Main Content

heatmap

Create heatmap chart

  • Heatmap chart

Description

example

heatmap(tbl,xvar,yvar) creates a heatmap 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. The default colors are based on a count aggregation, which totals the number of times each pair of x and y values appears together in the table.

example

heatmap(tbl,xvar,yvar,'ColorVariable',cvar) uses the table variable specified by cvar to calculate the color data. The default calculation method is a mean aggregation.

example

heatmap(cdata) creates a heatmap from matrix cdata. The heatmap has one cell for each value in cdata.

example

heatmap(xvalues,yvalues,cdata) specifies the labels for the values that appear along the x-axis and y-axis.

example

heatmap(___,Name,Value) specifies additional options for the heatmap using one or more name-value pair arguments. Specify the options after all other input arguments. For a list of properties, see HeatmapChart Properties.

heatmap(parent,___) creates the heatmap in the figure, panel, or tab specified by parent.

h = heatmap(___) returns the HeatmapChart object. Use h to modify properties of the chart after creating it. For a list of properties, see HeatmapChart Properties.

Examples

collapse all

Create a heatmap 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 heatmap that counts the total number of patients with the same set of Smoker and SelfAssessedHealthStatus values.

load patients
tbl = table(LastName,Age,Gender,SelfAssessedHealthStatus,...
    Smoker,Weight,Location);
h = heatmap(tbl,'Smoker','SelfAssessedHealthStatus');

Figure contains an object of type heatmap. The chart of type heatmap has title Count of SelfAssessedHealthStatus vs. Smoker.

Create a heatmap and reorder the labels along the y-axis.

Load the patients data set and create a heatmap from the data. Assign the HeatmapChart object to the variable h.

load patients
tbl = table(LastName,Age,Gender,SelfAssessedHealthStatus,...
    Smoker,Weight,Location);
h = heatmap(tbl,'Smoker','SelfAssessedHealthStatus');

Figure contains an object of type heatmap. The chart of type heatmap has title Count of SelfAssessedHealthStatus vs. Smoker.

Reorder the labels along the y-axis.

h.YDisplayData = {'Excellent','Good','Fair','Poor'};

Figure contains an object of type heatmap. The chart of type heatmap has title Count of SelfAssessedHealthStatus vs. Smoker.

Alternatively, you can reorder the labels by changing the data to categorical data and then reordering the categories using the reordercats function. Similarly, you can add, remove, or rename the heatmap labels using the addcats, removecats, or renamecats functions, respectively.

Create a heatmap and specify the table variable to use when determining the heatmap cell colors.

Load the patients data set and create a heatmap from the data. Color each cell using the average age of patients with a particular pair of Smoker and SelfAssessedHealthStatus values by setting the ColorVariable option to 'Age'.

load patients
tbl = table(LastName,Age,Gender,SelfAssessedHealthStatus,...
    Smoker,Weight,Location);

h = heatmap(tbl,'Smoker','SelfAssessedHealthStatus',...
    'ColorVariable','Age');

Figure contains an object of type heatmap. The chart of type heatmap has title Mean of Age.

Create a heatmap and specify the table variable and calculation method to use when determining the heatmap cell colors.

Load the patients data set and create a heatmap from the data. Color each cell using the median age of patients with a particular pair of Smoker and SelfAssessedHealthStatus values. Specify the ColorVariable option as 'Age' and the ColorMethod option as 'median'.

load patients
tbl = table(LastName,Age,Gender,SelfAssessedHealthStatus,...
    Smoker,Weight,Location);
h = heatmap(tbl,'Smoker','SelfAssessedHealthStatus',...
    'ColorVariable','Age','ColorMethod','median');

Figure contains an object of type heatmap. The chart of type heatmap has title Median of Age.

Create a matrix of data. Then create a heatmap of the matrix values. The default labels along the x-axis and y-axis appear as 1, 2, 3, and so on.

cdata = [45 60 32; 43 54 76; 32 94 68; 23 95 58];
h = heatmap(cdata);

Create a matrix of data. Then create a heatmap of the matrix values. Use custom labels along the x-axis and y-axis by specifying the first two input arguments as the labels you want. Specify the title and axis labels by setting properties of the HeatmapChart object.

cdata = [45 60 32; 43 54 76; 32 94 68; 23 95 58];
xvalues = {'Small','Medium','Large'};
yvalues = {'Green','Red','Blue','Gray'};
h = heatmap(xvalues,yvalues,cdata);

h.Title = 'T-Shirt Orders';
h.XLabel = 'Sizes';
h.YLabel = 'Colors';

Figure contains an object of type heatmap. The chart of type heatmap has title T-Shirt Orders.

Since R2023b

To use LaTeX (or TeX) markup in the title, axis labels, or data tips, set the Interpreter property of the HeatmapChart object.

