Scatter plot by group
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Syntax
gscatter(x,y,g)
gscatter(x,y,g,clr,sym,siz)
gscatter(x,y,g,clr,sym,siz,doleg)
gscatter(x,y,g,clr,sym,siz,doleg,xnam,ynam)
gscatter(ax,___)
gscatter(___,"filled")
h = gscatter(___)
Description
example
gscatter(x,y,g)
creates a scatter plot of x
and y
, grouped by g
. The inputs x
and y
are vectors of the same size.
example
gscatter(x,y,g,clr,sym,siz)
specifies the marker color clr
, symbol sym
, and size siz
for each group.
gscatter(x,y,g,clr,sym,siz,doleg)
controls whether a legend is displayed on the graph. gscatter
creates a legend by default.
example
gscatter(x,y,g,clr,sym,siz,doleg,xnam,ynam)
specifies the names to use for the x-axis and y-axis labels. If you do not provide xnam
and ynam
, and the x
and y
inputs are variables with names, then gscatter
labels the axes with the variable names.
example
gscatter(ax,___)
uses the plot axes specified by the axes object ax
. Specify ax
as the first input argument followed by any of the input argument combinations in the previous syntaxes.
gscatter(___,"filled")
fills in marker interiors. gscatter
ignores this option for markers that do not have interiors.
example
h = gscatter(___)
returns graphics handles corresponding to the groups in g.
You can pass in []
for clr, sym, and siz to use their default values.
Examples
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Scatter Plot with Default Settings
Open Live Script
Load the carsmall
data set.
load carsmall
Plot the Displacement
values on the x-axis and the Horsepower
values on the y-axis. gscatter
uses the variable names as the default labels for the axes. Group the data points by Model_Year
.
gscatter(Displacement,Horsepower,Model_Year)
Scatter Plot with One Grouping Variable
Open Live Script
Load the discrim
data set.
load discrim
The data set contains ratings of cities according to nine factors such as climate, housing, education, and health. The matrix ratings
contains the ratings information.
Plot the relationship between the ratings for climate (first column) and housing (second column) grouped by city size in the matrix group
. Choose different colors and plotting symbols for each group.
gscatter(ratings(:,1),ratings(:,2),group,'br','xo')xlabel('climate')ylabel('housing')
Scatter Plot with Multiple Grouping Variables
Open Live Script
Load the hospital
data set.
load hospital
Plot the ages and weights of the hospital patients. Group the patients according to their gender and smoker status. Use the o
symbol to represent nonsmokers and the *
symbol to represent smokers.
x = hospital.Age;y = hospital.Weight;g = {hospital.Sex,hospital.Smoker};gscatter(x,y,g,'rkgb','o*',8,'on','Age','Weight')legend('Location','northeastoutside')
Specify Axes for Scatter Plot
Open Live Script
Load the carsmall
data set. Create a figure with two subplots and return the axes
objects as ax1
and ax2
. Create a scatter plot in each set of axes by referring to the corresponding Axes
object. In the left subplot, group the data using the Model_Year
variable. In the right subplot, group the data using the Cylinders
variable. Add a title to each plot by passing the corresponding Axes
object to the title
function.
load carsmallcolor = lines(6); % Generate color valuesax1 = subplot(1,2,1); % Left subplotgscatter(ax1,Acceleration,MPG,Model_Year,color(1:3,:))title(ax1,'Left Subplot (Model Year)')ax2 = subplot(1,2,2); % Right subplotgscatter(ax2,Acceleration,MPG,Cylinders,color(4:6,:))title(ax2,'Right Subplot (Cylinders)')
Specify Marker Colors
Open Live Script
Specify marker colors using the colormap determined by the hsv function.
Load the Lidar scan data set which contains the coordinates of objects surrounding a vehicle, stored as a collection of 3-D points.
load('lidar_subset.mat') loc = lidar_subset;
To highlight the environment around the vehicle, set the region of interest to span 20 meters to the left and right of the vehicle, 20 meters in front and back of the vehicle, and the area above the surface of the road.
xBound = 20; % in metersyBound = 20; % in meterszLowerBound = 0; % in meters
Crop the data to contain only points within the specified region.
indices = loc(:,1) <= xBound & loc(:,1) >= -xBound ... & loc(:,2) <= yBound & loc(:,2) >= -yBound ... & loc(:,3) > zLowerBound;loc = loc(indices,:);
Cluster the data by using dbscan
with pairwise distances.
