pareto( creates a Pareto chart of
y. A Pareto chart is a bar chart with the bars sorted in descending
order, and it includes a line that shows the cumulative distribution. The chart displays the
tallest bars that comprise 95% of the cumulative distribution, up to a maximum of
10 bars. If
n bars contain exactly 95% of the
n is less than
10, the chart
The bar labels along the x-axis are the indices to the bar values in
pareto(___, specifies a
threshold value between
1. The threshold is the
fraction of the cumulative distribution to include in the chart. The chart includes the
tallest bars that comprise that fraction, up to a maximum of
10 bars. If
n bars contain exactly the specified fraction, and
is less than
10, the chart displays
Create a Pareto Chart
y as a vector of five numbers that sum to 100, so you can see the relationship between the numbers and the bars in the chart.
Then, create a Pareto chart of
y without specifying the x-coordinates. The x-axis tick labels are the locations of the bar values in
y. In this case,
y(3) is the largest value, so its bar displays in the left most position, followed by
y(4). These three bars comprise more than 95% of the cumulative distribution, so they are the only bars shown in the chart.
y = [2 3 45 20 32]; pareto(y)
n of the tallest bars comprise exactly 95% of the cumulative distribution,
n+1 bars in the chart. For example, define
y such that two bars contain exactly 95% of the data.
pareto displays the tallest three bars.
y = [4 1 40 55]; pareto(y)
Display All the Values in the Cumulative Distribution
Use a Pareto chart to examine the preferred types of pie in a survey of 200 participants. Define
x as a string vector containing five pie flavors, and define
y as the number of votes for each flavor. Create a Pareto chart, and include all the values in the cumulative distribution by setting the
threshold argument to
x = ["Chocolate" "Apple" "Pecan" "Cherry" "Pumpkin"]; y = [35 50 30 5 80]; pareto(y,x,1) ylabel('Votes')
Specify String Labels Along x-Axis
x as a string vector containing the names of eight programmers that contributed to a project. Define
y as the number of lines of code that each programmer contributed. Display the data in a Pareto chart with a title.
x = ["Fred" "Gina" "Norman" "Josphat" "Julia" "Wally" "Heidi" "Pat"]; y = [200 120 555 608 1024 101 57 687]; pareto(y,x) title('Lines of Code by Programmer')
Specify Categories Along x-Axis
x as a categorical vector of the names of five different model rockets manufactured at a particular factory. Define
y as the number of rockets that failed to launch from a random sampling within each category. Display the data in a Pareto chart, and add labels to the x- and y-axes.
x = categorical(["Firestorm" "Mr. Ballista" "Moonshot" "Lil' Joe" "Houston"]); y = [526 100 221 40 10]; pareto(y,x) xlabel('Rocket Model') ylabel('Launch Failures')
Specify Dates Along x-Axis
x as a datetime vector indicating the manufacturing dates for a particular electronic component. Define
y as the number of defects for each batch of components. Display the data in a Pareto chart, and add labels to the x- and y-axes.
x = datetime(2018,5,1:5,'Format','d MMM'); y = [100 526 221 60 49]; pareto(y,x) xlabel('Manufacturing Date') ylabel('Defects')
Customize Chart Appearance
y as a vector of five numbers, and create a Pareto chart. Specify return arguments so you can customize aspects of the chart and axes.
y = [20 30 10 55 5]; [charts, ax] = pareto(y);
charts array to change the colors of the
Bar and the
Line objects. The first element in
charts is the
Bar object, and the second element is the
Line object. Change the bar colors to a shade of purple, and change the line color to a shade of green.
charts(1).FaceColor = [0.50 0.37 0.60]; charts(2).Color = [0 0.50 0.10];
Next, change the color of the left y-axis to match the bars, and change the color of the right y-axis to match the line. The
Axes object for the left side is the first element of the
ax array. The other
Axes object is in the second element of the
After changing the colors, display the axes grid lines.
ax(1).YColor = [0.50 0.37 0.60]; ax(2).YColor = [0 0.50 0.10]; grid on
Create Multiple Charts in Same Figure
To create multiple charts in a figure, use a tiled chart layout. Call the
nexttile function to create an axes object in a tiled chart layout. If there is no layout available,
nexttile creates one. Create a Pareto chart by passing the axes to the
pareto function as the first argument.
ax1 = nexttile; pareto(ax1,[20 50 33 12])
nexttile function to add a second axes object to the layout. Then create a second Pareto chart.
ax2 = nexttile; pareto(ax2,[50 10 20 25 30])
y — y-coordinates (bar heights)
y-coordinates, or bar heights, specified as a vector of finite, nonnegative, numeric values.
x — x-coordinates (bar labels)
x-coordinates, or bar labels, specified as a vector the same
y. The values in the vector can be of finite, nonnegative,
numeric values, datetime values, duration values, or categorical values.
threshold — Fraction of cumulative distribution
0.95 (default) | number between
Fraction of the cumulative distribution to include in the chart, specified as a
pareto displays the bars that contribute to the cumulative
distribution in descending order, until just beyond the threshold, up to a maximum of
pareto([70 15 10 5],0.75) displays the tallest bars that
contain 75% of the cumulative distribution.
pareto([70 15 10 5],0.85) displays the tallest bars that
contain 85% of the cumulative distribution.
pareto([70 15 10 5],1) displays all the bars, since the
y is less than 10.
pareto(1:11,1) displays only the tallest 10 bars, since
the length of
y is greater than 10.
target — Target axes
Target axes, specified as an
Axes object. If you do not specify
the axes, and if the current axes is Cartesian,
pareto uses the
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.
Usage notes and limitations:
This function accepts GPU arrays, but does not run on a GPU.
For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).
Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.
Usage notes and limitations:
This function operates on distributed arrays, but executes in the client MATLAB®.
For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).