For example, create a heatmap chart with a title that uses LaTeX to display Greek letters. Set the Interpreter property to "latex" when you create the chart. Then include the markup when you call the title function.

heatmap(randi(100,5,3),Interpreter="latex")
title("$\hat{\psi_1}$ Values for ${1\le\alpha\le3}$")

Figure contains an object of type heatmap. The chart of type heatmap has title $\hat{\psi_1}$ Values for ${1\le\alpha\le3}$.

Create a heatmap and normalize the colors along each column or row by setting the ColorScaling property.

Read the sample file outages.csv into a table. The sample file contains data representing electric utility outages in the Unites States. The table contains six columns: Region, OutageTime, Loss, Customers, RestorationTime, and Cause. Display the first five rows of each column.

T = readtable('outages.csv');
T(1:5,:)
ans=5×6 table
       Region             OutageTime          Loss     Customers       RestorationTime              Cause       
    _____________    ____________________    ______    __________    ____________________    ___________________

    {'SouthWest'}    01-Feb-2002 12:18:00    458.98    1.8202e+06    07-Feb-2002 16:50:00    {'winter storm'   }
    {'SouthEast'}    23-Jan-2003 00:49:00    530.14    2.1204e+05                     NaT    {'winter storm'   }
    {'SouthEast'}    07-Feb-2003 21:15:00     289.4    1.4294e+05    17-Feb-2003 08:14:00    {'winter storm'   }
    {'West'     }    06-Apr-2004 05:44:00    434.81    3.4037e+05    06-Apr-2004 06:10:00    {'equipment fault'}
    {'MidWest'  }    16-Mar-2002 06:18:00    186.44    2.1275e+05    18-Mar-2002 23:23:00    {'severe storm'   }

Create a heatmap that shows the different regions along the x-axis and the different outage causes along the y-axis. In each cell, show how many times each region experienced a power outage due to a particular cause.

h = heatmap(T,'Region','Cause');

Figure contains an object of type heatmap. The chart of type heatmap has title Count of Cause vs. Region.

Normalize the colors along each column. The smallest value in each column maps to the first color in the colormap and the largest value maps to the last color. The last color indicates the cause that caused the most power outages for each region.

h.ColorScaling = 'scaledcolumns';

Figure contains an object of type heatmap. The chart of type heatmap has title Count of Cause vs. Region.

Normalize the colors along each row instead. The smallest value in each row maps to the first color in the colormap and the largest value maps to the last color. The last color indicates the region that experienced the most power outages due to each cause.

h.ColorScaling = 'scaledrows';

Figure contains an object of type heatmap. The chart of type heatmap has title Count of Cause vs. Region.

Create a heatmap and color the cells using data computed with a custom aggregation method. Use the pivot function to compute the color data.

Read the sample file TemperatureData.csv into a table. The file contains four columns: Year, Month, Day, and TemperatureF.

tbl = readtable('TemperatureData.csv');

Compute the color data as the maximum temperature for each month and year combination using the pivot function. Use NaN for missing month and year combinations.

P = pivot(tbl,Columns="Month",Rows="Year",DataVariable="TemperatureF",Method=@(x) mean(x,"includenan"))
P=2×13 table
    Year    April     August    December    February    January     July      June     March      May      November    October    September
    ____    ______    ______    ________    ________    _______    ______    ______    ______    ______    ________    _______    _________

    2015    43.267    69.903     40.548      15.448     21.355     69.161    59.967    28.484    57.548      43.8      49.323      64.467  
    2016    42.267       NaN        NaN      29.966      27.71     68.824    63.733    37.806    53.806       NaN         NaN         NaN  

Rearrange the variables in the pivoted table.

P = P(:,["Year" "January" "February" "March" "April" "May" "June" "July" "August" "September" "October" "November" "December"]);

Create the heatmap, and color the heatmap cells using the computed data values.

xvar = P.Properties.VariableNames(2:end);
yvar = string(P.(1));
cvar = P{:,2:end};
heatmap(xvar,yvar,cvar)
title("Maximum Temperatures (F)")

Heatmap charts use the 256-sampling of the sky colormap by default. You can change the sampling by specifying the Colormap name-value argument.

For example, create two heatmap charts in a 2-by-1 tiled chart layout. The top chart uses the default set of 256 colors, and the bottom chart uses only two colors.

tiledlayout(2,1,TileSpacing="compact")

% Top chart with default colors
nexttile
heatmap(magic(10))

% Bottom chart with two colors
nexttile
heatmap(magic(10),Colormap=sky(2))

Figure contains objects of type heatmap.

Input Arguments

collapse all

Source table, specified as a table or timetable.

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

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

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

  • Character vector or string scalar indicating one of the variable names. For example, heatmap(tbl,'HealthStatus','Gender') selects the variable named 'HealthStatus' for the x-axis.

  • Numeric scalar indicating the table variable index. For example, heatmap(tbl,2,3) selects the second variable in the table for the x-axis.