D = pdist2(loc,loc);idx = dbscan(D,2,50,'Distance','precomputed');
Visualize the resulting clusters as a 2-D group scatter plot by using the gscatter
function. By default, gscatter
uses the seven MATLAB default colors. If the number of unique clusters exceeds seven, the function cycles through the default colors as needed. Find the number of clusters, and generate the corresponding number of colors by using the hsv
function. Specify marker colors to use a unique color for each cluster.
numGroups = length(unique(idx));clr = hsv(numGroups);gscatter(loc(:,1),loc(:,2),idx,clr)xlabel('x')ylabel('y')
Create and Modify Scatter Plot
Open Live Script
Load the carbig
data set.
load carbig
Create a scatter plot comparing Acceleration
to MPG
. Group data points based on Origin
.
h = gscatter(Acceleration,MPG,Origin)
h = 7x1 Line array: Line (USA) Line (France) Line (Japan) Line (Germany) Line (Sweden) Line (Italy) Line (England)
Display the Line
object corresponding to the group labeled (Japan)
.
jgroup = h(3)
jgroup = Line (Japan) with properties: Color: [0.9290 0.6940 0.1250] LineStyle: 'none' LineWidth: 0.5000 Marker: '.' MarkerSize: 15 MarkerFaceColor: 'none' XData: [15 14.5000 14.5000 14 19 18 15.5000 13.5000 17 14.5000 16.5000 19 16.5000 13.5000 13.5000 19 21 16.5000 19 15 15.5000 16 13.5000 17 17.5000 17.4000 17 16.4000 15.5000 18.5000 16.8000 18.2000 16.4000 14.5000 ... ] (1x79 double) YData: [24 27 27 25 31 35 24 19 28 23 27 20 22 18 20 31 32 31 32 24 26 29 24 24 33 33 32 28 19 31.5000 33.5000 26 30 22 21.5000 32.8000 39.4000 36.1000 27.5000 27.2000 21.1000 23.9000 29.5000 34.1000 31.8000 38.1000 ... ] (1x79 double) Use GET to show all properties
Change the marker color for the Japan
group to black.
jgroup.Color = 'k';
Input Arguments
collapse all
x
— x-axis values
numeric vector
x-axis values, specified as a numeric vector. x
must have the same size as y.
Data Types: single
| double
y
— y-axis values
numeric vector
y-axis values, specified as a numeric vector. y
must have the same size as x.
Data Types: single
| double
g
— Grouping variable
categorical vector | logical vector | numeric vector | character array | string array | cell array of character vectors | cell array
Grouping variable, specified as a categorical vector, logical vector, numeric vector, character array, string array, or cell array of character vectors. Alternatively, g
can be a cell array containing several grouping variables (such as {g1 g2 g3}
), in which case observations are in the same group if they have common values of all grouping variables. Points in the same group appear on the scatter plot with the same marker color, symbol, and size.
The number of rows in g
must be equal to the length of x.
Example: species
Example: {Cylinders,Origin}
Data Types: categorical
| logical
| single
| double
| char
| string
| cell
clr
— Marker colors
MATLAB® default colors (default) | character vector or string scalar of short color names | matrix of RGB triplets
Marker colors, specified as a character vector or string scalar of short color names or a matrix of RGB triplets.
For a custom color, specify a matrix of RGB triplets. An RGB triplet is a three-element row vector whose elements specify the intensities of the red, green, and blue components of the color. The intensities must be in the range [0,1]
; for example, [0.4 0.6 0.7]
.
Alternatively, you can specify some common colors by name. This table lists the named color options and the equivalent RGB triplets
Short Name | RGB Triplet | Appearance |
---|---|---|
'r' | [1 0 0] | |
'g' | [0 1 0] | |
'b' | [0 0 1] | |
'c' | [0 1 1] | |
'm' | [1 0 1] | |
'y' | [1 1 0] | |
'k' | [0 0 0] | |
'w' | [1 1 1] | |
Here are the RGB triplet color codes for the default colors MATLAB uses in many types of plots.
