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MissingValuePattern

is an option for SynthesizeMissingValues and ToTabular to specify which data elements are considered missing.

Details
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Examples  
Basic Examples  
Scope  
Applications  
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MissingValuePattern

MissingValuePattern

is an option for SynthesizeMissingValues and ToTabular to specify which data elements are considered missing.

Details

  • MissingValuePattern is typically used to identify missing values. For instance, it is common to have some proxy value be interpreted as missing.
  • Possible settings include:
  • Automaticautomatically determine missing values
    pattuse patt for each element to determine missing values
  • The patti can also be Automatic, in which case, missing for that column is automatically recognized.
  • By default, Missing[…] and Indeterminate values are considered missing.

Examples

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Basic Examples  (2)

Specify that missing values are indicated by the value "99":

Wolfram Language code: data = {{1, 1.2}, {2, 2}, {3, 99}, {99, 1}, {2, 6}};
Wolfram Language code: SynthesizeMissingValues[data, MissingValuePattern -> 99]

Specify that the missing values are integers:

Wolfram Language code: data = {{1.1, 3, "A"}, {2, 4.2, "A"}, {3.2, 3, "B"}, {4.4, 5, "B"}, {5.2, 6.0, "A"}, {7, 7.3, "B"}, {9.1, 10.2, "B"}};
Wolfram Language code: SynthesizeMissingValues[data, MissingValuePattern -> _Integer]
Wolfram Language code: ToTabular[data, MissingValuePattern -> _Integer]

Scope  (3)

Specify missing values with Condition:

Wolfram Language code: data = {{1.1, 3}, {2, 4.2}, {3, 4}, {4.4, 5}, {5, 6}, {7, 8.3}, {9, 10}};
Wolfram Language code: SynthesizeMissingValues[data, MissingValuePattern -> x_ /; x < 3]
Wolfram Language code: ToTabular[data, MissingValuePattern -> x_ /; x < 3]

Train a distribution on a two-dimensional dataset:

Wolfram Language code: ld = LearnDistribution[{{1.1, 1.4}, {2.3, 3.1}, {4.4, 5.4}, {8.7, 7.5}}]

Specify that missing values are indicated by the value "7":

Wolfram Language code: SynthesizeMissingValues[ld, {{4.2, 5.2}, {5.8, 7}}, MissingValuePattern -> 7]

By default, Tabular only interprets explicit Missing[…] expressions as missing values:

Wolfram Language code: Tabular[{{1, Yesterday}, {3, today}, {Missing[], Tomorrow}}]

Use ToTabular to specify a pattern for the entries that should be additionally interpreted as missing values:

Wolfram Language code: ToTabular[{{1, Yesterday}, {3, today}, {Missing[], Tomorrow}}, MissingValuePattern -> _Symbol]

Specify multiple MissingValuePattern values:

Wolfram Language code: Tabular[{{1, Yesterday}, {3, today}, {Infinity, Tomorrow}}]
Wolfram Language code: ToTabular[{{1, Yesterday}, {3, today}, {Infinity, Tomorrow}}, MissingValuePattern -> (Infinity | _Symbol)]

Applications  (1)

Obtain a dataset of images:

Wolfram Language code: data = RandomSample[ResourceData["MNIST", "TrainingData"][[All, 1]], 10000];
Wolfram Language code: RandomSample[data, 10]

Train a distribution on the images:

Wolfram Language code: ld = LearnDistribution[ImageData /@ data]

Use MissingValuePattern to replace the pixel values that should be considered missing with the samples generated from the learned distribution:

Wolfram Language code: synthdata = SynthesizeMissingValues[ld, ImageData /@ {[image], [image]}, MissingValuePattern -> 0.5, Method -> "ModeFinding"];
Wolfram Language code: Image /@ synthdata
Wolfram Research (2019), MissingValuePattern, Wolfram Language function, https://reference.wolfram.com/language/ref/MissingValuePattern.html (updated 2025).

Text

Wolfram Research (2019), MissingValuePattern, Wolfram Language function, https://reference.wolfram.com/language/ref/MissingValuePattern.html (updated 2025).

CMS

Wolfram Language. 2019. "MissingValuePattern." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2025. https://reference.wolfram.com/language/ref/MissingValuePattern.html.

APA

Wolfram Language. (2019). MissingValuePattern. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/MissingValuePattern.html

BibTeX

@misc{reference.wolfram_2026_missingvaluepattern, author="Wolfram Research", title="{MissingValuePattern}", year="2025", howpublished="\url{https://reference.wolfram.com/language/ref/MissingValuePattern.html}", note=[Accessed: 12-June-2026]}

BibLaTeX

@online{reference.wolfram_2026_missingvaluepattern, organization={Wolfram Research}, title={MissingValuePattern}, year={2025}, url={https://reference.wolfram.com/language/ref/MissingValuePattern.html}, note=[Accessed: 12-June-2026]}