Belgiumin Maps

Official Belgian data, explained

Low education among known 25+ by municipality in Belgium (2017)

This page maps Low 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

Low education among known 25+

Low education among known 25+. Low education among known 25+

Indicator dossier

Data passport

Selected reference period
2017
Geography
municipalities
Measure
Low education among known 25+
Unit
%
Comparable areas
589
Coverage
100%

Latest published slice

How to read the pattern

Median
35.6%
Unweighted area mean
35.4%
Minimum
16.2%
Maximum
55.2%

Across the valid national comparison set, the median is 35.6 %. Values extend from 16.2 to 55.2 %. This describes geographic variation; it is not a score of local quality.

Geography

Map of Belgium

Low education among known 25+, 2017. Exact official boundaries; missing values remain neutral.
  1. 16.2–30.3120 areas
  2. 30.3–34.1115 areas
  3. 34.1–37118 areas
  4. 37–40.6117 areas
  5. 40.6–55.2119 areas
Low education among known 25+, 2017. Exact official boundaries; missing values remain neutral.

Categories

Distribution by official map class

Distribution by official map classOne bar per catalogue-owned map class. The x-axis is the indicator value range; bar height is the number of areas.12016.2–30.311530.3–34.111834.1–3711737–40.611940.6–55.2LowerHigher
One bar per catalogue-owned map class. The x-axis is the indicator value range; bar height is the number of areas.
ValueAreasCategories
16.2–30.3120
30.3–34.1115
34.1–37118
37–40.6117
40.6–55.2119

Explore this exact slice in the atlas

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 and lowest values
Position#AreaOfficial codeValue
Highest1Farciennes5201855.2 %
Highest2La Calamine6304053.9 %
Highest3Butgenbach6301353.7 %
Highest4Bullange6301252.6 %
Highest5Burg-Reuland6308752 %
Highest6Amblève6300151.3 %
Highest7Saint-Josse-ten-Noode2101451.1 %
Highest8Dison6302051 %
Highest9Châtelet5201251 %
Highest10Comines-Warneton5401050.9 %
Lowest589Woluwe-Saint-Pierre2101916.2 %
Lowest588Lasne2511916.4 %
Lowest587Sint-Martens-Latem4406417.9 %
Lowest586Wezembeek-Oppem2310318.3 %
Lowest585Kraainem2309918.4 %
Lowest584Hove (Antwerpen)1102118.6 %
Lowest583Oud-Heverlee2408619.2 %
Lowest582De Pinte4401219.6 %
Lowest581Chaumont-Gistoux2501819.9 %
Lowest580Leuven2406220 %

Method and limitations

Method and limitations

No missing value is imputed. Classification breaks and colours come from the catalogue, and 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 methodology

Sources, licence and provenance

Sources, licence and provenance

Sources, licence and provenance