Generate a heatmap in a set X, Y, Z with Z being the intensity of the color

heatmap expects discrete x and y values. You goal is to bin your x and y's into 20 discrete bins and average the z values for each bin, but x and y themselves are continuous.

To achieve your goal take the advice of the warning message and use discretize to bin your x and y values.

% I used the following stand ins for your data:
% x = rand(540, 1);
% y = rand(540, 1);

n_bins = 20; % Number of grid cells
% If you want the width of the grid cell to be 20, use 
% n_bins = (max(x) - min(x)) / 20; 

x_discrete = discretize(x, n_bins);
y_discrete = discretize(y, n_bins);
tbl = table(X_discrete,y_discrete,z, 'VariableNames', {'x', 'y', 'z'});
h = heatmap(tbl,'x','y','ColorVariable','z','ColorMethod','mean');

Note: Why was this not a problem with the sample data?

Using your sample data,

x = [49.8, 14.5, -60.7, -21.6, -10.6];
y = [45.3, 7.9, 23.9, -58.5, -55.4];
z = [0.2 , -0.06, -0.35, -0.15, -0.08];
tbl = table(x',y',z', 'VariableNames', {'x', 'y', 'z'});
h = heatmap(tbl,'x','y','ColorVariable','z','ColorMethod','mean');

Does not throw an error because it treats each x and y value as a separate category. heatmap uses a call to categorical to transform the continuous values into categorical values.

Aside from not really providing the output you want (each point would be its own box instead of averaging grid cells), categorical seems to have a limit in how many categorical values it will create. I wasn't able to find any documentation about exactly what that limit is, but by experimentation, it tops out in the mid 200's. Since your vectors are 540 elements long, you get the warning about using discretize instead.