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Guess you have a slight wrong idea of KNN-Classifier. Quoting SciKit-Learn which have a nice explanation (Source: http://scikit-learn.org/stable/modules/neighbors.html)
Classification is computed from a simple majority vote of the nearest neighbors of each point: a query point is assigned the data class which has the most representatives within the nearest neighbors of the point.
Let's take the first row of your example, from a given point it computes the 3 nearest neighbors, unfortunately they come all from different classes, so it has just picked the one with the lowest class-nr (it could have picked any other as well).
Note that this is the typical behavior of a KNN-Classifier, however, in some implementations like the one from scikit-learn you can specify that the output also depends on the distances to the k nearest neighbors.
