Just use the filter button on salary column and remove any “null” values. Remove staff with no salary: This operation is also called “Filtering”.Replace missing values – gender & department columns: Select each column with missing data and either right click or use “replace values” button to find & replace nulls with alternative values.Just use “Remove columns” button to nix them. Remove blank columns: The file also loads a few blank columns.From home ribbon, just tap on the “use first row as headers” button. Promote headers: Now that our data is has no extra rows on top, let’s use row number 3 as header.From “Home ribbon” in Power Query editor, using the “Remove rows” button, remove top 2 rows. Remove top rows: The file contains 2 rows of header information which is not needed.Once the data is loaded into Power Query, you can quickly apply all the necessary data cleansing steps in there. Step 2: Apply data cleansing steps in Power Query Close & Load button: This button, also shown as “Publish” in Power BI is what we use to close Power Query and return to main application (Excel or Power BI).You can enable / disable this formula bar from “View ribbon”. Formula bar (optional): The optional formula bar shows corresponding M Language code for current step.We use this to make changes to the query or delete any steps. Query settings: You can adjust query name, see all the applied steps here.This data view looks almost like Excel spreadsheet view. As you make changes to the data, this preview is updated. Data view: You find the preview of current step of selected query here.You can select a query to preview its results and work on it. Queries Pane: This is where all the queries (or connections) you have in the workbook are listed.The other ribbons are transform, add column and view. There is home ribbon where common query options like column / row adjustments, clean-up and joins are found.

Ribbon: You will see the ribbons on top of Power Query editor UI.

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