--- schema_version: "1" id: 05cc6221773a232c64adb85bba60c823ba40f5c2252a9302376a965d3ebd2597 title: Map Objects collection: mulesoft version: current locale: en-us portal_url: https://docs.salesforce.com/mulesoft/current/en-us/dataweave/2.11/dataweave-cookbook-map-an-object.md canonical_url: https://docs.mulesoft.com/dataweave/2.11/dataweave-cookbook-map-an-object source_site: docs.mulesoft.com content_type: documentation content_hash: 42cd6ba6400a305a696569eb86475e671f9c9bcc1d604e74cbea77189e5a8543 description: MuleSoft Documentation Site release: "2.11" latest: false --- --- product: DataWeave version: 2.11 keywords: studio, anypoint, transform, transformer, format, aggregate, rename, split, filter convert, json, metadata, dataweave, data weave, datamapper, dwl, dfl, dw, output structure, input structure, map, mapping, as --- # Map Objects > For the full documentation index, see: https://docs.mulesoft.com/llms.txt The following DataWeave examples use the `mapObject` function to iterate through the keys and values of objects. ## First Example This example uses both the `map` and `mapObject` functions to iterate through the input and set all of the keys to upper case. The example uses these DataWeave functions: - `map` to go through the elements in the "books" array. - `mapObject` to go through the keys and values in each of the objects of the array. - `upper` to set each key to upper case. DataWeave Script: ```dataweave %dw 2.0 output application/json --- items: payload.books map (item, index) -> { book: item mapObject (value, key) -> { (upper(key)): value } } ``` Input JSON Payload: ```json { "books": [ { "-category": "cooking", "title": "Everyday Italian", "author": "Giada De Laurentiis", "year": "2005", "price": "30.00" }, { "-category": "children", "title": "Harry Potter", "author": "J K. Rowling", "year": "2005", "price": "29.99" }, { "-category": "web", "title": "XQuery Kick Start", "author": [ "James McGovern", "Per Bothner", "Kurt Cagle", "James Linn", "Vaidyanathan Nagarajan" ], "year": "2003", "price": "49.99" }, { "-category": "web", "-cover": "paperback", "title": "Learning XML", "author": "Erik T. Ray", "year": "2003", "price": "39.95" } ] } ``` Output JSON: ```json { "items": [ { "book": { "-CATEGORY": "cooking", "TITLE": "Everyday Italian", "AUTHOR": "Giada De Laurentiis", "YEAR": "2005", "PRICE": "30.00" } }, { "book": { "-CATEGORY": "children", "TITLE": "Harry Potter", "AUTHOR": "J K. Rowling", "YEAR": "2005", "PRICE": "29.99" } }, { "book": { "-CATEGORY": "web", "TITLE": "XQuery Kick Start", "AUTHOR": [ "James McGovern", "Per Bothner", "Kurt Cagle", "James Linn", "Vaidyanathan Nagarajan" ], "YEAR": "2003", "PRICE": "49.99" } }, { "book": { "-CATEGORY": "web", "-COVER": "paperback", "TITLE": "Learning XML", "AUTHOR": "Erik T. Ray", "YEAR": "2003", "PRICE": "39.95" } } ] } ``` ## Second Example This example uses the `mapObject` function to iterate through the keys and values of the object that results from using `groupBy` on the payload. If some objects of the input payload have the same values in the `FirstName`, `LastName` and `Age` keys, the DataWeave script transforms those objects into a single row in a CSV file. The remaining values in the `Team Name` and `Role` keys for those objects are concatenated with `:` in the single CSV row. Input JSON Payload: ```json [ { "Sr.No.": 1, "FirstName": "Charles", "LastName": "Lock", "Age": 40, "Team Name": "Scrum team 1", "Role": "developer" }, { "Sr.No.": 2, "FirstName": "Josh", "LastName": "Rodriguez", "Age": 45, "Team Name": "architecture", "Role": "SA" }, { "Sr.No.": 3, "FirstName": "Josh", "LastName": "Rodriguez", "Age": 45, "Team Name": "technology", "Role": "advisor" }, { "Sr.No.": 4, "FirstName": "Josh", "LastName": "Rodriguez", "Age": 35, "Team Name": "development", "Role": "developer" }, { "Sr.No.": 5, "FirstName": "Jane", "LastName": "Rodriguez", "Age": 30, "Team Name": "architecture", "Role": "SA" }, { "Sr.No.": 6, "FirstName": "Jane", "LastName": "Rodriguez", "Age": 30, "Team Name": "Scrum team 1", "Role": "developer" }, { "Sr.No.": 7, "FirstName": "Josh", "LastName": "Lee", "Age": 42, "Team Name": "Scrum team1", "Role": "developer" } ] ``` In the previous input example, `Sr.No. 2` and `Sr.No. 3`, as well as `Sr.No. 5` and `Sr.No. 6`, refer to the same person, as they have the same first name, last name, and age. However, `Sr.No. 4` refers to a different person, as it has the same first and last name but a different age. DataWeave Script: ```dataweave output application/csv --- valuesOf( payload groupBy ((item, index) -> ( item.FirstName ++ item.LastName ++ item.Age)) mapObject ((value, key, index) -> (index): { "Sr.No.": value."Sr.No." joinBy ":", "FirstName": value.FirstName[0], "LastName": value.LastName[0], "Age": value.Age[0], "Team Name": value."Team Name" joinBy ":", "Role": value.Role joinBy ":" }) ) ``` The DataWeave script merges the repeated values of keys `FirstName`, `LastName` and `Age` of the objects with key-value `Sr.No. 2` and `Sr.No. 3`, as well as `Sr.No. 5` and `Sr.No. 6`. These values are separated with `,` in the single CSV row. The values of `Team Name` and `Role` for those objects are concatenated with `:` in the single CSV row. Output CSV: ```CSV Sr.No.,FirstName,LastName,Age,Team Name,Role 1,Charles,Lock,40,Scrum team 1,developer 2:3,Josh,Rodriguez,45,architecture:technology,SA:advisor 4,Josh,Rodriguez,35,development,developer 5:6,Jane,Rodriguez,30,architecture:Scrum team 1,SA:developer 7,Josh,Lee,42,Scrum team1,developer ``` ## Related Examples - [Map Data with DataWeave](https://docs.mulesoft.com/dataweave/2.11/dataweave-cookbook-map) - [Map Object Elements as an Array](https://docs.mulesoft.com/dataweave/2.11/dataweave-cookbook-map-object-elements-as-an-array) - [Extract Data](https://docs.mulesoft.com/dataweave/2.11/dataweave-cookbook-extract-data) - [Transform XML to JSON](https://docs.mulesoft.com/dataweave/2.11/dataweave-cookbook-perform-basic-transformation) - [Rename Keys](https://docs.mulesoft.com/dataweave/2.11/dataweave-cookbook-rename-keys) ## See Also - [DataWeave Types](https://docs.mulesoft.com/dataweave/2.11/dataweave-types) - [DataWeave Selectors](https://docs.mulesoft.com/dataweave/2.11/dataweave-selectors) - [DataWeave Cookbook](https://docs.mulesoft.com/dataweave/2.11/dataweave-cookbook)