unique

Unique values in array

Syntax

C = unique(A)

C = unique(A,setOrder)

C = unique(A,occurrence)

C = unique(A,___,'rows')

C = unique(A,'rows',___)

[C,ia,ic] = unique(___)

[C,ia,ic] = unique(A,'legacy')

[C,ia,ic] = unique(A,'rows','legacy')

[C,ia,ic] = unique(A,occurrence,'legacy')

[C,ia,ic] = unique(A,'rows',occurrence,'legacy')

Description

C = unique(A) returns the same data as in A, but with no repetitions. C is in sorted order.

• If A is a table or timetable, then unique returns the unique rows in A in sorted order. For timetables, unique takes row times and row values into account when determining whether rows are unique, and sorts the output timetable C by row times.

• If A is a categorical array, then the sort order is determined by the order of the categories.

C = unique(A,setOrder) returns the unique values of A in a specific order. setOrder can be 'sorted' (default) or 'stable'.

C = unique(A,occurrence) specifies which indices to return in case of repeated values. occurrence can be 'first' (default) or 'last'.

C = unique(A,___,'rows') and C = unique(A,'rows',___) treat each row of A as a single entity and return the unique rows of A in sorted order. You must specify A and optionally can specify setOrder or occurrence.

The 'rows' option does not support cell arrays.

[C,ia,ic] = unique(___) also returns index vectors ia and ic using any of the previous syntaxes.

• If A is a vector, then C = A(ia) and A = C(ic).

• If A is a matrix or array, then C = A(ia) and A(:) = C(ic).

• If the 'rows' option is specified, then C = A(ia,:) and A = C(ic,:).

• If A is a table or a timetable, then C = A(ia,:) and A = C(ic,:).

[C,ia,ic] = unique(A,'legacy'), [C,ia,ic] = unique(A,'rows','legacy'), [C,ia,ic] = unique(A,occurrence,'legacy'),and [C,ia,ic] = unique(A,'rows',occurrence,'legacy') preserve the behavior of the unique function from R2012b and prior releases.

The 'legacy' option does not support categorical arrays, datetime arrays, duration arrays, calendarDuration arrays, tables, or timetables.

Examples

Unique Values in Vector

Define a vector with a repeated value.

A = [9 2 9 5];

Find the unique values of A.

C = unique(A)

C = 1×3

     2     5     9

Unique Rows in Table

Create a table with some repeated data.

Name = {'Fred';'Betty';'Bob';'George';'Jane'};
Age = [38;43;38;40;38];
Height = [71;69;64;67;64];
Weight = [176;163;131;185;131];
A = table(Age,Height,Weight,'RowNames',Name)

A=5×3 table
              Age    Height    Weight
              ___    ______    ______

    Fred      38       71       176  
    Betty     43       69       163  
    Bob       38       64       131  
    George    40       67       185  
    Jane      38       64       131  

Find the unique rows of A. unique returns the rows of A in sorted order by the first variable Age and then by the second variable Height.

C = unique(A)

C=4×3 table
              Age    Height    Weight
              ___    ______    ______

    Bob       38       64       131  
    Fred      38       71       176  
    George    40       67       185  
    Betty     43       69       163  

Find the table rows with unique values in the first variable Age. If you only want one table variable to contain unique values, you can use the indices returned by unique to extract those rows from the table.

[C,ia] = unique(A.Age);
B = A(ia,:)

B=3×3 table
              Age    Height    Weight
              ___    ______    ______

    Fred      38       71       176  
    George    40       67       185  
    Betty     43       69       163  

Unique Values and Their Indices

Define a vector with a repeated value.

A = [9 2 9 5];

Find the unique values of A and the index vectors ia and ic, such that C = A(ia) and A = C(ic).

[C, ia, ic] = unique(A)

C = 1×3

     2     5     9

ia = 3×1

     2
     4
     1

ic = 4×1

     3
     1
     3
     2

Unique Rows in Matrix

Create a 10-by-3 matrix with some repeated rows.

A = randi(3,10,3)

A = 10×3

     3     1     2
     3     3     1
     1     3     3
     3     2     3
     2     3     3
     1     1     3
     1     2     3
     2     3     2
     3     3     2
     3     3     1

Find the unique rows of A based on the data in the first two columns. Specify three outputs to return the index vectors ia and ic.

