grp2idx
Create index vector from grouping variable
Description
Examples
Create Index Vector from Categorical Vector
Create a categorical vector by using discretize
and convert it to an index vector by using grp2idx
.
Load the hospital
data set and convert the ages in hospital.Ages
to categorical values representing the ages by decade.
load hospital edges = 0:10:100; % Bin edges labels = strcat(num2str((0:10:90)','%d'),{'s'}); % Labels for the bins s = discretize(hospital.Age,edges,'Categorical',labels);
Display the ages and the groups of ages for the first five samples.
ages = hospital.Age(1:5)
ages = 5×1
38
43
38
40
49
groups = s(1:5)
groups = 5x1 categorical
30s
40s
30s
40s
40s
Create an index vector from the categorical vector s
.
[g,gN,gL] = grp2idx(s);
Display the index values corresponding to the first five samples.
g(1:5)
ans = 5×1
4
5
4
5
5
Reproduce the input argument s
using the output gL
.
gL(g(1:5))
ans = 5x1 categorical
30s
40s
30s
40s
40s
Use gN(g)
to reproduce the input argument s
as a cell array of character vectors.
gN(g(1:5))
ans = 5x1 cell
{'30s'}
{'40s'}
{'30s'}
{'40s'}
{'40s'}
Input Arguments
s
— Grouping variable
categorical vector | numeric vector | logical vector | datetime
vector | duration vector | string array | cell array of character vectors | character array
Grouping variable, specified as a categorical, numeric, logical,
datetime
, or duration vector, a string array, a cell
array of character vectors, or a character array with each row representing
a group label.
grp2idx
treats NaN
s (numeric,
duration, or logical), ''
(empty character arrays or cell
arrays of character vectors), ""
(empty strings),
<missing>
values (string),
<undefined>
values (categorical), and
NaT
s (datetime
) in
s
as missing values and returns
NaN
s in the corresponding rows of
g
. The outputs gN
and
gL
do not include entries for missing
values.
Data Types: single
| double
| int8
| int16
| int32
| int64
| uint8
| uint16
| uint32
| uint64
| logical
| char
| string
| cell
| categorical
| datetime
| duration
Output Arguments
g
— Group index
positive integer vector
Group index, returned as a positive integer vector with values from 1 up
to the number K of distinct groups in
s
.
gN
— List of group names
cell array of character vectors
List of group names, returned as a cell array of character vectors.
The order of gN
depends on the data type of the
grouping variable s
.
For numeric and logical vectors, the order is the sorted order of
s
.For categorical vectors, the order is the order of
categories(s)
.For other data types, the order is the order of first appearance in
s
.
gN(g)
reproduces the contents of s
in a cell array.
gL
— List of group levels
categorical vector | numeric vector | logical vector | datetime
vector | duration vector | cell array of character vectors | character array
List of group levels, returned as the same data type as
s
: a categorical, numeric, logical,
datetime
, or duration vector, a cell array of
character vectors, or a character array with each row representing a group
label. (The software treats string arrays as cell arrays of character
vectors.)
The set of groups and their order in gL
are the same
as those in gN
, but gL
has the
same data type as s
.
If s
is a character matrix, then
gL(g,:)
reproduces s
; otherwise,
gL(g)
reproduces s
.
Extended Capabilities
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
Usage notes and limitations:
The input argument
s
can be a numeric, logical, or character vector or a cell array of character vectors. Code generation does not support a categorical,datetime
, or duration vector or a string array for the input argument.In the generated code, the second and third outputs,
gN
andgL
, are identical.gN
andgL
have the same data type as the input arguments
.
For more information on code generation, see Introduction to Code Generation and General Code Generation Workflow.
GPU Arrays
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.
This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).
Version History
Introduced before R2006a
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