MATLAB: How to bin a set of data probability and plot it as a bar chart

bar chartbin datahistogramnormal distributionpdfprobability density

I have a set of observed data of 3 years of hourly measurements "x" (25920×1 double) with min = 0.00003484 and max = 3.8787 ;

I want to plot a figure that has the following characteristics:

1. x axis = x values, y axis = probability density

2. X should be binned for one month and plotted as a bar chart (look like a bar chart)

3. A normal pdf (based on the mean and std of the observed data) must be plotted

This is in order to compare the existing data and a normal dist or how well the fit in the graph.

I don't even know how to start, how can I do this? Any idea? I am having trouble binning the data and plotting it as a bar chart of the pdf. The normal pdf plotting is not an issue

Best Answer

If you have the Statistic and Machine Learning Toolbox, you could use the histfit command.

Related Solutions

MATLAB: How to plot simple histogram of multiple variables

How about the bar() function? Or the plot() function?

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clearvars;
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 16;
x1 = normrnd(10,1,[1,1000]) %normal distribution
x2 = gamrnd(10,1,[1,1000]) %gamma distribution
x3 = exprnd(10,[1,1000]) %exponential distribution
minValue = min([x1,x2,x3])
maxValue = max([x1,x2,x3])
numBins = 500;  % Whatever you want.
edges = linspace(minValue, maxValue, numBins);
counts1 = histcounts(x1, edges);
counts2 = histcounts(x2, edges);
counts3 = histcounts(x3, edges);
% Plot with bars.
subplot(1, 2, 1);
bar(edges(1:end-1), counts1, 'FaceColor', 'r');
hold on;
bar(edges(1:end-1), counts2, 'FaceColor', 'g');
bar(edges(1:end-1), counts3, 'FaceColor', 'b');
grid on;
xlabel('Value', 'FontSize', 20)
ylabel('Count', 'FontSize', 20)
title('Bar Chart', 'FontSize', 20)
legend('x1 histogram', 'x2 histogram', 'x3 histogram');
% Plot with lines.
subplot(1, 2, 2);
plot(edges(1:end-1), counts1, 'r-', 'LineWidth', 2);
hold on;
plot(edges(1:end-1), counts2, 'g-', 'LineWidth', 2);
plot(edges(1:end-1), counts3, 'b-', 'LineWidth', 2);
grid on;
xlabel('Value', 'FontSize', 20)
ylabel('Count', 'FontSize', 20)
title('Line Plot', 'FontSize', 20)
legend('x1 histogram', 'x2 histogram', 'x3 histogram');
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0.04, 1, 0.96]);

MATLAB: Normalized distribution for histogram

If you have the Statistics Toolbox, you might find the dfittool distribution fitting tool quite useful.

doc dfittool

If not, you can normalize a histogram by scaling the counts in each bin. With the normalized counts, you can plot both the normalized histogram and your curve. The trick is to identify the appropriate scaling factor.

Here is some example code where I plot the normal probability with the normalized histogram data:

% Arbitrary data generation and statistics
dataVec = randn(1000,1);
muData = mean(dataVec);
stdData = std(dataVec);
% Defining the bin centers
binStep    = 0.1;
binCenters = -5:binStep:5;
% Compute the histogram scaling factor. (If all histogram counts are in a
% single bin, the probability = 1)
binCount   = histc(dataVec,binCenters);
probScale  = sum(binCount)*binStep;
% Plot the normalized histogram and change the bar color for line
% visibility
histHandle = bar(binCenters,binCount/probScale,'hist');
set(histHandle,'FaceColor',[1,1,1]); 
hold on;
% Overlay the distribution fit on the histogram
x = binCenters;
y = normpdf(x,muData,stdData);
plot(x,y);
xlabel('Data');
ylabel('Probability');

Hope this helps to get you started!

Best Answer

Related Solutions

MATLAB: How to plot simple histogram of multiple variables

MATLAB: Normalized distribution for histogram

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