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How to Delete Columns in Excel (5-Minute Guide)

In this article, you will learn two simple ways to delete columns in Excel workbooks.

Method 1: Deleting a column in Excel using the ‘Delete’ function

Step 1: Select the column which you wish to delete by left-clicking on the column header.

Step 2: Right-click on the column header and select the ‘Delete’ option. The column selected in step 1 will be deleted.

For example: If you wish to delete the ‘Total’ column (column O) from the Profit and Loss statement shown in the image below -> Left click on column O in the column header section -> Then right-click and select the ‘Delete’ option. 

Steps to follow while deleting a column in Excel using the ‘Delete’ function

Method 2: Removing a column in Excel using keyboard shortcuts

Step 1: Select the column which you wish to delete by left-clicking on the column header.

Step 2: Using the keyboard, press and hold the “CTRL” (“Command” in case of Mac) and “-” keys. The column selected in step 1 will be deleted.

Can I quickly delete multiple columns in Excel?

Yes, Excel can be used to easily delete multiple adjacent columns together. However, if you wish to delete multiple non-adjacent columns, you will need to individually delete each column.

Method 1: Deleting multiple columns in Excel using the ‘Delete’ function

Step 1: Select all the columns you wish to delete.

Learn how to select more than one column in Excel: How to Select Multiple Columns in Excel

Step 2: Right-click on the column header section and select the ‘Delete’ option. All the adjacent columns selected in step 1 will be deleted.

Method 2: Removing multiple columns in Excel using Keyboard Shortcuts

Step 1: Select all the columns you wish to delete.

Learn how to select more than one column in Excel: How to Select Multiple Columns in Excel

Step 2: Using the keyboard, press and hold the “CTRL” (“Command” in case of Mac) and “-” keys. The multiple adjacent columns selected in step 1 will be deleted.

Learn how to do this step-by-step in the video below 👇

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