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# swarmchart

Swarm scatter chart

• ## Syntax

``swarmchart(x,y)``
``swarmchart(x,y,sz)``
``swarmchart(x,y,sz,c)``
``swarmchart(___,mkr)``
``swarmchart(___,'filled')``
``swarmchart(___,Name,Value)``
``swarmchart(ax,___)``
``s = swarmchart(___)``

## Description

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````swarmchart(x,y)` displays a swarm chart, which is a scatter plot with the points offset (jittered) in the `x`-dimension. The points form distinct shapes, and the outline of each shape is similar to a violin plot. Swarm charts help you to visualize discrete `x` data with the distribution of the `y` data. At each location in `x`, the points are jittered based on the kernel density estimate of `y`. To plot one set of points, specify `x` and `y` as vectors of equal length.To plot multiple sets of points on the same set of axes, specify at least one of `x` or `y` as a matrix. ```

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````swarmchart(x,y,sz)` specifies the marker sizes. To plot all the markers with the same size, specify `sz` as a scalar. To plot the markers with different sizes, specify `sz` as a vector or a matrix.```

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````swarmchart(x,y,sz,c)` specifies the marker colors. You can specify one color for all the markers, or you can vary the color. For example, you can plot all red circles by specifying `c` as `'red'`.```

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````swarmchart(___,mkr)` specifies a different marker than the default marker, which is a circle. Specify `mkr` after all the arguments in any of the previous syntaxes.```

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````swarmchart(___,'filled')` fills in the markers. Specify the `'filled'` option after all the arguments in any of the previous syntaxes.```

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````swarmchart(___,Name,Value)` specifies additional properties for the swarm chart using one or more `Name,Value` pair arguments. Specify the properties after all other input arguments. For a list of properties, see Scatter Properties.```

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````swarmchart(ax,___)` displays the swarm chart in the target axes. Specify the axes before all the arguments in any of the previous syntaxes.```

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````s = swarmchart(___)` returns the `Scatter` object or an array of `Scatter` objects. Use `s` to modify properties of the chart after creating it. For a list of properties, see Scatter Properties.```

## Examples

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Create a vector of `x` coordinates, and use the `randn` function to generate normally distributed random values for `y`. Then create a swarm chart of `x` and `y`.

```x = [ones(1,500) 2*ones(1,500) 3*ones(1,500)]; y1 = 2 * randn(1,500); y2 = 3 * randn(1,500) + 5; y3 = 5 * randn(1,500) + 5; y = [y1 y2 y3]; swarmchart(x,y)``` Create three sets of `x` and `y` coordinates. Use the `randn` function to generate random values for `y`.

```x1 = ones(1,500); x2 = 2 * ones(1,500); x3 = 3 * ones(1,500); y1 = 2 * randn(1,500); y2 = [randn(1,250) randn(1,250) + 4]; y3 = 5 * randn(1,500) + 5;```

Create a swarm chart of the first data set, and specify a uniform marker size of `5`. Then call `hold on` to plot the second and third data sets together with the first data set. Call `hold off` to release the hold state of the axes.

```swarmchart(x1,y1,5) hold on swarmchart(x2,y2,5) swarmchart(x3,y3,5) hold off``` Read the `BicycleCounts.csv` data set into a timetable called `tbl`. This data set contains bicycle traffic data over a period of time. Display the first five rows of `tbl`.

```tbl = readtable(fullfile(matlabroot,'examples','matlab','data','BicycleCounts.csv')); tbl(1:5,:)```
```ans=5×5 table Timestamp Day Total Westbound Eastbound ___________________ _____________ _____ _________ _________ 2015-06-24 00:00:00 {'Wednesday'} 13 9 4 2015-06-24 01:00:00 {'Wednesday'} 3 3 0 2015-06-24 02:00:00 {'Wednesday'} 1 1 0 2015-06-24 03:00:00 {'Wednesday'} 1 1 0 2015-06-24 04:00:00 {'Wednesday'} 1 1 0 ```

Create a vector `x` with the day name from each observation, and another vector y with the bicycle traffic observed. Then create a swarm chart of `x` and `y`, and specify the point marker `('.')`. The chart shows the distribution of bicycle traffic according to the day of the week.

