Create Simple Line Plots

Create a table containing three variables. Then pass the table as the first argument to the plot function followed by the names of the variables you want to plot. In this case, plot the Input variable on the x-axis and the Output1 variable on the y-axis. Notice that the axis labels match the variable names.

% Create a table
Input = linspace(0,12)';
Output1 = sin(Input);
Output2 = sin(Input/3);
tbl = table(Input,Output1,Output2);

% Plot the table variables
plot(tbl,"Input","Output1")

To plot multiple data sets together, specify a string vector of table variable names for the x-coordinates, y-coordinates, or both. For example, plot the Output1 and Output2 variables together on the y-axis.

Because the y-coordinates come from two different table variables, it is not clear what the y-axis label should be, so the axis label remains blank. However, if you add a legend, the legend entries match the corresponding variable names.

plot(tbl,"Input",["Output1","Output2"])
legend

Customize Line Plots

To customize the appearance of lines after plotting with a table, set the LineStyle and Color properties. For example, read weather.csv as a timetable and plot the Temperature variable against the row times. Return the Line object as p so you can set its properties later.

Note: This code omits the variable for the x-coordinates. When you omit the x-coordinates, the y-coordinates are plotted against the row indices (for tables) or the row times (for timetables).

tbl = readtimetable("weather.csv");
p = plot(tbl,"Temperature");

Change the style of the line to dashed, and change the color to a shade of purple.

p.LineStyle = "--";
p.Color = [0.5 0 1];

Customize Scatter Plots

You can customize the appearance of the markers in scatter plots by setting properties after plotting with a table. For example, read patients.xls as a table and plot the Diastolic variable against the Systolic variable with filled markers. Return the Scatter object as s so you can set its properties later.

tbl = readtable("patients.xls");
s = scatter(tbl,"Systolic","Diastolic","filled");

Change the marker symbol to a square, fill the markers with a shade of light blue, and change the marker size to 80.

s.Marker = "sq";
s.MarkerFaceColor = [0.5 0.7 1];
s.SizeData = 80;

You can also vary the color and transparency of the markers according to table variables. For example, vary the colors according to the Age variable by setting the MarkerFaceColor property to "flat" and then setting the ColorVariable property to "Age".

Vary the transparency according to the Weight variable by setting the MarkerFaceAlpha property to "flat" and then setting the AlphaVariable property to "Weight".

% Vary the colors
s.MarkerFaceColor = "flat";
s.ColorVariable = "Age";

% Vary the transparency
s.MarkerFaceAlpha = "flat";
s.AlphaVariable = "Weight";

Update Plot by Modifying the Table

When you pass a table to a plotting function, a copy of the table is stored in the SourceTable property of the plot object. If you change the contents of the table stored in that property, the plot automatically updates to show the changes. (However, if you make changes to the table in your workspace, those changes have no effect on your plot.)

For example, read patients.xls as a table and plot the Weight variable versus the Height variable. Return the Scatter object as s, so you can access its properties later.

tbl = readtable("patients.xls");
s = scatter(tbl,"Height","Weight","filled");

To change a value in the table, use dot notation to reference the table from the SourceTable property of the Scatter object. In this case, find the maximum value of the Weight variable and change it to 300. The plot automatically updates.

[~,idx] = max(s.SourceTable.Weight);
s.SourceTable.Weight(idx) = 300;

Combine Table and Vector Data

Many plots that support tables allow you to specify some aspects of your plot using a table variable and other aspects using vectors or matrices. For instance, you can create a scatter plot using coordinates from a table and customize the colors of the markers by setting the CData property to a vector, an RGB triplet, or a matrix of RGB triplets.

For example, create a scatter plot using data from a table. Read patients.xls as a table, and plot the Weight variable versus the Height variable.

tbl = readtable("patients.xls");
s = scatter(tbl,"Height","Weight","filled");

Next, change the colors of the plotted points using a vector. When you combine data from different sources like this, the size of each vector, matrix, or table variable must be compatible with the plot you are creating. In this case, create a vector called bpratio by dividing the systolic values by the diastolic values from the table. Because bpratio is derived from the same table as the Height and Weight variables, it has the same number of elements as those variables, and so it is compatible with this plot.

Color each point according to the blood pressure ratio by setting the CData property to bpratio. Then add a colorbar.

% Vary the color by blood pressure ratio
bpratio = tbl.Systolic./tbl.Diastolic;
s.CData = bpratio;

% Add a colorbar
colorbar

You can also plot vectors or matrices, and modify the plot using table variables. After you create the plot, set the SourceTable property, and then set the table-related properties that you want. Table-related properties typically have the word Variable in their names. For example, plot two vectors of 100 random numbers.

x = rand(100,1);
y = rand(100,1);
s = scatter(x,y,"filled");

Change the marker colors so that they vary according to the values in a table variable. Read patients.xls as the table tbl. Set the SourceTable property and vary the marker colors according to the Age variable in the table. Because the table has 100 rows, and the plot has 100 points, the Age variable is compatible with the plot. Then, add a colorbar to the plot.

% Set source table and vary color by age
s.SourceTable = tbl;
s.ColorVariable = "Age";

% Add a colorbar
colorbar

Note: Standalone visualizations such as heatmap do not support combinations of table and vector data.