IsDuplicatedMask / Boolean Layer

Create boolean mask columns identifying duplicate values in specified columns. Similar to pandas duplicated(keep=False) or dplyr's duplicated(). Returns True for ALL occurrences of values that appear more than once.

Common applications:

Detecting duplicate records
Finding repeated transactions
Identifying redundant entries
Data cleaning
Quality control checks

Example:

Index	Value	Is Duplicated
0	apple	true
1	banana	true
2	apple	true
3	orange	false
4	banana	true

Table

Mask

[, ...]

List of duplicate checking operations to perform. Each mask creates a new boolean column. Common scenarios:

Finding all duplicate customer records
Identifying all repeated transactions
Detecting all redundant measurements
Marking all duplicate entries

At least one mask must be specified.

Select

column

The column to check for duplicates. Works with any data type. The mask will be a boolean column where:

True indicates a value that appears multiple times (ALL occurrences)
False indicates values that appear exactly once

Useful for finding ALL rows involved in data redundancy.

AsColumn

name

Name for the new column. If not provided, the system generates a unique name. If AsColumn matches an existing column, the existing column is replaced. The name should follow valid column naming conventions.