Boolean Token Normalizer
Normalize trimmed case-insensitive yes/no, true/false, and 1/0 column cells into booleans, returning a cell-specific error for unknown tokens.
Description
Boolean columns often mix human-readable tokens and numeric-looking text.
Boolean columns often mix human-readable tokens and numeric-looking text. A controlled mapping turns these known spellings into booleans while rejecting unknown values that could otherwise be silently misinterpreted.1
Normalize trimmed case-insensitive yes/no, true/false, and 1/0 column cells into booleans, returning a cell-specific error for unknown tokens.
When to use Boolean Token Normalizer
Use this tool to normalize trimmed case-insensitive yes/no, true/false, and 1/0 column cells into booleans, returning a cell-specific error for unknown tokens.
Choose the original CSV text, decoded cell strings, byte values or counts requested by this tool. Use the stated delimiter, encoding, indexing and number/date convention.
How to use Boolean Token Normalizer and understand its results
- Choose the original CSV text, decoded cell strings, byte values or counts requested by this tool. Use the stated delimiter, encoding, indexing and number/date convention.
- Enter values using the field table and calculation rules, then run the tool.
- Read values. The explanation below defines the units, signs, ordering and any flags or placeholder values.
- If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.
| Input field | Meaning | Value type; see rules below | Requirement |
|---|---|---|---|
| values | Values | list of string; maximum length: 10000; minimum entries: 0; maximum entries: 10000 | Required |
Provide decoded cell strings. Each cell is trimmed and lowercased before matching the six supported tokens. The result is an aligned boolean list. A blank or unrecognized token returns a cell-specific input error for the entire request; an empty input list returns an empty list.
true tokens = yes, true, 1; false tokens = no, false, 0 Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| values | Values | list of boolean |
{
"input": {
"values": [
" YES ",
"false",
"1",
"0"
]
},
"output": {
"values": [
true,
false,
true,
false
]
}
}Limitations and assumptions
This is a deliberate token mapping, not JavaScript truthiness or numeric coercion. It does not accept y/n, on/off, arbitrary nonzero numbers or localized words, and does not provide a separate null/missing-value convention.
Numeric inputs must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Cell-string lists also have a combined text budget of 100,000 UTF-16 units per list. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.
Alternative or Complementary methods
Use Column Type Inference From Sample: Infer empty, integer, decimal, or string from a column sample using ASCII decimal token syntax; blanks are ignored and leading-zero identifiers remain strings. For a complementary task, use Accounting Dash-for-Zero Normalizer: Replace cells consisting of a trimmed ASCII accounting dash with the exact string 0, preserving all other cell text including numeric signs and Unicode dashes.
References
-
Boolean Token Normalizer — tool.io
Similar or alternative tools
- Column Type Inference From Sample
Infer empty, integer, decimal, or string from a column sample using ASCII decimal token syntax; blanks are ignored and leading-zero identifiers remain strings.
- Accounting Dash-for-Zero Normalizer
Replace cells consisting of a trimmed ASCII accounting dash with the exact string 0, preserving all other cell text including numeric signs and Unicode dashes.