MATLAB Answers


How to draw the below type of graph in MATLAB?

Asked by Changho LEE on 10 Sep 2019
Latest activity Commented on by Cris LaPierre
on 11 Sep 2019
I'm trying to draw a graph of the form below.
But I can't figure out how to draw it.
Attached data here.
I want to hear from the experts.
Thank you.


2019 年 9 月 10 日
Nice plot design -- unfortunately, MATLAB doesn't have builtin solution. Best idea I have otomh would be to create 12 axes for each independent month and plot with barh() then add yet another overall to plot the overall monthly average.
How about attaching a .mat file with the data so folks can play around with it instead of having to create their own? Might get a few takers-on for the challenge...
Changho LEE 2019 年 9 月 10 日
The data file is attached here.
Changho LEE 2019 年 9 月 11 日
The advice made good results.
Thank you.

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2 Answers

回答者: Cris LaPierre
2019 年 9 月 10 日

I didn't worry about importing your data specifically since it appears to be a summary and not the raw data anyway.
% import bar plot data from spreadsheet
opts = detectImportOptions('data.xlsx','Range',[1 1 18 18]);
data = readtable('data.xlsx',opts);
% import line plot data
ave = readmatrix('data.xlsx',"Range","B20");
% Create x vector of 13 months to give room for Dec bar plot
d = datetime(2019,1,1,'Format',"MMM") + calmonths(0:12);
% Plot ave data
ylim([0 16])
% Plot 13th month separately to give room for Dec bar plot
hold on
hold off
% Turn off x-label for Jan 2020
ax = gca;
ax.XTickLabel{13} = "";
% Use position of current plot to determine placement of bar plots
p = get(gca,'position'); % [left bottom width height]
dx = [0 p(3).*days(diff(d))/365]; % width of each month
% Create bin data for bar plots
edges = 1:16;
% plot bar plots by positioning a new axes on top of the current axis
for i = 1:length(d)-1
a = axes('Position',[p(1)+sum(dx(1:i)) p(2) .75*dx(i+1) p(4)]);
b = barh(a,edges,data{:,i+1});
axis off
Not perfect, but it should be able to get your started.


Adam Danz
2019 年 9 月 11 日
Yeah, that was my approach in my answer except that I added 1 instead of inf to the final bin edge since the other bins were in increments of 1. But inf is a better idea in case there are outlers.
The other big difference between our answers it that your bar axes are 'off' and on top of the summary axis whereas my histogram axes are plotted first and then the summary axis is on top so that there is only 1 invisible axis.
Cris LaPierre
2019 年 9 月 11 日
Good point. I thought about doing it that way, but went with the summary axis first so that it could set where I needed to place the histograms. Had to hunt for the uistack fxn because of that. I'd never used it before.
Changho LEE 2019 年 9 月 11 日
This graph is part of my teacher's research in 1975.
His research was so beautiful that I wanted to make it MATLAB and use it for other research.
You made it so perfect and beautiful.
It looks really elegant.
This is a wonderful thing I never thought of.
Thank you very much for creating such a wonderful work of art.
Thank you very much.

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回答者: Adam Danz
2019 年 9 月 10 日
編集済み: Adam Danz
2019 年 9 月 11 日

"Feb" in your excel file has a $ character which needs fixed. If you have many excel sheets, you can fix it from within the code but I assumed it's fixed prior to running this.
The first section loads the data and prepares it for histogram().
The 2nd section defines the plot layout. You can change the margin size etc.
The 3rd section does the plotting and saves each axis handle.
The 4th section cleans up the axes and does all of the cosmetics.
The 5th section overlays an additonal axis at the same scale as the underlying subplots (as dpb suggested) and plots the mean curve.
See comments for details.
data = readtable('data.xlsx');
edgesStr = data{:,1}; %save edges to an array
edges = str2double(cellfun(@(x)regexp(x,'^\d+','match'),edgesStr(1:end-2))); %edges, numeric
data(:,1) = []; %remove edges from data table
data = fillmissing(data,'constant', 0); %replace NaNs with 0
% Determine subplot dimensions (all in normalized units)
nSubplots = size(data,2); %number of subplots needed
LRmargins = [.1,.08]; %left and right figure margins
TBmargins = [.1, .1]; %top and bottom figure margins
subplotWidth = (1-sum(LRmargins))/nSubplots; %width of each subplot
subplotHeight = 1-sum(TBmargins); %height of each subplot
subplotPos = linspace(LRmargins(1),1-LRmargins(2)-subplotWidth, nSubplots); % lateral position of each subplot
% Loop through each subplot, create subplot and plot the data
binEdges = [edges(:).',edges(end)+1];
sph = gobjects(1,nSubplots); %store subplot handles
for i = 1:nSubplots
sph(i) = axes('Units', 'Normalize', 'Position', [subplotPos(i),TBmargins(1),subplotWidth,subplotHeight]);
histogram(sph(i),'BinEdges', binEdges, 'BinCounts', data{1:17,i},'Orientation','Horizontal');
% Clean up
maxBarHeight = max(data{1:17,:},[],'all'); %max bar height
% remove the x axis ticks for all subplots
% Set the y tick for the left most subplot as the bin lables
set(sph,'YTick', binEdges(1:end-1))
set(sph(2:end), 'YTickLabel',[])
% Make sure all axes have the same ylim
% Make sure all axes have same scale
% Set the month labels along the horizontal, bottom axis
% Label bins
% overlay summary axis
sph2 = axes('Position',[subplotPos(1),TBmargins(1),1-sum(LRmargins),subplotHeight]);
% plot mean curve
plot(data{end,:}, 'r-s','Linewidth',1.5)
% Scale the axis to match the range of subplots
% Turn off axis
axis(sph2, 'off')
190910 235121-Figure 1.png


Cris LaPierre
2019 年 9 月 11 日
I see what it is. It's this line of code:
data{nanRow,nanCol} = 0;
This is interpreted as 'access the specified rows for each listed column/variable'. Rows 3-7 are the only rows that never have a NaN, so are never specified in nanRow and therefore don't get changed to 0.
You get the same result doing this:
or for that matter,
For what it's worth, this wouldn't work for an array either. You can read more here. You would need to use linear indexing instead, which is not supported for tables.
There are a bunch of ways around this. Here are some options:
1. Use a for loop to change NaN to 0 for each NaN
for i = 1:length(nanRow)
data{nanRow(i),nanCol(i)} = 0 % replace NaNs with 0 so histrogram() doesn't throw error
2. Chanage NaN to 0 for each variable
for i = 1:width(data)
data{isnan(data{:,i}),i} = 0 % replace NaNs with 0 so histrogram() doesn't throw error
3. Extract to an array, use linear indexing, then assign back to table.
Adam Danz
2019 年 9 月 11 日
Yeah, I would have rather used your last option which should be implemented for tables too.
But instead I used option 4, fillmissing, which is a one-liner that does work with tables.
Cris LaPierre
2019 年 9 月 11 日
Ah, much better :)

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