[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["이해하기 어려움","hardToUnderstand","thumb-down"],["잘못된 정보 또는 샘플 코드","incorrectInformationOrSampleCode","thumb-down"],["필요한 정보/샘플이 없음","missingTheInformationSamplesINeed","thumb-down"],["번역 문제","translationIssue","thumb-down"],["기타","otherDown","thumb-down"]],["최종 업데이트: 2025-09-04(UTC)"],[[["\u003cp\u003eThis guide details how to manage columns within the Cloud Data Fusion Wrangler workspace, including renaming, copying, deleting, and keeping columns.\u003c/p\u003e\n"],["\u003cp\u003eRenaming a column is done by clicking on the column name and entering the new one, which will add the \u003ccode\u003erename\u003c/code\u003e directive to the recipe.\u003c/p\u003e\n"],["\u003cp\u003eCopying a column involves using the "Copy column" option from the column's dropdown, which then allows you to apply directives to a duplicated column, adding the \u003ccode\u003ecopy\u003c/code\u003e directive to the recipe.\u003c/p\u003e\n"],["\u003cp\u003eDeleting a column is done via the "Delete column" option, reducing the dataset's size and improving pipeline efficiency, and this adds the \u003ccode\u003edrop\u003c/code\u003e directive to the recipe.\u003c/p\u003e\n"],["\u003cp\u003eThe "Keep column" feature deletes all columns except the selected one, making it possible to quickly isolate a single column, which adds the \u003ccode\u003ekeep\u003c/code\u003e directive to the recipe.\u003c/p\u003e\n"]]],[],null,["# Rename, copy, delete, or keep columns\n\nThis page explains how to rename, copy, delete, or keep columns when you prepare\ndata in the Wrangler workspace of the Cloud Data Fusion Studio.\n\nRename a column\n---------------\n\nTo rename a column in the Wrangler workspace, click a column name and enter a\nnew name. Wrangler adds the `rename` directive to the recipe.\n\nCopy a column\n-------------\n\nTo understand the impact of using a new directive on a dataset, you can copy a\ncolumn into a new column with a different name and apply directives there.\n\nTo copy a column, follow these steps:\n\n1. [Go to Wrangler workspace in Cloud Data Fusion](/data-fusion/docs/concepts/wrangler-overview#navigate-to-wrangler).\n2. On the **Data** tab, go to a column name and click the arrow_drop_down expander arrow.\n3. Select **Copy column** and enter a name for the new column.\n\nWrangler copies the column and adds the `copy` directive to the recipe.\n\nDelete a column\n---------------\n\nFor datasets with many columns, you can improve pipeline performance and save\nresources by deleting unnecessary columns. With fewer columns, the pipeline\nrun completes faster. This is especially true for pipelines that include a\nJoiner transformation.\n\nTo delete a column from a dataset, follow these steps:\n\n1. [Go to Wrangler workspace in Cloud Data Fusion](/data-fusion/docs/concepts/wrangler-overview#navigate-to-wrangler).\n2. On the **Data** tab, go to a column name and click the arrow_drop_down expander arrow.\n3. Select **Delete column**.\n\nWrangler deletes the column and adds the `drop` directive to the recipe.\n\nKeep a column\n-------------\n\nYou can keep a column in a dataset and delete all other columns.\n\nTo keep a column, follow these steps:\n\n1. [Go to Wrangler workspace in Cloud Data Fusion](/data-fusion/docs/concepts/wrangler-overview#navigate-to-wrangler).\n2. On the **Data** tab, go to a column name and click the arrow_drop_down expander arrow.\n3. Select **Keep column**.\n\nWrangler deletes all columns in the dataset, except the one you chose, and adds\nthe `keep` directive to the recipe.\n\nWhat's next\n-----------\n\n- Learn more about [Wrangler directives](/data-fusion/docs/concepts/wrangler-overview#apply_directives)."]]
