violinplot
Syntax
Description
Vector and Matrix Data
violinplot(
creates a Violin Plot for each column of the
matrix ydata
)ydata
. If ydata
is a vector, then
violinplot
creates a single violin plot.
violinplot(
groups the data in xgroupdata
,ydata
)ydata
according to the unique values in
xgroupdata
and plots each group of data as a separate violin plot.
xgroupdata
determines the position of each violin plot along the
x-axis.
violinplot(___,GroupByColor=
uses color to differentiate between violin plots. The function groups the data in
cgroupdata
)ydata
according to the unique value combinations in
xgroupdata
(if specified) and cgroupdata
, and
plots each group of data as a separate violin plot. The vector
cgroupdata
then determines the color of each violin plot.
ydata
must be a vector, and cgroupdata
must
have the same length as ydata
. Specify the color grouping data
name-value pair argument after any of the input argument combinations in the previous
syntaxes.
Table Data
violinplot(
creates a violin plot of the data in tbl
,xvar
,yvar
)yvar
grouped by the data in
xvar
, where xvar
and yvar
are variables from the table tbl
. To plot one data set, specify one
variable for xvar
and one variable for yvar
. To plot
multiple data sets, specify multiple variables for xvar
,
yvar
, or both. If both arguments specify multiple variables, they
must specify the same number of variables.
Additional Options
violinplot(___,
specifies additional options using one or more name-value arguments. For example, you can
specify the orientation and which half of the violin to plot.Name=Value
)
returns a
v
= violinplot(___)ViolinPlot
object or a vector of ViolinPlot
objects.
Use v
to set properties of the violin plots after creating them. For
a list of properties, see ViolinPlot Properties.
Examples
Violin Plot from Vector
Create a single violin plot from a vector of patient ages. Use the violin plot to analyze the distribution of ages.
Load the patients
data set. The Age
vector contains the ages of 100 patients. Create a violin plot to visualize the distribution of ages.
load patients violinplot(Age) ylabel("Age (years)")
The outline of the violin plot is determined by the kernel density estimate (kde) for the probability density function. The kde is bell-shaped with a peak near 40
on the vertical axis. The plot shows that the data in Age
is approximately normally distributed and the median patient age is around 40.
Violin Plots from Matrix
Generate a matrix of normally distributed random numbers. Create a violin plot for the data in each column of the matrix.
ydata = randn(100,3); violinplot(ydata)
The three violin plots have group labels 1, 2, and 3. The shapes of the violin plots are slightly different due to randomness in the data. However, each violin plot has the bell shape characteristic of a normal distribution.
Use Positional Grouping Data
Generate a vector of normally distributed random numbers and create a vector of grouping data.
ydata = randn(100,1); xgroupdata = categorical(repelem(["group1";"group2";"group3"],[20,50,30]));
Create a set of violin plots for the data in ydata
grouped by the unique values in xgroupdata
. Each violin plot in the figure corresponds to a unique value in xgroupdata
.
violinplot(xgroupdata,ydata)
Compare Violin Plots
Generate two vectors of normally distributed data and three vectors of grouping data.
ydata1 = randn(100,1); ydata2 = randn(100,1)+5; xgroupdata1 = categorical(repelem(["group1";"group2"],[90,10])); xgroupdata2 = categorical(repelem(["group1";"group2"],[10,90])); xgroupdata3 = categorical(repelem(["group3";"group4"],[25,75]));
The variables ydata1
and ydata2
contain normally distributed data with means of 0
and 5
, respectively. xgroupdata1
and xgroupdata2
contain different sequences of the same group labels. xgroupdata3
contains different group labels from those in xgroupdata1
and xgroupdata2
.
