Municipal statistics

More statistics and data analysis for a municipality or other administrative areas

Measure statistics

All municipalities at a glance, filtered by measures catalogue, type and federal state

Municipality clustering

Click a point for the cluster profile →

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Each municipality is described by its individual measure ratings (0 = barely/not, 1 = complete; N/A and missing ratings = 0). PCA reduces these high-dimensional vectors to two principal components (PC1/PC2), which explain most of the variance. k-means then groups similar municipalities. What can you read from this? Municipalities close together in the chart have a similar strengths/weaknesses profile across all measures. The cluster profile on the right shows the average sector scores for the selected cluster.

Cluster profile

Click a point in the chart to see the cluster profile.

Pairwise comparison (dominance analysis)

For each measure, municipalities are compared pair by pair to see which performed better. All individual comparisons are used to calculate a win rate per municipality: the share of matchups it won. This result is more robust than a simple total score because it reflects strength across many independent categories.

The dominance matrix shows, for each pair (row vs column), how often the row municipality outperformed the column municipality. Diagonal blue blocks indicate clusters of similarly strong municipalities: performance tiers. The matrix is sorted by win rate, with the strongest municipalities at the top.

Only municipalities in the current filter. Non-applicable measures are excluded from the comparison.

Win-rate ranking

Share of pairwise measure comparisons won by a municipality

Dominance matrix (top 40)

How often the row municipality wins against the column municipality. Blue = wins, red = loses, grey = tied

Dominance network

All municipalities as nodes. An edge between two nodes means one municipality outperforms the other in more than 60% of jointly rated measures. Node size and colour reflect win rate.

Closeness = municipalities are directly connected by a dominance edge and are pulled together. Distance = no direct edge, so repulsion dominates. Clusters of nearby nodes are performance tiers where municipalities outperform each other to a similar degree or are roughly level.