[C,ia,ic] = unique(A(:,1:2),'rows')

C = 7×2

     1     1
     1     2
     1     3
     2     3
     3     1
     3     2
     3     3

ia = 7×1

     6
     7
     3
     5
     1
     4
     2

ic = 10×1

     5
     7
     3
     6
     4
     1
     2
     4
     7
     7

Use ia to index into A and retrieve the rows that have unique combinations of elements in the first two columns.

uA = A(ia,:)

uA = 7×3

     1     1     3
     1     2     3
     1     3     3
     2     3     3
     3     1     2
     3     2     3
     3     3     1

Count of Unique Elements

Find the unique elements in a vector and then use accumarray to count the number of times each unique element appears.

Create a vector of random integers from 1 through 5.

a = randi([1 5],200,1);

Find the unique elements in the vector. Return the index vectors ia and ic.

[C,ia,ic] = unique(a);

Count the number of times each element in C appears in a. Specify ic as the first input to accumarray and 1 as the second input so that the function counts repeated subscripts in ic. Summarize the results.

a_counts = accumarray(ic,1);
value_counts = [C, a_counts]

value_counts = 5×2

     1    46
     2    36
     3    38
     4    39
     5    41

Unique Values in Vector with Specified Order

Use the setOrder argument to specify the ordering of the values in C.

Specify 'stable' if you want the values in C to have the same order as in A.

A = [9 2 9 5];
[C, ia, ic] = unique(A,'stable')

C = 1×3

     9     2     5

ia = 3×1

     1
     2
     4

ic = 4×1

     1
     2
     1
     3

Alternatively, you can specify 'sorted' order.

[C, ia, ic] = unique(A,'sorted')

C = 1×3

     2     5     9

ia = 3×1

     2
     4
     1

ic = 4×1

     3
     1
     3
     2

Unique Values in Array Containing NaNs

Define a vector containing NaN.

A = [5 5 NaN NaN];

Find the unique values of A.

C = unique(A)

C = 1×3

     5   NaN   NaN

unique treats NaN values as distinct.

Unique Elements in Presence of Numerical Error

Create a vector x. Obtain a second vector y by transforming and untransforming x. This transformation introduces round-off differences in y.

x = (1:6)'*pi;
y = 10.^log10(x);

Verify that x and y are not identical by taking the difference.

x-y

ans = 6×1
10-14 ×

    0.0444
         0
         0
         0
         0
   -0.3553

Use unique to find the unique elements in the concatenated vector [x;y]. The unique function performs exact comparisons and determines that some values in x are not exactly equal to values in y. These are the same elements that have a nonzero difference in x-y. Thus, c contains values that appear to be duplicates.

c = unique([x;y])

c = 8×1

    3.1416
    3.1416
    6.2832
    9.4248
   12.5664
   15.7080
   18.8496
   18.8496

Use uniquetol to perform the comparison using a small tolerance. uniquetol treats elements that are within tolerance as equal.

C = uniquetol([x;y])

C = 6×1

    3.1416
    6.2832
    9.4248
   12.5664
   15.7080
   18.8496

Unique Entries in Cell Array of Character Vectors

Create a cell array of character vectors.

A = {'one','two','twenty-two','One','two'};

Find the unique character vectors contained in A.

C = unique(A)

C = 1x4 cell
    {'One'}    {'one'}    {'twenty-two'}    {'two'}

Cell Array of Character Vectors with Trailing White Space

Create a cell array of character vectors, A, where some of the vectors have trailing white space.

A = {'dog','cat','fish','horse','dog ','fish '};

Find the unique character vectors contained in A.

C = unique(A)

C = 1x6 cell
    {'cat'}    {'dog'}    {'dog '}    {'fish'}    {'fish '}    {'horse'}

unique treats trailing white space in cell arrays of character vectors as distinct characters.

Preserve Legacy Behavior of unique

Use the 'legacy' flag to preserve the behavior of unique from R2012b and prior releases in your code.

Find the unique elements of A with the current behavior.

A = [9 2 9 5];
[C1, ia1, ic1] = unique(A)

C1 = 1×3

     2     5     9

ia1 = 3×1

     2
     4
     1

ic1 = 4×1

     3
     1
     3
     2

Find the unique elements of A, and preserve the legacy behavior.

[C2, ia2, ic2] = unique(A, 'legacy')

C2 = 1×3

     2     5     9

ia2 = 1×3

     2     4     3

ic2 = 1×4

     3     1     3     2

Input Arguments

A — Input array

array

Input array.

• If A is a table, then unique does not take row names into account. Two rows that have the same values, but different names, are considered equal.

• If A is a timetable, then unique takes row times into account. Two rows that have the same values, but different times, are not considered equal.