Create a table from the sample data and grouping data.
tbl = table(xgroupdata1,xgroupdata2,xgroupdata3, ... ydata1,ydata2,VariableNames=["X1","X2","X3","Y1","Y2"]);
Create a set of overlaid violin plots using the data in ydata1
grouped by xgroupdata1
and xgroupdata2
.
violinplot(tbl,["X1","X2"],"Y1")
The figure shows two sets of overlaid violin plots. The blue violin plots represent the data in ydata1
grouped by xgroupdata1
, and the orange violin plots represent the same data grouped by xgroupdata2
. The overlaid plots show that the different groupings do not significantly change the median values for each group. However, the different groupings have a visible effect on the shape of the violin plots corresponding to each group. This result suggests that the distribution of the data in each group is affected by how the data is grouped.
Create another set of violin plots using the data in ydata1
grouped by xgroupdata1
and the data in ydata2
grouped by xgroupdata3
.
violinplot(tbl,["X1","X3"],["Y1","Y2"])
The blue plots corresponding to groups 1 and 2 represent the data in ydata1
, and the orange plots corresponding to groups 3 and 4 represent the data in ydata2
. The plots show that the median values for the data in groups 3 and 4 are larger than those for groups 1 and 2.
Use Positional and Color Grouping Data
Generate a vector of normally distributed random numbers. Create two vectors for positional and color grouping data.
ydata = randn(100,1); xgroupdata = categorical(repelem(["group1";"group2";"group3"],[20;50;30])); cgroupdata = categorical(repelem(["a";"b";"a";"b";"c";"d";"e"],[10;10;25;25;10;10;10]));
The variable ydata
contains normally distributed data with a mean of 0
. xgroupdata
contains labels for three different groups. The labels in cgroupdata
split the first two groups in xgroupdata
into the same two colors, and the third group in xgroupdata
into three different colors.
Plot the data in ydata
using xgroupdata
as the positional grouping data and cgroupdata
as the color grouping data.
violinplot(xgroupdata,ydata,GroupByColor=cgroupdata)
The figure shows a set of violin plots for each of the three group labels in xgroupdata
. The sets for groups 1 and 2 each contain an orange and a blue violin plot. The set of violin plots for group 3 contains a yellow, a purple, and a green violin plot.
Specify Evaluation Points and Density Values
Generate a vector of random numbers. Estimate the pdf for the data by calculating its kernel density estimate (kde).
ydata = [randn(100,1); 6+2*randn(100,1)]; [f,xf] = kde(ydata,Bandwidth=0.6);
f
contains values for the kde, and xf
contains the corresponding evaluation points.
Create a violin plot using f
as the density values and xf
as the evaluation points. The shape of the violin plot shows that the data has a bimodal nature.
violinplot(EvaluationPoints=xf,DensityValues=f)
Compare Data Sets
Create two vectors of randomly generated data. Create two vectors of positional grouping data.
ydata1 = randn(100,1); ydata2 = [randn(25,1)+2;randn(75,1)+5]; xgroupdata1 = repelem([1;2],[50;50]); xgroupdata2 = repelem([1;2],[25;75]);;
The variables ydata1
and ydata2
contain the randomly generated data. xgroupdata1
and xgroupdata2
contain different sequences of the same two group labels.
Compare the data in ydata1
grouped by the labels in xgroupdata1
with the data in ydata2
grouped by the labels in xgroupdata2
. For each group, create a horizontal violin plot with the data in ydata1
represented in the top half and the data in ydata2
represented in the bottom half.
violinplot(xgroupdata1,ydata1,Orientation="horizontal",DensityDirection="positive") hold on violinplot(xgroupdata2,ydata2,Orientation="horizontal",DensityDirection="negative") legend("ydata1","ydata2")
The violin plots show that, for each group, the data for ydata1
and ydata2
is approximately normally distributed and the data for ydata1
has a smaller mean than the data for ydata2
. Moreover, the data for ydata2
has a larger mean in group 2
than it does in group 1
.
Specify Axes for Violin Plots
Create violin plots from patient data to compare the blood pressure of smokers and nonsmokers. The plots show that smokers have higher systolic and diastolic blood pressure than nonsmokers.
