Value | Areas |
|---|---|
| 11.7–13.9 | 1 |
| 13.9–16.1 | 2 |
| 16.1–18.4 | 13 |
| 18.4–20.6 | 16 |
| 20.6–22.8 | 28 |
| 22.8–25.1 | 45 |
| 25.1–27.3 | 75 |
| 27.3–29.5 | 78 |
| 29.5–31.7 | 75 |
| 31.7–34 | 67 |
| 34–36.2 | 45 |
| 36.2–38.4 | 41 |
| 38.4–40.6 | 24 |
| 40.6–42.9 | 24 |
| 42.9–45.1 | 13 |
| 45.1–47.3 | 10 |
| 47.3–49.6 | 6 |
| 49.6–51.8 | 4 |
| 51.8–54 | 10 |
| 54–56.2 | 5 |
| 56.2–58.5 | 6 |
| 58.5–60.7 | 1 |
Explore this exact slice in the atlas Download this data as CSV
municipalities
Highest and lowest values
From 589 comparable areas, the table shows a concise descriptive high-and-low sample. Equal values do not imply equal local circumstances.
| Highest | 1 | Woluwe-Saint-Pierre | 21019 | 60.7 % |
|---|---|---|---|---|
| Highest | 2 | Wezembeek-Oppem | 23103 | 58.4 % |
| Highest | 3 | Kraainem | 23099 | 58.2 % |
| Highest | 4 | Lasne | 25119 | 57.5 % |
| Highest | 5 | Leuven | 24062 | 57.4 % |
| Highest | 6 | Sint-Martens-Latem | 44064 | 56.7 % |
| Highest | 7 | Oud-Heverlee | 24086 | 56.3 % |
| Highest | 8 | Ottignies-Louvain-la-Neuve | 25121 | 55.2 % |
| Highest | 9 | De Pinte | 44012 | 54.5 % |
| Highest | 10 | Ixelles | 21009 | 54.3 % |
| Lowest | 589 | Farciennes | 52018 | 11.7 % |
| Lowest | 588 | Châtelet | 52012 | 15.2 % |
| Lowest | 587 | Hastière | 91142 | 15.5 % |
| Lowest | 586 | Mesen | 33016 | 16.2 % |
| Lowest | 585 | Colfontaine | 53082 | 16.3 % |
| Lowest | 584 | Saint-Nicolas (Liège) | 62093 | 16.4 % |
| Lowest | 583 | Quaregnon | 53065 | 16.8 % |
| Lowest | 582 | La Calamine | 63040 | 16.9 % |
| Lowest | 581 | Boussu | 53014 | 17.1 % |
| Lowest | 580 | Dison | 63020 | 17.6 % |
Method and limitations
Method and limitations
No missing value is imputed. Where colour classes are used, their breaks and colours come from the catalogue; source-declared suppression remains missing.
The area mean gives every published geographic area equal weight. It is not weighted by population, exposure or area size.
Education shares use only age-25+ LOW/MIDDLE/HIGH as the known denominator. UNK is excluded from attainment shares and exposed through the known-coverage KPI. District components are summed through explicit municipality districtCode and shares are recomputed after selection.
Statbel DataLab reference year 2017.
Read the methodologySources, licence and provenance