```daynames = ["Sunday" "Monday" "Tuesday" "Wednesday" "Thursday" "Friday" "Saturday"]; x = categorical(tbl.Day,daynames); y = tbl.Total; swarmchart(x,y,'.');``` Read the `BicycleCounts.csv` data set into a timetable called `tbl`. Create a vector `x` with the day name for each observation, another vector `y` with the bicycle traffic observed, and a third vector `c` with the hour of the day.

Then create a swarm chart of `x` and `y`, and specify the marker size as `20`. Specify the colors of the markers as vector `c`. The values in the vector index into the figure's colormap. Thus, the colors change according to the hour for each data point. Use the `'filled'` option to fill the markers with color instead of displaying them as hollow circles.

```tbl = readtable(fullfile(matlabroot,'examples','matlab','data','BicycleCounts.csv')); daynames = ["Sunday" "Monday" "Tuesday" "Wednesday" "Thursday" "Friday" "Saturday"]; x = categorical(tbl.Day,daynames); y = tbl.Total; c = hour(tbl.Timestamp); swarmchart(x,y,20,c,'filled');``` Read the `BicycleCounts.csv` data set into a timetable called `tbl`. Create a vector `x` with the day name for each observation, another vector `y` with the bicycle traffic observed, and a third vector `c` with the hour of the day. Then create a swarm chart of `x` and `y`, and specify the marker size as `5`, and the colors of the markers as vector `c`. Call the `swarmchart` function with the return argument `s`, so that you can modify the chart after creating it.

```tbl = readtable(fullfile(matlabroot,'examples','matlab','data','BicycleCounts.csv')); daynames = ["Sunday" "Monday" "Tuesday" "Wednesday" "Thursday" "Friday" "Saturday"]; x = categorical(tbl.Day,daynames); y = tbl.Total; c = hour(tbl.Timestamp); s = swarmchart(x,y,5,c);``` Change the shapes of the clusters at each `x` location, so that the points are uniformly and randomly distributed and the spacing is limited to no more than `0.5` data units.

```s.XJitter = 'rand'; s.XJitterWidth = 0.5;``` Create a pair of `x` and `y` coordinates. Use the `randn` function to generate random values for `y`. Then create a swarm chart with filled markers that are 50% transparent both on their faces and on their edges.

```x1 = ones(1,500); x2 = 2 * ones(1,500); x = [x1 x2]; y1 = 2 * randn(1,500); y2 = [randn(1,250) randn(1,250) + 4]; y = [y1 y2]; swarmchart(x,y,'filled','MarkerFaceAlpha',0.5,'MarkerEdgeAlpha',0.5)``` Read the `BicycleCounts.csv` data set into a timetable called `tbl`. This data set contains bicycle traffic data over a period of time. Display the first five rows of `tbl`.

```tbl = readtable(fullfile(matlabroot,'examples','matlab','data','BicycleCounts.csv')); tbl(1:5,:)```
```ans=5×5 table Timestamp Day Total Westbound Eastbound ___________________ _____________ _____ _________ _________ 2015-06-24 00:00:00 {'Wednesday'} 13 9 4 2015-06-24 01:00:00 {'Wednesday'} 3 3 0 2015-06-24 02:00:00 {'Wednesday'} 1 1 0 2015-06-24 03:00:00 {'Wednesday'} 1 1 0 2015-06-24 04:00:00 {'Wednesday'} 1 1 0 ```

Define `x` as a categorical array of the day names in the table. Define `yEast` and `yWest` as vectors containing the eastbound and westbound bicycle traffic counts.

```daynames = ["Sunday" "Monday" "Tuesday" "Wednesday" "Thursday" "Friday" "Saturday"]; x = categorical(tbl.Day,daynames); yEast = tbl.Eastbound; yWest = tbl.Westbound;```

Create a tiled chart layout in the `'flow'` tile arrangement, so that the axes fill the available space in the layout. Call the `nexttile` function to create an axes object and return it as `ax1`. Then create a swarm chart of the eastbound data by passing `ax1` to the `swarmchart` function.

