scatterhistogram

Create scatter plot with histograms

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Syntax

scatterhistogram(tbl,xvar,yvar)

scatterhistogram(tbl,xvar,yvar,'GroupVariable',grpvar)

scatterhistogram(xvalues,yvalues)

scatterhistogram(xvalues,yvalues,'GroupData',grpvalues)

scatterhistogram(___,Name,Value)

scatterhistogram(parent,___)

s = scatterhistogram(___)

Description

scatterhistogram(tbl,xvar,yvar) creates a scatter plot with marginal histograms from the table tbl. The xvar input indicates the table variable to display along the x-axis. The yvar input indicates the table variable to display along the y-axis.

scatterhistogram(tbl,xvar,yvar,'GroupVariable',grpvar) uses the table variable specified by grpvar to group observations specified by xvar and yvar.

scatterhistogram(xvalues,yvalues) creates a scatter plot of the data in xvalues and yvalues and displays the marginal histograms for the xvalues and yvalues data along the x-axis and y-axis, respectively.

scatterhistogram(xvalues,yvalues,'GroupData',grpvalues) uses the data in grpvalues to group the data in xvalues and yvalues.

scatterhistogram(___,Name,Value) specifies additional options for the scatter plot with marginal histograms using one or more name-value pair arguments. Specify the options after all other input arguments. For a list of properties, see ScatterHistogramChart Properties.

scatterhistogram(parent,___) creates the scatter plot with marginal histograms in the figure, panel, or tab specified by parent.

s = scatterhistogram(___) returns the ScatterHistogramChart object. Use s to modify the object after you create it. For a list of properties, see ScatterHistogramChart Properties.

Examples

Scatter Histogram Chart with Tabular Data

Create a scatter plot with marginal histograms from a table of data for medical patients.

Load the patients data set and create a table from a subset of the variables loaded into the workspace. Then, create a scatter histogram chart comparing the Height values to the Weight values.

load patients
tbl = table(LastName,Age,Gender,Height,Weight);
s = scatterhistogram(tbl,'Height','Weight');

Specify Table Variable for Grouping Data

Using the patients data set, create a scatter plot with marginal histograms and specify the table variable to use for grouping the data.

Load the patients data set and create a scatter histogram chart from the data. Compare the patients' Systolic and Diastolic values. Group the data according to the patients' smoker status by setting the 'GroupVariable' name-value pair argument to 'Smoker'.

load patients
tbl = table(LastName,Diastolic,Systolic,Smoker);
s = scatterhistogram(tbl,'Diastolic','Systolic','GroupVariable','Smoker');

Visualize Categorical and Numeric Data

Use a scatter plot with marginal histograms to visualize categorical and numeric medical data.

Load the patients data set, and convert the Smoker data to a categorical array. Then, create a scatter histogram chart that compares patients' Age values to their smoker status. The resulting scatter plot contains overlapping data points. However, the y-axis marginal histogram indicates that there are far more nonsmokers than smokers in the data set.

load patients
Smoker = categorical(Smoker);
s = scatterhistogram(Age,Smoker);
xlabel('Age')
ylabel('Smoker')

Specify Group Data and Customize Chart Properties

Create a scatter plot with marginal histograms using arrays of shoe data. Group the data according to shoe color, and customize properties of the scatter histogram chart.

Create arrays of data. Then, create a scatter histogram chart to visualize the data. Use custom labels along the x-axis and y-axis to specify the variable names of the first two input arguments. You can specify the title, axis labels, and legend title by setting properties of the ScatterHistogramChart object.

xvalues = [7 6 5 6.5 9 7.5 8.5 7.5 10 8];
yvalues = categorical({'onsale','regular','onsale','onsale', ...
    'regular','regular','onsale','onsale','regular','regular'});
grpvalues = {'Red','Black','Blue','Red','Black','Blue','Red', ...
    'Red','Blue','Black'};
s = scatterhistogram(xvalues,yvalues,'GroupData',grpvalues);

s.Title = 'Shoe Sales';
s.XLabel = 'Shoe Size';
s.YLabel = 'Price';
s.LegendTitle = 'Shoe Color';

Change the colors in the scatter histogram chart to match the group labels. Change the histogram bin widths to be the same for all groups.

s.Color = {'Red','Black','Blue'};
s.BinWidths = 1;

Specify Scatter Histogram Chart Appearance

Create a scatter plot with marginal histograms. Specify the number of bins and line widths of the histograms, the location of the scatter plot, and the legend visibility.