RGB Triplet | Appearance |
---|---|
[0 0.4470 0.7410] | |
[0.8500 0.3250 0.0980] | |
[0.9290 0.6940 0.1250] | |
[0.4940 0.1840 0.5560] | |
[0.4660 0.6740 0.1880] | |
[0.3010 0.7450 0.9330] | |
[0.6350 0.0780 0.1840] | |
The default value for clr
is the matrix of RGB triplets containing the MATLAB default colors.
If you do not specify enough colors for all unique groups in g, then gscatter
cycles through the specified values in clr
. If you use default values when the number of unique groups exceeds the number of default colors (7), then gscatter
cycles through the default values as needed.
Example: 'rgb'
Example: [0 0 1; 0 0 0]
Data Types: char
| string
| single
| double
sym
— Marker symbols
'.'
(default) | character vector or string scalar of symbols
Marker symbols, specified as a character vector or string scalar of symbols recognized by the plot
function. This table lists the available marker symbols.
Value | Description |
---|---|
'o' | Circle |
'+' | Plus sign |
'*' | Asterisk |
'.' | Point |
'x' | Cross |
's' | Square |
'd' | Diamond |
'^' | Upward-pointing triangle |
'v' | Downward-pointing triangle |
'>' | Right-pointing triangle |
'<' | Left-pointing triangle |
'p' | Five-pointed star (pentagram) |
'h' | Six-pointed star (hexagram) |
'n' | No markers |
If you do not specify enough values for all groups, then gscatter
cycles through the specified values as needed.
Example: 'o+*v'
Data Types: char
| string
siz
— Marker sizes
positive numeric vector
Marker sizes, specified as a positive numeric vector in points. The default value is determined by the number of observations. If you do not specify enough values for all groups, then gscatter
cycles through the specified values as needed.
Example: [6 12]
Data Types: single
| double
doleg
— Option to include legend
'on'
(default) | 'off'
Option to include a legend, specified as either 'on'
or 'off'
. By default, the legend is displayed on the graph.
xnam
— x-axis label
x
variable name (default) | character vector | string scalar
x-axis label, specified as a character vector or string scalar.
Data Types: char
| string
ynam
— y-axis label
y
variable name (default) | character vector | string scalar
y-axis label, specified as a character vector or string scalar.
Data Types: char
| string
"filled"
— Option to fill interior of markers
"filled"
Option to fill the interior of markers, specified as "filled"
. Use this option with markers that have an interior, such as "o"
and "s"
. gscatter
ignores "filled"
for markers that do not have an interior, such as "."
and "+"
.
Data Types: string
ax
— Axes for plot
Axes
object | UIAxes
object
Axes for the plot, specified as an Axes
or UIAxes
object. If you do not specify ax
, then gscatter
creates the plot using the current axes. For more information on creating an axes object, see axes and uiaxes.
Output Arguments
collapse all
h
— Graphics handles
array of Line
objects
Graphics handles, returned as an array of Line
objects. Each Line
object corresponds to one of the groups in g. You can use dot notation to query and set properties of the line objects. For a list of Line
object properties, see Line Properties.
Version History
Introduced before R2006a
expand all
R2022a: gscatter
uses the MATLAB default color scheme
Starting in R2022a, the gscatter
function uses the MATLAB default color scheme to determine marker colors, following the order specified in the ColorOrder property of the axes.
In previous releases, the gscatter
function uses the colormap returned by the hsv function. If you want to determine marker colors using the hsv
colormap, specify marker colors (fourth input argument of gscatter
) as hsv(numGroups)
, where numGroups
is the number of unique group combinations in the grouping variables.
If you use the new default color scheme and the number of unique groups exceeds the number of default colors (7), then gscatter
cycles through the default values as needed. If you want to use different colors for different groups, specify the marker colors as hsv(numGroups)
. For an example, see Specify Marker Colors.
See Also
gplotmatrix | grpstats | scatter
Topics
- Create Scatter Plots Using Grouped Data
- Perform Multivariate Analysis of Variance (MANOVA)
- Grouping Variables
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