Random Missing-Value Table Generator

Description

Generate typed primitive records, inject explicit independent null cells with a retained baseline and mask, then delegate canonical TableData and LF-terminated CSV serialization; not a model of real missingness or spreadsheet formula sanitization.

A parser corpus pairs literal input spellings or structured documents with observable parser results or explicitly constructed expectations. Successful parsing, semantic validity, and exact round-trip preservation are separate properties, so test records retain the relevant evidence.

When to use this tool

Use this generator to create reproducible missing value table cases from the supplied model or bank. Inspect the returned evidence before using cases in a test or exercise.

How to use the tool and how it works

Supply rowCount, columns, delimiter, missingProbability in the field shapes below. Set seed when you need an explicit replay.
Run the tool and correct any input error. For generated controls, distinguish a successful fixture containing an invalid case from failure to generate the fixture.
Read completeRecords, missingMask, records, table, csv. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Generate a complete primitive table, draw an independent missing-cell mask, and replace masked values with JSON null. Return original records, mask, incomplete records, and serialized table forms.^[1]

Input field	Meaning and units	Accepted input
rowCount	Row Count	Required. Safe integer; minimum 1; maximum 256.
columns	Columns	Required. Array of Object; no unknown keys. or Object; no unknown keys. or Object; no unknown keys. or Object; no unknown keys.; minimum items 1; maximum items 16.
delimiter	Delimiter	Required. Text; one of ",", ";", "\t", "\|".
missingProbability	Missing Probability	Required. Finite number; minimum 0; maximum 1.
seed	Optional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed.	Optional. Safe integer.

Output field	Interpretation	Returned shape
completeRecords	Complete Records	Required. Array of Object.; minimum items 1; maximum items 256.
missingMask	Missing Mask	Required. Array of Array of Boolean.; minimum items 1; maximum items 16.; minimum items 1; maximum items 256.
records	Records	Required. Array of Object.; minimum items 1; maximum items 256.
table	Table	Required. Object; no unknown keys.
table.kind	Kind	Required. Text; exactly "tool.io/table".
table.version	Version	Required. Safe integer; exactly 1.
table.rows	Rows	Required. Array of Array of Text; maximum UTF-16 length 128. or Finite number. or Boolean. or Null.; minimum items 1; maximum items 16.; minimum items 1; maximum items 256.
table.schema	Schema	Required. Object; no unknown keys.
table.schema.fields	Fields	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 16.
table.schema.fields[].dataType	Data Type	Required. Object; no unknown keys. or Object; no unknown keys. or Object; no unknown keys.
table.schema.fields[].id	Literal identifier used to match records, independently of their display labels.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
table.schema.fields[].label	Caller-facing text label; not a globally unique identifier.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 32.
table.schema.fields[].nullable	Nullable	Required. Boolean.
csv	Csv	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 1100000.
randomness	Replay metadata: source is seed or context; seed is the normalized 32-bit seed or null for a context source.	Required. Object; no unknown keys.
randomness.seed	Optional numeric replay seed; normalization and precedence are explained below.	Required. Safe integer. or Null.
randomness.source	Source	Required. Text; one of "context", "seed".

An explicit safe-integer seed takes precedence over injected context randomness and is normalized to an unsigned 32-bit integer. With no seed and no context source, replay uses the fixed tool.io default seed. A context source must return finite values from zero inclusive to one exclusive; its advancing state must be retained separately. randomness records the source and normalized seed, or null for context. These generators are not cryptographic random sources.

json

{
  "input": {
    "rowCount": 3,
    "columns": [
      {
        "key": "name",
        "kind": "text",
        "choices": [
          "Ada",
          "Grace",
          "Lin"
        ]
      },
      {
        "key": "age",
        "kind": "integer",
        "minimum": 20,
        "maximum": 60
      },
      {
        "key": "active",
        "kind": "boolean",
        "trueProbability": 0.7
      }
    ],
    "delimiter": ",",
    "missingProbability": 0.35,
    "seed": 42
  },
  "output": {
    "completeRecords": [
      {
        "name": "Grace",
        "age": 38,
        "active": false
      },
      {
        "name": "Lin",
        "age": 27,
        "active": true
      },
      {
        "name": "Ada",
        "age": 45,
        "active": false
      }
    ],
    "missingMask": [
      [
        false,
        true,
        false
      ],
      [
        false,
        true,
        true
      ],
      [
        false,
        false,
        false
      ]
    ],
    "records": [
      {
        "name": "Grace",
        "age": null,
        "active": false
      },
      {
        "name": "Lin",
        "age": null,
        "active": null
      },
      {
        "name": "Ada",
        "age": 45,
        "active": false
      }
    ],
    "table": {
      "kind": "tool.io/table",
      "rows": [
        [
          "Grace",
          null,
          false
        ],
        [
          "Lin",
          null,
          null
        ],
        [
          "Ada",
          45,
          false
        ]
      ],
      "schema": {
        "fields": [
          {
            "dataType": {
              "kind": "string"
            },
            "id": "name",
            "label": "name",
            "nullable": false
          },
          {
            "dataType": {
              "bits": 64,
              "kind": "integer",
              "signed": true
            },
            "id": "age",
            "label": "age",
            "nullable": true
          },
          {
            "dataType": {
              "kind": "boolean"
            },
            "id": "active",
            "label": "active",
            "nullable": true
          }
        ]
      },
      "version": 1
    },
    "csv": "name,age,active\nGrace,,false\nLin,,\nAda,45,false\n",
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

The mask distinguishes planted missingness from original values. This models independent random omission rather than informative missingness, and serialization does not impute or infer missing values.
A replay requires the same complete input and implementation. Randomized construction does not guarantee uniform coverage of every feasible output; finite samples can repeat unless a distinct-selection rule is explicitly stated.
The field tables state structural bounds; cross-field constraints and bounded search or output budgets also apply. Unknown keys are rejected where the object contract disallows them. Input errors are distinct from null fields and deliberate invalid controls in a successful output.

Alternative or Complementary methods

For a supplied example, inspect the returned construction or delegated check directly. To evaluate a consumer, also test cases chosen for its own boundaries; a generated finite corpus does not establish exhaustive coverage.

References

Tool behavior and example: Random Missing-Value Table Generator — tool.io

Similar or alternative tools

Random JSON Null and Missing Value Fixture Generator
Construct absent, null, empty-string and supplied-value fields with caller-selected interpretation labels and explicit own-property presence.
Random Identifier Transcription Error Corpus Generator
Generate synthetic checksum-valid EAN-13 and 978-prefixed ISBN-13 originals, apply a selected decimal substitution, deletion, or adjacent transposition, and record actual GTIN/ISBN validator outcomes; swaps may be unchanged or remain valid, and checksum validity is not product or publication allocation.