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Transforming Lists to Maps in Kotlin: A Detailed Guide

Anastasios Antoniadis

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Learn how to efficiently transform lists into maps in Kotlin using associateBy, associateWith, and associate functions. This detailed guide covers basic transformations, custom key-value pair creation, and handling duplicate keys, providing you with the tools to manage collections effectively in your Kotlin applications.


With its concise syntax and powerful standard library, Kotlin has become a favorite among developers, particularly those working on Android and server-side applications. One common programming task is converting a list of objects into a map for more efficient data retrieval. Kotlin’s collection processing capabilities make this task straightforward and elegant. This article explores various methods to transform lists into maps in Kotlin, highlighting the flexibility and efficiency of Kotlin’s approach.

Basic Transformation Using associateBy and associateWith

Kotlin provides several extension functions for converting collections. The associateBy and associateWith functions are among the simplest and most commonly used for transforming lists into maps.

Using associateBy

The associateBy function is ideal when you want to use a unique attribute of the objects in your list as the key in the resulting map.

data class Person(val id: Int, val name: String)

val people = listOf(Person(1, "John Doe"), Person(2, "Jane Doe"))
val peopleMapById = people.associateBy { it.id }

// Output: {1=Person(id=1, name=John Doe), 2=Person(id=2, name=Jane Doe)}

In this example, associateBy takes a lambda function that specifies the attribute of Person objects to use as keys (id in this case), producing a map where each key is a person’s ID and each value is the corresponding Person object.

Using associateWith

Conversely, if you want to create a map where the keys are the objects in your list and the values are derived from those objects, you can use associateWith.

val namesToLength = people.associateWith { it.name.length }

// Output: {Person(id=1, name=John Doe)=8, Person(id=2, name=Jane Doe)=8}

Here, associateWith creates a map where each Person object is a key, and the length of each person’s name is the value.

Custom Transformations Using associate

For scenarios that require more control over both keys and values of the resulting map, Kotlin offers the associate function. It allows you to define custom transformations for both by using a lambda function that returns a Pair.

val customMap = people.associate { it.id to it.name.uppercase() }

// Output: {1=JOHN DOE, 2=JANE DOE}

This code snippet transforms the list into a map with person IDs as keys and their names in uppercase as values.

Handling Duplicate Keys

When using associateBy, associateWith, or associate, if the lambda functions produce duplicate keys, only the last entry for each key is retained in the map. This behavior is often desirable, but when you need to aggregate or handle duplicates differently, you’ll have to use a more manual approach.

Aggregating Duplicate Keys

You can use groupBy followed by mapValues to handle duplicate keys by aggregating the values into a list or using another aggregation strategy.

val peopleByName = people.groupBy { it.name }
    .mapValues { (_, people) -> people.map { it.id } }

// Output for a list with duplicate names would aggregate IDs into a list

This approach groups Person objects by name, then transforms each group into a map where names are keys and lists of IDs are values.


Kotlin’s collection processing functions provide developers with powerful tools to transform lists into maps efficiently, making data manipulation tasks more concise and readable. Whether you need a straightforward transformation with associateBy or associateWith, or you require more control with associate, Kotlin has you covered. Additionally, understanding how to handle duplicate keys ensures you can confidently tackle more complex data transformation tasks. By leveraging these capabilities, Kotlin developers can write cleaner, more efficient code for managing collections in their applications.

Anastasios Antoniadis
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