To make such a legend, you will have to use the "findobj" function to obtain handles to the different elements of the "boxplot" and then add a legend for each. Please try the following code:
% Generate some random data
rng(0); % For reproducibility
data = normrnd(5,1,100,1);
% Create a boxplot
figure;
boxplot(data, 'Colors', 'k', 'Symbol', 'ro');
% Customize the boxplot
% Use findobj to get a handle to the IQR box
hBox = findobj(gca, 'Tag', 'Box');
% Change the color of the IQR box
set(hBox, 'Color', 'blue', 'LineWidth', 2);
% Manually calculate the 9th and 91st percentiles
percentile_9 = prctile(data, 9);
percentile_91 = prctile(data, 91);
% Use hold on to plot the 9%-91% range and the mean
hold on;
% Add lines for the 9% to 91% range
p9_line = plot([0.85, 1.15], [percentile_9, percentile_9], 'g--', 'LineWidth', 2, 'DisplayName', '9% to 91% Range');
p91_line = plot([0.85, 1.15], [percentile_91, percentile_91], 'g--', 'LineWidth', 2);
% Calculate and plot the mean
mean_value = mean(data);
mean_point = scatter(1, mean_value, 100, 'filled', 'd', 'MarkerFaceColor', 'red', 'DisplayName', 'Mean');
% Capture outliers for legend
hOutliers = findobj(gca, 'Tag', 'Outliers');
% Add legend
hLegend = legend([findobj(gca, 'Tag', 'Median'), mean_point, hBox(1), p9_line, hOutliers(1)], ...
{'Median', 'Mean', '25%-75%', '9%-91%' 'Outliers'}, ...
'Location', 'northeast');
% Set labels and title
title('Boxplot with summary statistics');
ylabel('Values');
hold off;
Please refer to the following resources for more information:
- "findobj" documentation - https://www.mathworks.com/help/releases/R2023b/matlab/ref/findobj.html
- "prctile" documentation - https://in.mathworks.com/help/releases/R2023b/matlab/ref/prctile.html
- "legend" documentation - https://in.mathworks.com/help/releases/R2023b/matlab/ref/legend.html
Hope this helps!
