Parallel coordinates plot


h = parallelcoords(X,...)


parallelcoords(X) creates a parallel coordinates plot of the multivariate data in the n-by-p matrix X. Rows of X correspond to observations, columns to variables. A parallel coordinates plot is a tool for visualizing high dimensional data, where each observation is represented by the sequence of its coordinate values plotted against their coordinate indices. parallelcoords treats NaNs in X as missing values and does not plot those coordinate values.

parallelcoords(X,...,'Standardize','on') scales each column of X to have mean 0 and standard deviation 1 before making the plot.

parallelcoords(X,...,'Standardize','PCA') creates a parallel coordinates plot from the principal component scores of X, in order of decreasing eigenvalues. parallelcoords removes rows of X containing missing values (NaNs) for principal components analysis (PCA) standardization.

parallelcoords(X,...,'Standardize','PCAStd') creates a parallel coordinates plot using the standardized principal component scores.

parallelcoords(X,...,'Quantile',alpha) plots only the median and the alpha and 1-alpha quantiles of f (t) at each value of t. This is useful if X contains many observations.

parallelcoords(X,...,'Group',group) plots the data in different groups with different colors. Groups are defined by group, a numeric array containing a group index for each observation. group can also be a categorical variable, character matrix, or cell array of strings, containing a group name for each observation.

parallelcoords(X,...,'Labels',labels) labels the coordinate tick marks along the horizontal axis using labels, a character array or cell array of strings.

parallelcoords(X,...,PropertyName,PropertyValue,...) sets properties to the specified property values for all line graphics objects created by parallelcoords.

h = parallelcoords(X,...) returns a column vector of handles to the line objects created by parallelcoords, one handle per row of X. If you use the 'Quantile' input argument, h contains one handle for each of the three lines objects created. If you use both the 'Quantile' and the 'Group' input arguments, h contains three handles for each group.

parallelcoords(axes,...) plots into the axes with handle axes.


% Make a grouped plot of the raw data
load fisheriris
labels = {'Sepal Length','Sepal Width',...
          'Petal Length','Petal Width'};

% Plot only the median and quartiles of each group
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