Load the patients
data set. Convert Smoker
to a categorical
variable with the descriptive category names Smoker
and Nonsmoker
rather than 1
and 0
.
load patients Smoker = categorical(Smoker,logical([1 0]),["Smoker","Nonsmoker"]);
Create a 1-by-2 tiled chart layout using the tiledlayout
function. Create the first set of axes ax1
by calling the nexttile
function. In the first set of axes, display two violin plots representing the systolic blood pressure values, one for smokers and the other for nonsmokers. Create the second set of axes ax2
within the tiled chart layout by calling the nexttile
function. In the second set of axes, do the same for diastolic blood pressure.
tiledlayout(1,2) % Left axes ax1 = nexttile; violinplot(ax1,Systolic,GroupByColor=Smoker) ylabel(ax1,'Systolic Blood Pressure') legend("Smoker","Nonsmoker") % Right axes ax2 = nexttile; violinplot(ax2,Diastolic,GroupByColor=Smoker) ylabel(ax2,"Diastolic Blood Pressure") legend("Smoker","Nonsmoker")
Update Violin Plot Color
Load the patients
data set, and convert the Smoker
variable to categorical
.
load patients Smoker = categorical(Smoker,logical([1 0]),["Smoker","Nonsmoker"]);
The variables Diastolic
and Smoker
contain data for patient diastolic blood pressure and smoker status.
Create a set of violin plots for the data in Diastolic
grouped by Smoker
.
v = violinplot(Diastolic,GroupByColor=Smoker)
v = 1x2 ViolinPlot array: ViolinPlot ViolinPlot
v
is an array containing two ViolinPlot
objects. You can modify the violin plots by specifying the properties of the ViolinPlot
objects in v
. For more information, see ViolinPlot Properties.
Update the colors of the violin plots so that the plot for smokers is pink and the plot for nonsmokers is green.
v(1).FaceColor = [1 0 1]; % Pink v(2).FaceColor = [0 1 0]; % Green legend("Smoker","Nonsmoker")
Input Arguments
ydata
— Sample data
numeric vector | numeric matrix
Sample data, specified as a numeric vector or matrix.
If
ydata
is a matrix, thenviolinplot
creates a violin plot for each column ofydata
.If
ydata
is a vector and you do not specifyxgroupdata
orcgroupdata
, thenviolinplot
creates a single violin plot.If
ydata
is a vector and you specifyxgroupdata
orcgroupdata
, thenviolinplot
creates a violin plot for each unique value combination inxgroupdata
andcgroupdata
.
Data Types: single
| double
xgroupdata
— Positional grouping data
numeric vector | numeric matrix | categorical vector | categorical matrix
Positional grouping data, specified as a numeric or categorical vector.
If ydata
is a vector, xgroupdata
must be a
vector of the same length. If ydata
is a matrix,
xgroupdata
must be a matrix of the same size, or a vector of
length equal to the number of rows or columns in ydata
.
violinplot
groups the data in ydata
according to the unique value combinations in xgroupdata
and
cgroupdata
, and creates a violin plot for each group. By default,
violinplot
vertically orients the violin plots and displays the
xgroupdata
values along the x-axis. You can
change the violin plot orientation by using the Orientation
property.
Data Types: single
| double
| categorical
cgroupdata
— Color grouping data
numeric vector | categorical vector | logical vector | string array | character vector | cell array of character vectors
Color grouping data, specified as a numeric vector, categorical vector, logical
vector, string array, character vector, or cell array of character vectors.
cgroupdata
must have the same length as the vector
ydata
; you cannot specify cgroupdata
when
ydata
is a matrix.
violinplot
groups the data in ydata
according to the unique value combinations in xgroupdata
and
cgroupdata
. The function creates a violin plot for each group of
data and assigns the same color to groups with the same cgroupdata
value.