Load the patients data set and create a scatter histogram chart from the data. Compare the patients' Diastolic and Systolic values, and group the data according to the patients' SelfAssessedHealthStatus values. Adjust the histograms by specifying the NumBins and LineWidth options. Place the scatter plot in the 'NorthEast' location of the figure by using the ScatterPlotLocation option. Ensure the legend is visible by specifying the LegendVisible option as 'on'.

load patients
tbl = table(LastName,Diastolic,Systolic,SelfAssessedHealthStatus);
s = scatterhistogram(tbl,'Diastolic','Systolic','GroupVariable','SelfAssessedHealthStatus', ...
    'NumBins',4,'LineWidth',1.5,'ScatterPlotLocation','NorthEast','LegendVisible','on');

Group Data Using Two Variables

Create a scatter plot with marginal histograms. Group the data by using a combination of two different variables.

Load the patients data set. Combine the Smoker and Gender data to create a new variable. Create a scatter histogram chart that compares the Diastolic and Systolic values of the patients. Use the new variable SmokerGender to group the data in the scatter histogram chart.

load patients
[idx,genderStatus,smokerStatus] = findgroups(string(Gender),string(Smoker));
SmokerGender = strcat(genderStatus(idx),"-",smokerStatus(idx));
s = scatterhistogram(Diastolic,Systolic,'GroupData',SmokerGender,'LegendVisible','on');
xlabel('Diastolic')
ylabel('Systolic')

Specify Kernel Density Plots

Create a scatter plot with marginal kernel density histograms.

Load the patients data set. Create a table from the Diastolic, Systolic, and Smoker variables.

load patients.mat
tbl = table(Diastolic,Systolic,Smoker);

Create a scatter histogram chart that compares the Diastolic and Systolic pressure values of the patients. Use patient smoking status to group the data and display marginal kernel density plots. The plot shows that smokers have higher average systolic and diastolic blood pressure compared to nonsmokers.

s = scatterhistogram(tbl,"Diastolic","Systolic", ...
    GroupVariable="Smoker",HistogramDisplayStyle="smooth", ...
    LineStyle="-");

Input Arguments

tbl — Source table

table

Source table, specified as a table.

You can create a table from workspace variables using the table function, or you can import data as a table using the readtable function.

The SourceTable property of the ScatterHistogramChart object stores the source table.

xvar — Table variable for x-axis

character vector | string scalar | numeric scalar | logical vector

Table variable for x-axis, specified in one of these forms:

• Character vector or string scalar — Indicating one of the variable names. For example, scatterhistogram(tbl,'Acceleration','Horsepower') selects the variable named 'Acceleration' for the x-axis.

• Numeric scalar — Indicating the table variable index. For example, scatterhistogram(tbl,5,3) selects the fifth variable in the table for the x-axis.

• Logical vector — Containing one true element.

The values associated with your table variable must be of a numeric type or categorical.

The XVariable property of the ScatterHistogramChart object stores the selected variable name.

yvar — Table variable for y-axis

character vector | string scalar | numeric scalar | logical vector

Table variable for y-axis, specified in one of these forms:

• Character vector or string scalar — Indicating one of the variable names. For example, scatterhistogram(tbl,'Acceleration','Horsepower') selects the variable named 'Horsepower' for the y-axis.

• Numeric scalar — Indicating the table variable index. For example, scatterhistogram(tbl,5,3) selects the third variable in the table for the y-axis.

• Logical vector — Containing one true element.

The values associated with your table variable must be of a numeric type or categorical.

The YVariable property of the ScatterHistogramChart object stores the selected variable name.

grpvar — Table variable for grouping data

character vector | string scalar | numeric scalar | logical vector

Table variable for grouping data, specified in one of these forms:

• Character vector or string scalar — Indicating one of the variable names

• Numeric scalar — Indicating the table variable index

• Logical vector — Containing one true element

The values associated with your table variable must form a numeric vector, logical vector, categorical array, string array, or cell array of character vectors.

grpvar splits the data in xvar and yvar into unique groups. Each group has a default color and an independent histogram in each axis. In the legend, scatterhistogram displays the group names in order of their first appearance in GroupData.

