categorical
is a data type to store data
with values from a finite set of discrete categories, which can have
a natural order. You can specify and rearrange the order of categories
in all categorical arrays. However, you only can treat ordinal categorical
arrays as having a mathematical ordering to their categories. Use
an ordinal categorical array if you want to use the functions min
, max
,
or relational operations, such as greater than and less than.
The discrete set of pet categories {'dog' 'cat' 'bird'}
has
no meaningful mathematical ordering. You are free to use any category
order and the meaning of the associated data does not change. For
example, pets = categorical({'bird','cat','dog','dog','cat'})
creates
a categorical array and the categories are listed in alphabetical
order, {'bird' 'cat' 'dog'}
. You can choose to
specify or change the order of the categories to {'dog' 'cat'
'bird'}
and the meaning of the data does not change.
ordinal categorical arrays contain categories
that have a meaningful mathematical ordering. For example, the discrete
set of size categories {'small', 'medium', 'large'}
has
the mathematical ordering small < medium < large
.
The first category listed is the smallest and the last category is
the largest. The order of the categories in an ordinal categorical
array affects the result from relational comparisons of ordinal categorical
arrays.
This example shows how to create an ordinal categorical array using the categorical
function with the 'Ordinal',true
name-value pair argument.
Ordinal Categorical Array from a Cell Array of Character Vectors
Create an ordinal categorical array, sizes
, from a cell array of character vectors, A
. Use valueset
, specified as a vector of unique values, to define the categories for sizes
.
A = {'medium' 'large';'small' 'medium'; 'large' 'small'}; valueset = {'small', 'medium', 'large'}; sizes = categorical(A,valueset,'Ordinal',true)
sizes = 3x2 categorical
medium large
small medium
large small
sizes
is 3-by-2 ordinal categorical array with three categories such that small < medium < large
. The order of the values in valueset
becomes the order of the categories of sizes
.
Ordinal Categorical Array from Integers
Create an equivalent categorical array from an array of integers. Use the values 1
, 2
, and 3
to define the categories small
, medium
, and large
, respectively.
A2 = [2 3; 1 2; 3 1]; valueset = 1:3; catnames = {'small','medium','large'}; sizes2 = categorical(A2,valueset,catnames,'Ordinal',true)
sizes2 = 3x2 categorical
medium large
small medium
large small
Compare sizes
and sizes2
isequal(sizes,sizes2)
ans = logical
1
sizes
and sizes2
are equivalent categorical arrays with the same ordering of categories.
Convert a Categorical Array from Nonordinal to Ordinal
Create a nonordinal categorical array from the cell array of character vectors, A
.
sizes3 = categorical(A)
sizes3 = 3x2 categorical
medium large
small medium
large small
Determine if the categorical array is ordinal.
isordinal(sizes3)
ans = logical
0
sizes3
is a nonordinal categorical array with three categories, {'large','medium','small'}
. The categories of sizes3
are the sorted unique values from A
. You must use the input argument, valueset
, to specify a different category order.
Convert sizes3
to an ordinal categorical array, such that small < medium < large
.
sizes3 = categorical(sizes3,{'small','medium','large'},'Ordinal',true);
sizes3
is now a 3-by-2 ordinal categorical array equivalent to sizes
and sizes2
.
In order to combine or compare two categorical arrays, the sets of categories for both input arrays must be identical, including their order. Furthermore, ordinal categorical arrays are always protected. Therefore, when you assign values to an ordinal categorical array, the values must belong to one of the existing categories. For more information see Work with Protected Categorical Arrays.
categorical
| categories
| isequal
| isordinal