variabilitychart
R2026bSyntax
Description
variabilitychart(___,
specifies additional options using one or more name-value arguments. For example, you can
specify the names of the factors or add boxes around the level data for specific
factors.Name=Value)
variabilitychart(
creates the variability chart in the specified parent container.parent,___)
v = variabilitychart(___)VariabilityChart object. Use v to set properties of
the variability chart after creating it. For a list of properties, see VariabilityChart Properties.
Examples
This example shows how to create a variability chart from categorical factor vectors and a numeric response vector to identify sources of variation in a manufacturing process.
Define data for a component manufacturing process with three operators and two machines. Each operator uses each machine four times.
operator = repelem(categorical(["Op1","Op2","Op3"]),8)'; machine = repmat(categorical(["M1","M2"]),1,12)';
Simulate part thickness measurements with variation due to operator and machine differences.
rng(0) % For reproducibility
thickness = 5 + 0.3*double(operator) + 0.5*double(machine) + 0.2*randn(24,1);Create a variability chart to visualize how thickness varies across operators and machines.
variabilitychart({operator,machine},thickness)
Use the variability chart to observe trends in the data. For example, machine M2 seems to produce thicker components than M1. There also appears to be variation based on who is operating the machine.
This example shows how to create a variability chart by passing a table and specifying the response variable name.
Construct a table of product weights measured across two production lines, two shifts, and three operators.
rng(0) % For reproducibility Line = repelem(categorical(["Line1","Line2"]),60)'; Shift = repmat(repelem(categorical(["Day","Night"]),30),1,2)'; Operator = repmat(repelem(categorical(["Op1","Op2","Op3"]),10),1,4)'; Weight = 50 + 2*double(Line) + 1.5*double(Shift) + 0.8*randn(120,1); tbl = table(Line,Shift,Operator,Weight);
Create a variability chart for the Weight variable. The function uses the remaining table variables as factors.
variabilitychart(tbl,"Weight")
Add boxes around factor levels and a target line to a variability chart using name-value arguments.
Load the patients data set and store the diastolic blood pressure readings with location and gender factors in a table.
load patients tbl = table(categorical(Location),categorical(Gender),Diastolic, ... VariableNames=["Location","Gender","Diastolic"]);
Create a variability chart with boxes around the first factor and a target line at 80 mmHg representing a clinical threshold.
variabilitychart(tbl,"Diastolic", ... FactorsWithBoxes=1, ... TargetValue=80)
The chart now highlights the grouping structure with boxes around location levels and marks the clinical threshold with a target line at 80 mmHg.
Create variability charts in specific panel containers within a figure to compare how fuel economy and vehicle weight vary across countries of origin and engine sizes.
Load the carbig data set and store the origin, cylinder count, fuel economy, and weight data in a table. Filter to the three most-represented countries and remove rows with missing values.
load carbig tbl = table(categorical(cellstr(Origin)),categorical(Cylinders),MPG,Weight, ... VariableNames=["Origin","Cylinders","MPG","Weight"]); tbl = tbl(ismember(tbl.Origin,["USA","Japan","Germany"]) & ~isnan(tbl.MPG) & ~isnan(tbl.Weight),:);
Create a figure with two panels, then plot a variability chart in each panel by passing the panel as the first argument.
f = figure(Position=[100 100 900 400]); p1 = uipanel(f,Position=[0 0 0.5 1],Title="MPG"); variabilitychart(p1,tbl,"MPG",FactorVariables=["Origin","Cylinders"]) p2 = uipanel(f,Position=[0.5 0 0.5 1],Title="Weight"); variabilitychart(p2,tbl,"Weight",FactorVariables=["Origin","Cylinders"])
Input Arguments
Name-Value Arguments
Output Arguments
More About
Version History
Introduced in R2026b