  • Logical vector containing one true element.

The values associated with your table variable must be grouped into a finite set of discrete categories that the categorical function accepts. If the values are not grouped into a finite set of categories, use the discretize function to group them.

The labels that appear along the x-axis are in alphabetical order. You can customize the labels using categorical arrays. For an example, see Create Heatmap from Tabular Data.

The XVariable property of the HeatmapChart object stores the selected variable.

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

  • Character vector or string scalar of one of the variable names. For example, heatmap(tbl,'HealthStatus','Gender') selects the variable named 'Gender' for the y-axis.

  • Numeric scalar indicating the table variable index. For example, heatmap(tbl,2,3) 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 grouped into a finite set of discrete categories that the categorical function accepts. If the values are not grouped into a finite set of categories, use the discretize function to group them.

The labels that appear along the y-axis are in alphabetical order. You can customize the labels using categorical arrays. For an example, see Create Heatmap from Tabular Data.

The YVariable property of the HeatmapChart object stores the selected variable.

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

  • A character vector or string scalar of one of the variable names. For example, heatmap(__,'ColorVariable','HealthStatus') selects the variable named 'HealthStatus' for the y-axis.

  • A numeric scalar indicating the table variable index. For example, heatmap(__,'ColorVariable',1) selects the third variable in the table for the y-axis.

  • A logical vector containing one true element.

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

The property value is empty [] when using matrix data. The ColorVariable property of the HeatmapChart object stores the selected variable. The ColorData property populates with data based on the selected variable.

By default, heatmap calculates the color data based on a mean aggregation. To change the calculation method, set the ColorMethod property.

Color data for the heatmap cells, specified as a matrix.

The ColorData property of the HeatmapChart object stores the values.

Example: [40 24 68; 68 37 58; 49 23 46]

Values appearing along the x-axis, specified as a categorical array, string array, numeric array, or cell array of character vectors.

Example: {'small','medium','large'}

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

Values appearing along y-axis, specified as a categorical array, string array, numeric array, or cell array of character vectors.

Example: {'small','medium','large'}

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

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: heatmap(tbl,xvar,yvar,'ColorVariable','Temperatures','ColorMethod','median')

Note

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

Chart title, specified as a character vector, cell array of character vectors, string array, or categorical array.

Example: h = heatmap(rand(10,10),'Title','My Title Text')

Example: h.Title = 'My Title Text';

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

Example: h.Title = {'My','Title'};

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

If you create the chart using tabular data, the default chart has an autogenerated title. If you do not want a title, specify ''.

By default, heatmaps support a subset of TeX markup for the text you specify. Use TeX markup to add superscripts and subscripts, modify the font type and color, and include special characters in the text. If you want a TeX markup character in regular text, such as an underscore (_), then insert a backslash (\) before the character you want to include. The backslash is the TeX escape character. For more information, see the Interpreter property of the text object.

Method to calculate the color data values (stored in ColorData), specified as 'count', 'mean', 'median', 'sum', 'max', 'min', or 'none'.

If you do not want to use a third variable from the table for the color data, then specify the method as 'count'. When the method is 'count', the heatmap does not use the ColorVariable property and instead counts the number of times each pair of x and y values appears in the source table. This value is the default value when you are using tabular data and do not specify the ColorVariable parameter.

If you want to use a third variable from the table for the color data, then set the ColorVariable property to the variable you want and specify the ColorMethod property as one of the methods listed in this table. For each pair of x and y values, the methods use the corresponding values in the ColorVariable column of the source table to calculate the data.

MethodDescription
'mean'Calculate the average value. This value is the default value when you specify the ColorVariable property.
'median'Calculate the median value.
'sum'Sum the values.
'max'Use the maximum value.
'min'Use the minimum value.
'none'Use the value exactly. The table cannot contain more than one instance of each pair of x and y values. This value is the default value when using matrix data.

If you want to compute your own matrix of aggregated data, use the accumarray function. Specify the matrix as input to the heatmap function.

Example: h = heatmap(__,'ColorMethod','median')

Example: h.ColorMethod = 'median'

Output Arguments

collapse all

HeatmapChart object, which is a standalone visualization. Use h to set properties on the heatmap chart after creating it.

More About

collapse all

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 heatmap, use these options.

    • Zoom — Use the scroll wheel or the + and - keys to zoom.

    • Pan — Click and drag the heatmap or use the arrow keys to pan across the rows or columns.

    • Data tips — Hover over the heatmap to display a data tip.

    • Rearrange rows and columns — Click and drag a row or column label to move it to a different position.

    • Sort values — Click the icon that appears when you hover over the row or column label. Click once to sort the values in ascending order, twice to sort the values in descending order, and a third time to reset the order.

  • If you create a heatmap chart from a table, then you can customize its data tips.

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

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

Version History

Introduced in R2017a

expand all