• If A is a categorical array, then the sort order is determined by the order of the categories. To see the sort order of a categorical array, use the categories function.

A can also be an object with the following class methods:

• sort (or sortrows for the 'rows' option)

• ne

The object class methods must be consistent with each other. These objects include heterogeneous arrays derived from the same root class. For example, A can be an array of handles to graphics objects.

setOrder — Order flag

'sorted' (default) | 'stable'

Order flag, specified as 'sorted' or 'stable', indicates the order of the values (or rows) in C.

Flag	Description
'sorted'	The values (or rows) in C return in sorted order as returned by sort. Example C = unique([5 5 3 4],'sorted') C = 3 4 5
'stable'	The values (or rows) in C return in the same order as in A. Example C = unique([5 5 3 4],'stable') C = 5 3 4

Data Types: char | string

occurrence — Occurrence flag

'first' (default) | 'last'

Occurrence flag, specified as 'first' or 'last', indicates whether ia should contain the first or last indices to repeated values found in A.

Occurrence Flag	Meaning
'last'	If there are repeated values (or rows) in A, then ia contains the index to the last occurrence of the repeated value. For example: [C,ia,ic] = unique([9 9 9],'last','legacy') returns ia = 3. This is the default behavior when the 'legacy' flag is specified.
'first'	If there are repeated values (or rows) in A, then ia contains the index to the first occurrence of the repeated value. For example: [C,ia,ic] = unique([9 9 9],'first') returns ia = 1. This is the default behavior.

Data Types: char | string

Output Arguments

C — Unique data of A

array

Unique data of A, returned as an array. The class of C is the same as the class of the input A. The shape of C depends on whether the input is a vector or a matrix:

• If the 'rows' flag is not specified and A is a row vector, then C is a row vector.

• If the 'rows' flag is not specified and A is not a row vector, then C is a column vector.

• If the 'rows' flag is specified, then C is a matrix containing the unique rows of A.

ia — Index to A

column vector

Index to A, returned as a column vector of indices to the first occurrence of repeated elements. When the 'legacy' flag is specified, ia is a row vector that contains indices to the last occurrence of repeated elements.

The indices generally satisfy C = A(ia). If A is a table, or if the 'rows' option is specified, then C = A(ia,:).

ic — Index to C

column vector

Index to C, returned as a column vector when the 'legacy' flag is not specified. ic contains indices that satisfy the following properties.

• If A is a vector, then A = C(ic).

• If A is a matrix or array, then A(:) = C(ic).

• If A is a table, or if the 'rows' option is specified, then A = C(ic,:).

Tips

• Use uniquetol to find unique floating-point numbers using a tolerance.

• To find unique rows in tables or timetables with respect to a subset of variables, you can use column subscripting. For example, you can use unique(A(:,vars)), where vars is a positive integer, a vector of positive integers, a variable name, a cell array of variable names, or a logical vector. Alternatively, you can use vartype to create a subscript that selects variables of a specified type.

Extended Capabilities

Tall Arrays

Calculate with arrays that have more rows than fit in memory.

This function supports tall arrays with the limitations:

• For tall vectors and tall tables, use the syntaxes:

  • C = unique(A)

  • [C,ia,ic] = unique(A)

• For tall matrices, use the syntaxes:

  • C = unique(A,'rows')

  • [C,ia,ic] = unique(A,'rows')

For more information, see Tall Arrays for Out-of-Memory Data.

C/C++ Code Generation

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

• Code generation does not support cell arrays for the first argument.

• When you do not specify the'rows' option:

  • The input A must be a vector. If you specify the 'legacy' option, the input A must be a row vector.

  • The first dimension of a variable-size row vector must have fixed length 1. The second dimension of a variable-size column vector must have fixed length 1.

  • The input [] is not supported. Use a 1-by-0 or 0-by-1 input, for example, zeros(1,0), to represent the empty set.

  • If you specify the 'legacy' option, then empty outputs are row vectors, 1-by-0. They are never 0-by-0.

• When you specify both the 'rows' option and the 'legacy'option, outputs ia and ic are column vectors. If these outputs are empty, then they are 0-by-1, even if the output C is 0-by-0.

• When the setOrder is not 'stable' or when you specify the 'legacy' option, the input A must already be sorted in ascending order. The first output, C, is sorted in ascending order.

• Complex inputs must be single or double.

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

Usage notes and limitations:

• The 'legacy' flag is not supported.

• 64-bit integers are not supported.

For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

Distributed Arrays

Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.

This function fully supports distributed arrays. For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).