Several indexing and searching methods for categorical arrays.
Compute and compare measures of dispersion for sample data that contains one outlier.
Categorize numeric data into a categorical ordinal array using ordinal . This is useful for discretizing continuous data.
Select an observation or subset of observations from a dataset array.
Sort observations (rows) in a dataset array using the command line. You can also sort rows using the Variables editor.
Compute and compare measures of location for sample data that contains one outlier.
Compute summary statistics grouped by levels of a categorical variable. You can compute group summary statistics for a numeric array or a dataset array using grpstats .
Create a 3-by-3 matrix of sample data. Remove two data values by replacing them with NaN .
Create a dataset array from a numeric array existing in the MATLAB® workspace.
Change the labels for category levels in categorical arrays using setlabels . You also have the option to specify labels when creating a categorical array.
Reorder the category levels in nominal arrays using reorderlevels . By definition, nominal array categories have no natural ordering. However, you might want to change the order of levels
Merge categories in a nominal or ordinal array using mergelevels . This is useful for collapsing categories with few observations.
Create a dataset array from heterogeneous variables existing in the MATLAB® workspace.
Reorder the category levels in an ordinal array using reorderlevels .
Visualize multivariate data using various statistical plots. Many statistical analyses involve only two variables: a predictor variable and a response variable. Such data are easy to