Remove Rows Using Power Query

Power Query lets you perform a series of steps to transform your messy Excel data.

One of the most common steps I do, is  to clean my data and remove rows, and Power Query gives you a lot of options to do so!

Here is our source table that we want to modify:

Let’s go through the steps in detail:

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STEP 1: Our sample data contains the Sales numbers for each month. Let us first prepare to use this data in Power Query.

Go to Data > Get & Transform > From Table (Excel 2016) or Power Query > Excel Data > From Table (Excel 2013 & 2010)

Excel 2016:

Excel 2013 & 2010:

STEP 2: This will open up the Power Query Editor.

If you go to Home > Reduce Rows > Remove Rows

There are a lot of options! Let us see these 3 in action:

• Remove Top Rows
• Remove Bottom Rows
• Remove Alternate Rows

STEP 3: Go to Home > Reduce Rows > Remove Rows > Remove Top Rows

Let us try to remove the first two rows. Input 2 as the number of rows. Click OK.

You can see January and February are now removed.

STEP 4: Go to Home > Reduce Rows > Remove Rows > Remove Bottom Rows

Let us try to remove the bottom two rows. Input 2 as the number of rows. Click OK.

You can see November and December are now removed.

STEP 5: Go to Home > Reduce Rows > Remove Rows > Remove Alternate Rows

This is a bit trickier to use. Let us say we want to remove the following months: 3 (March), 6 (June) and 9 (September).

To do that, let us input the following:

• First row to remove – 1
• Number of rows to remove – 1
• Number of rows to keep – 2
• Click OK.

This will remove starting from the first row, then the pattern is that row will be removed, then skip the next 2 rows, then do the same pattern again. Essentially it means removing the first row of every 3 rows.

You can see March, June, and September are now removed.

STEP 6: Click Close & Load from the Home tab and this will open up a brand new worksheet in your Excel workbook with the new data.

You now have your new Excel table with the cleaned up rows!

How to Remove Rows Using Power Query

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