```tiledlayout('flow') ax1 = nexttile; y = tbl.Eastbound; swarmchart(ax1,x,y,'.');``` Repeat the process to create a second axes object and a swarm chart for the westbound traffic.

```ax2 = nexttile; y = tbl.Westbound; s = swarmchart(ax2,x,y,'.');``` ## Input Arguments

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x-coordinates, specified as a scalar, vector, or matrix. The size and shape of `x` depends on the shape of your data. This table describes the most common situations.

Type of PlotHow to Specify Coordinates
Single point

Specify `x` and `y` as scalars. For example:

`swarmchart(1,1)`

One set of points

Specify `x` and `y` as any combination of row or column vectors of the same length. For example:

```x = randi(3,100,1); y = randn(1,100); swarmchart(x,y)```

Multiple sets of points that are different colors

If all the sets share the same x- or y-coordinates, specify the shared coordinates as a vector and the other coordinates as a matrix. The length of the vector must match one of the dimensions of the matrix. For example:

```x = randi(2,1,100); y = [randn(100,1) randn(100,1)+5]; swarmchart(x,y,100)```
If the matrix is square, `swarmchart` plots a separate set of points for each column in the matrix.

Alternatively, specify `x` and `y` as matrices of equal size. In this case, `swarmchart` plots each column of `y` against the corresponding column of `x`. For example:

```x = randi(2,100,2); y = [randn(100,1) randn(100,1)+5]; swarmchart(x,y,100)```

Data Types: `single` | `double` | `int8` | `int16` | `int32` | `int64` | `uint8` | `uint16` | `uint32` | `uint64` | `categorical`

y-coordinates, specified as a scalar, vector, or matrix. The size and shape of `y` depends on the shape of your data. This table describes the most common situations.

Type of PlotHow to Specify Coordinates
Single point

Specify `x` and `y` as scalars. For example:

`swarmchart(1,1)`

One set of points

Specify `x` and `y` as any combination of row or column vectors of the same length. For example:

```x = randi(3,100,1); y = randn(1,100); swarmchart(x,y)```

Multiple sets of points that are different colors

If all the sets share the same x- or y-coordinates, specify the shared coordinates as a vector and the other coordinates as a matrix. The length of the vector must match one of the dimensions of the matrix. For example:

```x = randi(2,1,100); y = [randn(100,1) randn(100,1)+5]; swarmchart(x,y,100)```
If the matrix is square, `swarmchart` plots a separate set of points for each column in the matrix.

Alternatively, specify `x` and `y` as matrices of equal size. In this case, `swarmchart` plots each column of `y` against the corresponding column of `x`. For example:

```x = randi(2,100,2); y = [randn(100,1) randn(100,1)+5]; swarmchart(x,y,100)```

Data Types: `single` | `double` | `int8` | `int16` | `int32` | `int64` | `uint8` | `uint16` | `uint32` | `uint64` | `categorical` | `datetime` | `duration`

Marker size, specified as a numeric scalar, vector, matrix, or empty array (`[]`). The size controls the area of each marker in points squared. An empty array specifies the default size of 36 points. The way you specify the size depends on how you specify `x` and `y`, and how you want the plot to look. This table describes the most common situations.

Desired Marker Sizes`x` and `y` `sz`Example

Same size for all points

Any valid combination of vectors or matrices described for `x` and `y`.

Scalar

Specify `x` as a vector, `y` as a matrix, and `sz` as a scalar.

```x = randi(2,1,100); y = randn(100,1); swarmchart(x,y,100)```

Different size for each point

Vectors of the same length

• A vector with the same length as `x` and `y`.

• A matrix with at least one dimension that matches the lengths of `x` and `y`. Specifying a matrix is useful for displaying multiple markers with different sizes at each (x,y) location.