Data Types: single
| double
| categorical
| logical
| string
| char
| cell
tbl
— Source table
table | timetable
Source table containing the data to plot, specified as a table or timetable.
xvar
— Table variables containing positional grouping data
string array | character vector | cell array | pattern | numeric scalar or vector | logical vector | vartype
subscript
Table variables containing the positional grouping data, specified as one or more table variable indices.
Specifying Table Indices
Use any of the following indexing schemes to specify the intended variable or variables.
Indexing Scheme | Examples |
---|---|
Variable names:
|
|
Variable index:
|
|
Variable type:
|
|
Plotting Your Data
The table variables you specify can contain numeric or categorical values.
To plot one set of violin plots, specify one variable for xvar
and one variable for yvar
. For example, create a table with one
categorical grouping variable and two variables containing normally distributed random
values. Plot the data in Y1
grouped by the data in
X
.
X = categorical(repelem(["a1";"b1"],50)); Y1 = randn(100,1); Y2 = 5*randn(100,1)+10; tbl = table(X,Y1,Y2); violinplot(tbl,"X","Y1")
To plot multiple data sets together, specify multiple variables for
xvar
, yvar
, or both. If you specify multiple
variables for both arguments, the number of variables for each argument must be the
same.
For example, create a set of violin plots from the data in Y1
using X
as the grouping variable, and a set using
Y2
as the
data.
violinplot(tbl,"X",["Y1","Y2"])
You can also use different indexing schemes for xvar
and
yvar
. For example, specify xvar
as a variable
name and yvar
as an index
number.
violinplot(tbl,"X",3)
yvar
— Table variables containing sample data
string array | character vector | cell array | pattern | numeric scalar or vector | logical vector | vartype
subscript
Table variables containing the sample data, specified as one or more table variable indices.
Specifying Table Indices
Use any of the following indexing schemes to specify the intended variable or variables.
Indexing Scheme | Examples |
---|---|
Variable names:
|
|
Variable index:
|
|
Variable type:
|
|
Plotting Your Data
The table variables you specify must contain numeric values.
To plot one set of violin plots, specify one variable for xvar
and one variable for yvar
. For example, create a table with two
categorical grouping variables and one variable containing normally distributed random
values. Plot the data in Y
grouped by the data in
X1
.
X1 = categorical(repelem(["a1";"b1"],50)); X2 = categorical(repelem(["a2";"b2";"c2"],[33,33,34])); Y = randn(100,1); tbl = table(X1,X2,Y); violinplot(tbl,"X1","Y")
To plot multiple data sets together, specify multiple variables for
xvar
, yvar
, or both. If you specify multiple
variables for both arguments, the number of variables for each argument must be the
same.
For example, create a set of violin plots from the data in Y
using X1
as the grouping variable, and a set using
X2
as the grouping
variable.
violinplot(tbl,["X1","X2"],"Y")
You can also use different indexing schemes for xvar
and
yvar
. For example, specify xvar
as a variable
name and yvar
as an index
number.
violinplot(tbl,"X1",3)
evalPts
— Evaluation points
numeric vector | numeric matrix
Evaluation points for the probability density function (pdf), specified as one of these values:
numeric vector — Create a single violin plot using the evaluation points in
evalPts
and the pdf values indensVals
.numeric matrix — Create multiple violin plots. Each violin plot represents the evaluation points in a column of
evalPts
and the pdf values in the corresponding column ofdensVals
.
If you specify evalPts
, you must also specify
densVals
, and they must be the same size.
Data Types: single
| double
densVals
— Values for pdf
numeric vector | numeric matrix
Values for the pdf, specified as one of these values:
numeric vector — Create a single violin plot using the evaluation points in
evalPts
and the pdf values indensVals
.numeric matrix — Create multiple violin plots. Each violin plot represents the evaluation points in a column of
evalPts
and the pdf values in the corresponding column ofdensVals
.