Example: 'Model_Year'

Example: 2

xvalues — Values appearing along x-axis

numeric vector | categorical array

Values appearing along the x-axis, specified as a numeric vector or categorical array.

The XData property of the ScatterHistogramChart object stores the xvalues data.

Example: [0.5 4.3 2.4 5.6 3.4]

Example: categorical({'small','medium','small','large','medium','small'})

yvalues — Values appearing along y-axis

numeric vector | categorical array

Values appearing along the y-axis, specified as a numeric vector or categorical array.

The YData property of the ScatterHistogramChart object stores the yvalues data.

Example: [0.5 4.3 2.4 5.6 3.4]

Example: categorical({'small','medium','small','large','medium','small'})

grpvalues — Group values

numeric vector | logical vector | categorical array | string array | cell array of character vectors

Group values for the scatter plot and the corresponding marginal histograms, specified as a numeric vector, logical vector, categorical array, string array, or cell array of character vectors.

grpvalues splits the data in xvalues and yvalues into unique groups. Each group has a default color and an independent histogram in each axis. In the legend, scatterhistogram displays the group names in order of their first appearance in GroupData.

Example: [1 2 1 3 2 1 3]

Example: categorical({'blue','green','green','blue','green'})

parent — Parent container

Figure object | Panel object | Tab object | TiledChartLayout object | GridLayout object

Parent container, specified as a Figure, Panel, Tab, TiledChartLayout, or GridLayout object.

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.

Before R2021a, use commas to separate each name and value, and enclose Name in quotes.

Example: scatterhistogram(tbl,xvar,yvar,'GroupVariable',grpvar,'HistogramDisplayStyle','stairs') specifies grpvar as the grouping variable and displays stairstep plots next to the scatter plot.

Note

The properties listed here are only a subset. For a complete list, see ScatterHistogramChart Properties.

Title — Chart title

'' (default) | character vector | string array | cell array of character vectors | categorical array

Chart title, specified as a character vector, string array, cell array of character vectors, or categorical array. The default chart has no title.

To create a multiline title, specify a string array or cell array of character vectors. Each element in the array corresponds to a line of text.

If you specify the title as a categorical array, MATLAB^® uses the values in the array, not the categories.

Example: s = scatterhistogram(__,'Title','My Title Text')

Example: s.Title = 'My Title Text'

Example: s.Title = {'My','Title'}

NumBins — Number of histogram bins

positive integer scalar | positive integer column vector | positive integer matrix

Number of histogram bins, specified as a positive integer scalar, 2-by-1 positive integer vector, or 2-by-n positive integer matrix, where n is the number of groups in GroupData.

Specified Value	Description
scalar	The value is the number of bins for the x and y histograms.
2-by-1 vector	The first value is the number of bins for the x data, and the second value is the number of bins for the y data.
2-by-n matrix	The (1,j) value is the number of bins for the histogram of the x data that is in the jth group. Similarly, the (2,j) value is the number of bins for the histogram of the y data that is in the jth group.

scatterhistogram uses the 'BinMethod','auto' name-value pair argument of histogram to determine the default NumBins and BinWidths values.

You cannot change NumBins for categorical data.

Example: s = scatterhistogram(__,'NumBins',20)

Example: s.NumBins = [10; 15]

HistogramDisplayStyle — Histogram display style

'stairs' (default) | 'bar' | 'smooth'

Histogram display style, specified as one of these options.

Display Style	Description
'stairs'	Display a stairstep plot that shows the outline of the histogram without filling the bars.
'bar'	Display a histogram bar plot.
'smooth'	Display a smooth plot generated through kernel density estimates.

scatterhistogram uses the 'pdf' type of normalization to generate the histograms. For more information, see the 'Normalization' name-value pair argument of histogram.

Example: s = scatterhistogram(__,'HistogramDisplayStyle','smooth')

Example: s.HistogramDisplayStyle = 'bar'

LineWidth — Histogram line width

positive scalar | positive vector

Histogram line width, specified as a positive scalar or positive vector in points. By default, scatterhistogram assigns a line width of 0.5 to each histogram plot line.