Specify `x`, `y`, and `sz` as vectors.

```x = randi(2,1,100); y = randn(100,1); sz = randi([70 2000],100,1); swarmchart(x,y,sz)```

Specify `x` and `y` as vectors and `sz` as a matrix.

```x = randi(2,1,100); y = randn(100,1); sz = randi([70 2000],100,2); swarmchart(x,y,sz)```

Different size for each point

At least one of `x` or `y` is a matrix for plotting multiple data sets

• A vector with the same number of elements as there are points in each data set.

• A matrix that has the same size as the `x` or `y` matrix.

Specify `x` as a vector, `y` as a matrix, and `sz` as vector.

```x = randi(2,1,100); y = [randn(100,1) randn(100,1)+5]; sz = randi([70 2000],100,1); swarmchart(x,y,sz)```

Specify `x` as a vector, `y` as a matrix, and `sz` as a matrix the same size as `y`.

```x = randi(2,1,100); y = [randn(100,1) randn(100,1)+5]; sz = randi([70 2000],100,2); swarmchart(x,y,sz)```

Marker color, specified as a color name, RGB triplet, matrix of RGB triplets, or a vector of colormap indices.

• Color name — A color name such as `'red'`, or a short name such as `'r'`.

• RGB triplet — 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]```. RGB triplets are useful for creating custom colors.

• Matrix of RGB triplets — A three-column matrix in which each row is an RGB triplet.

• Vector of colormap indices — A vector of numeric values that is the same length as the `x` and `y` vectors.

The way you specify the color depends on the desired color scheme and whether you are plotting one set of coordinates or multiple sets of coordinates. This table describes the most common situations.

Color SchemeHow to Specify the ColorExample

Use one color for all the points.

Specify a color name or a short name from the table below, or specify one RGB triplet.

Plot one set of points, and specify the color as `'red'`.

```x = randi(2,1,100); y = randn(100,1); c = 'red'; swarmchart(x,y,[],c)```

Plot two sets of points, and specify the color as red using an RGB triplet.

```x = randi(2,1,100); y = randn(100,1); c = [0.6 0 0.9]; swarmchart(x,y,[],c)```

Assign different colors to each point using a colormap.

Specify a row or column vector of numbers. The numbers index into the current colormap array. The smallest value maps to the first row in the colormap, and the largest value maps to the last row. The intermediate values map linearly to the intermediate rows.

If your plot has three points, specify a column vector to ensure the values are interpreted as colormap indices.

You can use this method only when `x`, `y`, and `sz` are all vectors.

Create a vector `c` that specifies 100 colormap indices. Plot 100 points using the colors from the current colormap. Then, change the colormap to `winter`.

```x = randi(2,1,100); y = randn(100,1); c = 1:100; swarmchart(x,y,[],c) colormap(gca,'winter')```

Create a custom color for each point.

Specify an m-by-3 matrix of RGB triplets, where m is the number of points in the plot.

You can use this method only when `x`, `y`, and `sz` are all vectors.

Create a matrix `c` that specifies 100 random RGB triplets. Then create a swarm chart of 100 points using those colors.

```x = randi(2,1,100); y = randn(100,1); c = rand(100,3); swarmchart(x,y,[],c)```

Create a different color for each data set.

Specify an n-by-3 matrix of RGB triplets, where n is the number of data sets.

You can use this method only when at least one of `x`, `y`, or `sz` is a matrix.

