Visualize the distribution of data using plots such as histograms, pie charts, or word clouds. For example, use a histogram to group data into bins and display the number of elements in each bin.
|Bivariate histogram plot|
|Increase number of histogram bins|
|Decrease number of histogram bins|
|Histogram bin counts|
|Bivariate histogram bin counts|
|3-D scatter plot|
|Binned scatter plot|
|Create scatter plot with histograms|
|Visualize sparsity pattern of matrix|
|Scatter plot matrix|
|Histogram Properties||Histogram appearance and behavior|
|Histogram2 Properties||Histogram2 appearance and behavior|
|Scatter Properties||Scatter chart appearance and behavior|
|ScatterHistogramChart Properties||Control scatter histogram chart appearance and behavior|
|Binscatter Properties||Binscatter appearance and behavior|
|HeatmapChart Properties||Heatmap chart appearance and behavior|
|WordCloudChart Properties||Control word cloud chart appearance and behavior|
|ParallelCoordinatesPlot Properties||Control parallel coordinates plot appearance and behavior|
This example shows how to add a legend to a pie chart that displays a description for each slice.
This example shows how to create a pie graph and automatically offset the pie slice with the greatest contribution.
When you create a pie chart, MATLAB labels each pie slice with the percentage of the whole that slice represents.
This example shows how to adjust the color scale of a bivariate histogram plot to reveal additional details about the bins.
This example shows how to use
histogram to effectively view categorical data.
This example shows how to create a heatmap from a table and how to modify the heatmap appearance.
This example shows how to create a word cloud from plain text by reading it into a string array, preprocessing it, and passing it to the
This example shows how to create a parallel coordinates plot from a table and how to modify the appearance of the plot.
discretize are the recommended histogram creation and
computation functions for new code.