How to vectorise a knnsearch loop to find nearest neighbours

I have a table storing coordinates. For each pair of coordinates (each row), I want to find the nearest neighbour distances to all other pairs of coordinates and store the mean for each pair, and an overall mean for the table, which I then save to a text file.

Currently the example code below works, but for my actual data it is nested in another loop, so it processes multiple tables each with multiple pairs of coordinates at a time, so it's pretty slow. Is there a way to vectorise this loop to improve the speed? (Any other criticisms of this code are welcome too).

% Create example table
images = ["Image_1";"Image_1";"Image_1"];
x = [27;100;80];
y = [40;145;190];
table_example = table(images,x,y);

% Loop to process the table
for k = 1:height(table_example) % for every row (coordinate) in the  table, do the following:
    
    current_coordinate = table_example{k,["x","y"]}; % extract coordinate of current loop iteration
    table_example{k,["x","y"]} = [NaN];              % change current coordinate in original table to NaN, to avoid comparing to itself
    
    k_neighbours = height(table_example)-1;          % get number of neighbours to search for - height of table minus 1 coordinate
    [idx,dist] = knnsearch(table_example{:,["x","y"]}, current_coordinate,"K", k_neighbours,"Distance","euclidean"); % get NN distances for current coordinate
    
    mean_distances_per_pair(k,:) = mean(dist);              % get mean distance for each pair
      
    table_example{k,["x","y"]} = current_coordinate;        % return current coordinate to table
    
end

overall_mean_distance = mean(mean_distances_per_pair);  % get overall mean distances for the whole table once loop is finished

% Write mean distance to text file
% writematrix([mean_distances_per_pair],examplelocation1,"WriteMode","Append")
% writematrix([overall_mean_distance],examplelocation2,"WriteMode","Append")