When the total number of groups exceeds the number of specified line widths, scatterhistogram cycles through the specified line widths.

Example: s = scatterhistogram(__,'LineWidth',0.75)

Example: s.LineWidth = [0.5 0.75 0.5]

MarkerStyle — Marker symbol

character vector | string array | cell array of character vectors

Marker symbol for each scatter plot group, specified in one of these forms:

• Character vector designating a marker style

• String array or cell array of character vectors designating one or more marker styles

Choose among these marker options.

Marker	Description	Resulting Marker
"o"	Circle
"+"	Plus sign
"*"	Asterisk
"."	Point
"x"	Cross
"_"	Horizontal line
"|"	Vertical line
"square"	Square
"diamond"	Diamond
"^"	Upward-pointing triangle
"v"	Downward-pointing triangle
">"	Right-pointing triangle
"<"	Left-pointing triangle
"pentagram"	Pentagram
"hexagram"	Hexagram
"none"	No markers	Not applicable

By default, scatterhistogram assigns the marker symbol 'o' to each group in the scatter plot. When the total number of groups exceeds the number of specified symbols, scatterhistogram cycles through the specified symbols.

Example: s = scatterhistogram(__,'MarkerStyle','x')

Example: s.MarkerStyle = {'x','o'}

ScatterPlotLocation — Location of scatter plot

'SouthWest' (default) | 'SouthEast' | 'NorthEast' | 'NorthWest'

Location of the scatter plot, specified as one of these options.

Location	Description
'SouthWest'	Plot the histograms above and to the right of the scatter plot.
'SouthEast'	Plot the histograms above and to the left of the scatter plot.
'NorthEast'	Plot the histograms below and to the left of the scatter plot.
'NorthWest'	Plot the histograms below and to the right of the scatter plot.

Example: s = scatterhistogram(__,'ScatterPlotLocation','NorthEast')

Example: s.ScatterPlotLocation = 'SouthEast'

LegendVisible — State of legend visibility

'on' | 'off'

State of legend visibility, specified as 'on' or 'off'. Set LegendVisible to 'on' to display the legend or 'off' to hide the legend.

If GroupData is empty ([]) or contains a single group, then scatterhistogram does not display a legend. Otherwise, scatterhistogram displays a legend by default, unless the legend overlaps the scatter plot or marginal histograms.

In the legend, scatterhistogram displays the group names in order of their first appearance in GroupData.

Example: s = scatterhistogram(__,'LegendVisible','on')

Example: s.LegendVisible = 'off'

Output Arguments

s — Scatter plot with histograms

ScatterHistogramChart object

ScatterHistogramChart object, which is a standalone visualization. Use s to modify the object after you create it. For a list of properties, see ScatterHistogramChart Properties.

More About

Standalone Visualization

A standalone visualization is a chart designed for a special purpose that works independently from other charts. Unlike other charts such as plot and surf, a standalone visualization has a preconfigured axes object built into it, and some customizations are not available. A standalone visualization also has these characteristics:

• It cannot be combined with other graphics elements, such as lines, patches, or surfaces. Thus, the hold command is not supported.

• The gca function can return the chart object as the current axes.

• You can pass the chart object to many MATLAB functions that accept an axes object as an input argument. For example, you can pass the chart object to the title function.

Tips

• To interactively explore the data in your ScatterHistogramChart object, use these options. Some of these options are not available in the Live Editor.

  • Zoom/pan — Use the scroll wheel or the + and - buttons to zoom. Click and drag the scatter plot to pan. scatterhistogram updates the marginal histograms based on the data within the current scatter plot limits.

  • Data tips — Hover over the scatter plot or marginal histograms to display a data tip.

• If you create a scatter plot with marginal histograms from a table, then you can customize data tips for the scatter plot.

  • To add or remove a row from the data tip, right-click anywhere on the scatter plot and point to Modify Data Tips. Then, select or deselect a variable.

  • To add or remove multiple rows, right-click on the plot, point to Modify Data Tips, and select More. Then, add variables by clicking >> or remove them by clicking <<.

Version History

Introduced in R2018b

R2024a: Kernel density estimation no longer requires Statistics Toolbox

Starting in R2024a, you can specify the HistogramDisplayStyle name-value argument as "smooth" without a Statistics and Machine Learning Toolbox™ license.