Grouping Variables To Split Data
You can use grouping variables to split data variables into groups. Typically, selecting
grouping variables is the first step in the Split-Apply-Combine workflow. You can split data
into groups, apply a function to each group, and combine the results. You also can denote
missing values in grouping variables, so that corresponding values in data variables are
ignored.Grouping Variables
Grouping variables are variables used to group, or categorize, observations—that is, data
values in other variables. A grouping variable can be any of these data types:- Numeric, logical, categorical, datetime, or duration vector
- Cell array of character vectors
- Table, with table variables of any data type in this list
Data variables are the variables that contain observations. A grouping variable must have
a value corresponding to each value in the data variables. Data values belong to the same
group when the corresponding values in the grouping variable are the same.This table shows examples of data variables, grouping variables, and the groups that you
can create when you split the data variables using the grouping variables.Data Variable Grouping Variable Groups of Data
[5 10 15 20 25 30] [0 0 0 0 1 1] [5 10 15 20] [25 30]
[10 20 30 40 50 60] [1 3 3 1 2 1] [10 40 60] [50] [20 30]
[64 72 67 69 64 68] {'F','M','F','M','F','F
'}[64 67 64 68] [72 69]
You can give groups of data meaningful names when you use cell arrays of character
vectors or categorical arrays as grouping variables. A categorical array is an efficient and
flexible choice of grouping variable.Grouping Variables To Split Data