Create a matrix `c` that contains two RGB triplets. Then plot two data sets using those colors.

```x = randi(2,100,2); y = [randn(100,1) randn(100,1)+5]; c = [1 0 0; 0 0 1]; swarmchart(x,y,[],c)```

#### Color Names and RGB Triplets for Common Colors

Color NameShort NameRGB TripletHexadecimal Color CodeAppearance
`'red'``'r'``[1 0 0]``'#FF0000'` `'green'``'g'``[0 1 0]``'#00FF00'` `'blue'``'b'``[0 0 1]``'#0000FF'` `'cyan'` `'c'``[0 1 1]``'#00FFFF'` `'magenta'``'m'``[1 0 1]``'#FF00FF'` `'yellow'``'y'``[1 1 0]``'#FFFF00'` `'black'``'k'``[0 0 0]``'#000000'` `'white'``'w'``[1 1 1]``'#FFFFFF'` Here are the RGB triplets and hexadecimal color codes for the default colors MATLAB® uses in many types of plots.

RGB TripletHexadecimal Color CodeAppearance
`[0 0.4470 0.7410]``'#0072BD'` `[0.8500 0.3250 0.0980]``'#D95319'` `[0.9290 0.6940 0.1250]``'#EDB120'` `[0.4940 0.1840 0.5560]``'#7E2F8E'` `[0.4660 0.6740 0.1880]``'#77AC30'` `[0.3010 0.7450 0.9330]``'#4DBEEE'` `[0.6350 0.0780 0.1840]``'#A2142F'` Marker type, specified as one of the values listed in this table.

MarkerDescription
`'o'`Circle
`'+'`Plus sign
`'*'`Asterisk
`'.'`Point
`'x'`Cross
`'_'`Horizontal line
`'|'`Vertical line
`'s'`Square
`'d'`Diamond
`'^'`Upward-pointing triangle
`'v'`Downward-pointing triangle
`'>'`Right-pointing triangle
`'<'`Left-pointing triangle
`'p'`Pentagram
`'h'`Hexagram

Option to fill the interior of the markers, specified as `'filled'`. Use this option with markers that have a face, for example, `'o'` or `'square'`. Markers that do not have a face and contain only edges do not render at all (`'+'`, `'*'`, `'.'`, and `'x'`).

The `'filled'` option sets the `MarkerFaceColor` property of the `Scatter` object to `'flat'` and the `MarkerEdgeColor` property to `'none'`. In this case, MATLAB draws the marker faces, but not the edges.

Target axes, specified as an `Axes` object, a `PolarAxes` object, or a `GeographicAxes` object. If you do not specify the axes, MATLAB plots into the current axes, or it creates an `Axes` object if one does not exist.

### Name-Value Pair Arguments

Specify optional comma-separated pairs of `Name,Value` arguments. `Name` is the argument name and `Value` is the corresponding value. `Name` must appear inside quotes. You can specify several name and value pair arguments in any order as `Name1,Value1,...,NameN,ValueN`.

Example: `swarmchart(randi(4,500,1),randn(500,1),'MarkerFaceColor','red')` specifies red filled markers.

Note

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

Type of jitter (spacing of points) along the x-dimension, specified as one of the following values:

• `'none'` — Do not jitter the points.

• `'density'` — Jitter the points using the kernel density estimate of y for 2-D charts. If you specify this option in two dimensions for a 3-D chart, the points are jittered based on the kernel density estimate in the third dimension. For example, setting `XJitter` and `YJitter` to `'density'` uses the kernel density estimate of z.

• `'rand'` — Jitter the points randomly with a uniform distribution.

• `'randn'` — Jitter points randomly with a normal distribution.

Maximum amount of jitter (offset between points) along the x-dimension, specified as a nonnegative scalar value in data units.

For example, to set the jitter width to 90% of the shortest distance between adjacent points, take the minimum distance between unique values of `x` and scale by `0.9`.

`XJitterWidth = 0.9 * min(diff(unique(x)));`

## Algorithms

The points in a swarm chart are jittered using uniform random values that are weighted by the Gaussian kernel density estimate of `y` and the relative number of points at each `x` location. This behavior corresponds to the default `'density'` setting of the `XJitter` property on the `Scatter` object when you call the `swarmchart` function.

The maximum spread of points at each `x` location is 90% of the smallest distance between adjacent `x` values by default:

`spread = 0.9 * min(diff(unique(x)));`

You can control the spread by setting the `XJitterWidth` property on the `Scatter` object.

## See Also

### Properties

Introduced in R2020b

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