anymissing

Determine if any array element is missing

Since R2022a

Syntax

``TF = anymissing(A)``

Description

example

````TF = anymissing(A)` returns logical `1` (`true`) if at least one element of `A` is missing. It returns `0` (`false`) if no element is missing.Missing values are defined according to the data type of `A`: `NaN` — `double`, `single`, `duration`, and `calendarDuration``NaT` — `datetime``<missing>` — `string``<undefined>` — `categorical``{''}` — `cell` of character vectors If `A` is a table, then the data type of each variable defines the missing value for that variable.For data types with no default definition of a standard missing value, `anymissing` returns logical `0` (`false`).```

Examples

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Create a row vector `A` of type `double`. Determine if at least one element of `A` is missing, that is, if `A` contains at least one `NaN` value.

```A = [3.14 NaN -2.718 1.414 0.5]; TF = anymissing(A)```
```TF = logical 1 ```

Create a table with variables of different data types.

```dblVar = [1; 2; 3; 4; 5; 6]; singleVar = single([1; 2; 3; 4; 5; 6]); cellstrVar = {'one'; 'two'; ''; 'four'; 'five'; 'six'}; categoryVar = categorical({'red'; 'orange'; 'yellow'; ''; 'blue'; 'indigo'}); dateVar = [datetime(2015,1:6,15)]'; stringVar = ["a"; "b"; "c"; "d"; "e"; "f"]; A = table(dblVar,singleVar,cellstrVar,categoryVar,dateVar,stringVar)```
```A=6×6 table dblVar singleVar cellstrVar categoryVar dateVar stringVar ______ _________ __________ ___________ ___________ _________ 1 1 {'one' } red 15-Jan-2015 "a" 2 2 {'two' } orange 15-Feb-2015 "b" 3 3 {0x0 char} yellow 15-Mar-2015 "c" 4 4 {'four' } <undefined> 15-Apr-2015 "d" 5 5 {'five' } blue 15-May-2015 "e" 6 6 {'six' } indigo 15-Jun-2015 "f" ```

Determine if any element of the table has a missing value.

`anymissing` returns logical `1` because at least one element of `A` is missing. Here, the third element of `cellstrVar` is `''` and the fourth element of `categoryVar` is `<undefined>`, which are missing values.

`TF = anymissing(A)`
```TF = logical 1 ```

Create a 3-D array and determine if at least one of its elements is missing.

```A(:,:,1) = [2 1; 3 5]; A(:,:,2) = [NaN 0; 0 NaN]; A(:,:,3) = [-2 9; 4 1]```
```A = A(:,:,1) = 2 1 3 5 A(:,:,2) = NaN 0 0 NaN A(:,:,3) = -2 9 4 1 ```
`TF = anymissing(A)`
```TF = logical 1 ```

Input Arguments

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Input data, specified as a scalar, vector, matrix, multidimensional array, cell array of character vectors, table, or timetable.

• If `A` is a timetable, then `anymissing` operates on the table data only and ignores `NaT` or `NaN` values in the row times.

• If `A` is a cell array, then `anymissing` only detects missing elements when `A` is a cell array of character vectors.

Example: `["a" "b" missing "d"]`

Data Types: `double` | `single` | `int8` | `int16` | `int32` | `int64` | `uint8` | `uint16` | `uint32` | `uint64` | `logical` | `char` | `string` | `cell` | `table` | `timetable` | `categorical` | `datetime` | `duration` | `calendarDuration`
Complex Number Support: Yes

Tips

• For input data that is a structure array or a cell array of non-character vectors, `anymissing` returns `false`. To determine if any element of a structure array is missing, apply `anymissing` to each field in the structure by using the `structfun` function. To determine if any element of a cell array of non-character vectors is missing, apply `anymissing` to each cell in the cell array by using the `cellfun` function.

Version History

Introduced in R2022a

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