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ismissing

Find missing values

Description

example

TF = ismissing(A) returns a logical array that indicates which elements of the input data contain missing values. The size of TF is the same as the size of A.

Missing values are defined according to the data type of A:

  • NaNdouble, single, duration, and calendarDuration

  • NaTdatetime

  • <missing>string

  • <undefined>categorical

  • ' 'char

  • {''}cell of character vectors

If A is a table, then the data type of each column defines the missing value for that column.

For data types with no default definition of a standard missing value, ismissing(A) returns an array or table of logical 0 (false) values the same size as A.

example

TF = ismissing(A,indicator) treats the values in indicator as missing value indicators, ignoring all default indicators listed in the previous syntax. indicator can be a single indicator or multiple indicators. For example, if A is an array of type double, then ismissing(A,[0,-99]) treats 0 and –99 as missing double values instead of NaN.

TF = ismissing(___'OutputFormat',format) specifies for table or timetable input data the output data type for any of the previous syntaxes.

Examples

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Create a row vector A that contains NaN values, and identify their locations in A.

A = [3 NaN 5 6 7 NaN NaN 9];
TF = ismissing(A)
TF = 1x8 logical array

   0   1   0   0   0   1   1   0

Create a table with variables of different data types.

dblVar = [NaN;3;5;7;9;11;13];
singleVar = single([1;NaN;5;7;9;11;13]);
cellstrVar = {'one';'three';'';'seven';'nine';'eleven';'thirteen'};
charVar = ['A';'C';'E';' ';'I';'J';'L'];
categoryVar = categorical({'red';'yellow';'blue';'violet';'';'ultraviolet';'orange'});
dateVar = [datetime(2015,1:2:10,15) NaT datetime(2015,11,15)]';
stringVar = ["a";"b";"c";"d";"e";"f";missing];

A = table(dblVar,singleVar,cellstrVar,charVar,categoryVar,dateVar,stringVar)
A=7×7 table
    dblVar    singleVar     cellstrVar     charVar    categoryVar      dateVar      stringVar
    ______    _________    ____________    _______    ___________    ___________    _________

     NaN           1       {'one'     }       A       red            15-Jan-2015    "a"      
       3         NaN       {'three'   }       C       yellow         15-Mar-2015    "b"      
       5           5       {0x0 char  }       E       blue           15-May-2015    "c"      
       7           7       {'seven'   }               violet         15-Jul-2015    "d"      
       9           9       {'nine'    }       I       <undefined>    15-Sep-2015    "e"      
      11          11       {'eleven'  }       J       ultraviolet            NaT    "f"      
      13          13       {'thirteen'}       L       orange         15-Nov-2015    <missing>

Find the elements with missing values.

ismissing returns an array that has a logical 1 for every corresponding element in A with a missing value. The size of TF is the same as the size of A.

TF = ismissing(A)
TF = 7x7 logical array

   1   0   0   0   0   0   0
   0   1   0   0   0   0   0
   0   0   1   0   0   0   0
   0   0   0   1   0   0   0
   0   0   0   0   1   0   0
   0   0   0   0   0   1   0
   0   0   0   0   0   0   1

Create a table where 'NA', '', -99, NaN, and Inf represent missing values. Then, find the elements with missing values.

dblVar = [NaN;3;Inf;7;9];
int8Var = int8([1;3;5;7;-99]);
cellstrVar = {'one';'three';'';'NA';'nine'};
charVar = ['A';'C';'E';' ';'I'];

A = table(dblVar,int8Var,cellstrVar,charVar)
A=5×4 table
    dblVar    int8Var    cellstrVar    charVar
    ______    _______    __________    _______

     NaN          1      {'one'   }       A   
       3          3      {'three' }       C   
     Inf          5      {0x0 char}       E   
       7          7      {'NA'    }           
       9        -99      {'nine'  }       I   

Specify the missing value indicators. ismissing returns an array that has a logical 1 for every corresponding element in A with a missing value.

id = {'NA' '' -99 NaN Inf};
TF = ismissing(A,id)
TF = 5x4 logical array

   1   0   0   0
   0   0   0   0
   1   0   1   0
   0   0   1   1
   0   1   0   0

ismissing ignores trailing white space in character arrays. Therefore, because the empty character vector, '', is specified as a missing value indicator, ismissing identifies the empty character vector in A.cellstrVar and also the blank space in A.charVar as missing values.

Input Arguments

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Input data, specified as a vector, matrix, multidimensional array, table, or timetable.

  • If A is a timetable, then ismissing operates on the table data only and ignores NaT and NaN values in the vector of row times.

  • If A is a cell array or a table with cell array variables, then ismissing only detects missing elements when the cell array contains character vectors.

Missing value indicator, specified as a scalar, vector, or cell array.

  • If A is an array, then indicator must be a vector.

  • If A is a table or timetable, then indicator can also be a cell array with entries of multiple data types.

The entries of indicator indicate the values that ismissing treats as missing and overrides all default standard missing indicators. If you want to add indicators while maintaining the list of standard indicators, then you must include all default indicators as elements of indicator. For example, if A is a table with categorical and numeric values, use ismissing(A,{-99,'<undefined>'}) to indicate -99 as a missing numeric value, but preserve <undefined> as a missing categorical value.

You can also use the missing value as an indicator for any missing data represented as NaN, NaT, missing, or <undefined>. If A is a table, then missing is also an indicator for missing character vectors (' ') and missing cell arrays of character vectors ({''}).

Indicator data types match data types in the entries of A. These are additional data type matches between the indicator and elements of A:

  • double indicators match double, single, integer, and logical entries of A.

  • string and char indicators, and indicators that are cell arrays of character vectors, match string entries of A.

  • string and char indicators match categorical entries of A.

Example: TF = ismissing(A,0) recognizes only 0 as a missing value.

Output data type, specified as one of these values:

  • 'logical' — For table or timetable input data, return the output TF as a logical array.

  • 'tabular' — For table input data, return the output TF as a table. For timetable input data, return the output TF as a timetable.

For vector, matrix, or multidimensional array input data, OutputFormat is not supported.

Example: ismissing(T,'OutputFormat','tabular')

Tips

  • Because integer variables cannot store NaN, use a special integer value (otherwise unused) to indicate missing integer data, such as -99.

  • For more information on finding missing strings, see Test for Empty Strings and Missing Values.

Algorithms

ismissing handles leading and trailing white space differently for indicators that are cell arrays of character vectors, character arrays, or categorical arrays.

  • For cell arrays of character vectors, ismissing does not ignore indicator white space. All character vectors must match exactly.

  • For character arrays in table variables, ismissing ignores trailing white space in the indicator.

  • For categorical arrays, ismissing ignores leading and trailing white space in the indicator.

Extended Capabilities

Version History

Introduced in R2013b

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Behavior changed in R2022a