If you specify densVals
, you must also specify
evalPts
, and they must be the same size.
Data Types: single
| double
ax
— Target axes
Axes
object
Target axes, specified as an Axes
object. If you do not specify the
axes, then violinplot
uses the current axes
(gca
).
Name-Value Arguments
Specify optional pairs of arguments as
Name1=Value1,...,NameN=ValueN
, where Name
is
the argument name and Value
is the corresponding value.
Name-value arguments must appear after other arguments, but the order of the
pairs does not matter.
Example: violinplot(ydata,Orientation="horizontal",DensityDirection="negative")
uses the data in ydata
to plot the bottom half of a horizontal violin
plot.
Note
The ViolinPlot
properties listed here are only a subset. For a
complete list, see ViolinPlot Properties.
DensityWidth
— Maximum violin plot width
positive scalar
Maximum violin plot width, specified as a positive scalar.
DensityWidth
has the same units as the positional grouping data
specified by xgroupdata
or xvar
.
Example: DensityWidth=0.5
Data Types: single
| double
DensityDirection
— Plot full or half violin
"both"
(default) | "positive"
| "negative"
Plot a full or half violin, specified as one of the values in this table.
Value | Description |
---|---|
"both" | Plot both halves of the violin. |
"positive" | Plot the positive half of the violin, which depends on the
|
"negative" | Plot the negative half of the violin, which depends on the
|
Example: DensityDirection="negative"
Data Types: string
| char
DensityScale
— Method for normalizing violin plots
"area"
(default) | "width"
| "count"
Method for normalizing the violin plots, specified as one of the values in this table.
Value | Description |
---|---|
"area" | The violin plots have equal areas. |
"width" | The violin plots have widths equal to
DensityWidth . |
"count" | The violin plots have widths proportional to the number of data points in each group. |
Example: DensityScale="count"
Data Types: string
| char
Orientation
— Orientation of violin plots
"vertical"
(default) | "horizontal"
Orientation of the violin plots, specified as "vertical"
or
"horizontal"
. By default, the violin plots are vertically
oriented so that the violin plots align with the y-axis.
Regardless of the orientation, violinplot
stores the sample data
in the YData
property of the ViolinPlot
object.
Example: Orientation="horizontal"
Data Types: string
| char
Output Arguments
v
— Violin plots
ViolinPlot
object | vector of ViolinPlot
objects
Violin plots, returned as a ViolinPlot
object or a vector of
ViolinPlot
objects.
If you specify
ydata
as a matrix,violinplot
returns one object per column.If you specify
tbl
,violinplot
returns one object per index inxvar
oryvar
, whichever has the most elements.If you specify
cgroupdata
,violinplot
returns one object per group.
Use v
to set properties of the violin plots after
creating them. For a list of properties, see ViolinPlot Properties.
More About
Violin Plot
A violin plot provides a visual representation of the empirical distribution for a data sample. The shape of a violin plot is determined by the kernel density estimate (kde) for the probability density function (pdf) reflected about the vertical axis.
Version History
Introduced in R2024b
MATLAB Command
You clicked a link that corresponds to this MATLAB command:
Run the command by entering it in the MATLAB Command Window. Web browsers do not support MATLAB commands.
Select a Web Site
Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select: .
You can also select a web site from the following list:
How to Get Best Site Performance
Select the China site (in Chinese or English) for best site performance. Other MathWorks country sites are not optimized for visits from your location.
Americas
- América Latina (Español)
- Canada (English)
- United States (English)
Europe
- Belgium (English)
- Denmark (English)
- Deutschland (Deutsch)
- España (Español)
- Finland (English)
- France (Français)
- Ireland (English)
- Italia (Italiano)
- Luxembourg (English)
- Netherlands (English)
- Norway (English)
- Österreich (Deutsch)
- Portugal (English)
- Sweden (English)
- Switzerland
- United Kingdom (English)