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From the Water Cooler

As a ‘water cooler’ of sorts for this community, we meet some amazing people. Doug Burke shares with us how easy Power Query makes it to do powerful cleaning with a click of the mouse.

The Problem

If you’re like me, you get crappy data from your source systems.  Not that the data is inaccurate. No. It’s just that the data does not fit your view of the world. It doesn’t suit your needs right out of the box. That makes it crappy.

You need to clean it to make it usable. You need the ‘power’ of Power Query to turn night into day.

Did you know that Power Query’s most potent data cleanups are just a right-click away? Let me share the secret.

It’s a simple three-step process:

1. Import data into Power Query

2. Right-click a column

3. Select a data cleaning function

Let’s take a look . . .

right click

Try it yourself. Import some data. Right-click a column. Look at all those functions.

I count 42 data cleaning possibilities just from what’s visible. That doesn’t even include the additional transformation powers of ‘Group By,’ ‘Add Column From Examples’ and ‘Add as New Query.’

A whole lot of something is going on here.

Let’s start with a simple example. We’ll use right-click-column to fix inconsistent customer names.

• Customer XYZ sometimes is listed as XY&Z. We need to remove the ‘&’ symbol.

remove charachter


Select customer column


Replace Values

Your first reaction may be ‘So what. I can do the same thing with Excel’s Search and Replace’. True, but you would miss out on Power Query’s creating a series of ‘Applied Steps’ that are consistent, repeatable and set you up for more data transformations within the Power Query Editor.

Another example, this time using two columns. Find the unique instances of products bought by customers. It’s not as simple as it sounds because different customers purchase different products. You want to quickly see the unique combinations of which customers bought what products and exclude the duplicates.

Distinct List


Remove Other Columns


Remove Duplicates

A quick review of using right-click column data cleanups:

  • Consistent
  • Repeatable
  • Sets you up for more data transformations within the Power Query Editor

How about one more example to drive the point home? This time, let’s fill in missing customer names. This is a frequent problem if your source data is an existing formatted report which excludes repeating values. Power Query can handle it in a snap.

Before/After Fill down


Fill down


Filled table

‘Right-click-column’ is a fast, convenient way to get the job done. No need to review the Power Query ribbons for column cleanups functions. There are so many readily-available combinations that it boggles my mind.

Bonus: when done, you have a sequenced workflow (know as ‘Applied Steps’) that can be repeated the next time you get data.

Simple, right? That’s the point – – Power Query makes it simple. Right-click-column makes it simpler! Win-win!!

I am not saying this is the only way to clean up data. Or even the best way. But I am saying it’s a quick way. And sometimes its better to be quick than good.

Full disclosure: I’m using Excel 2013 Professional Plus 64-bit (2.49.4831.381). Your mileage may vary depending on your version of Excel and Power Query.

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Doug Burke

Doug is an independent consultant ( with 20+ years of experience creating Financial data and analytics systems at Fortune 500 companies.

He believes in the ability of Power Query and Power BI to
• Encourage your data dreams
• Fix your data challenges
• Lead you to ongoing data success

This Post Has 6 Comments
  1. Great post. Though PQ has a TON of bells and whistles, I find that simple, straightforward tips such as this are what get the more casual users of Excel on board. Thanks!

  2. Great article! I am trying to introduce my coworkers to Power Query. Some are slow to change their ways. This article may help them to see what can be done.

  3. This is more magical than the magic I was using last month. I was already using everything you mention here EXCEPT, it is better and quicker using this right click functionality, which was new to me.

    Thanks for this revelation!

  4. Has anyone had issues with it not cleaning (via CLEAN or TRIM) char 160, which is called a “non-breaking space” which will not match up with char 32, which is a normal space.

    1. Yes. I had data from a Windchill database that was driving me mad. It wasn’t until I pasted the offending data into Word that I could see why it was happening. Apparently data had been copied from HTML docs into the database. I created a step to replace the 160s with 32s. Once I knew what the problem was, I could handle it easily but until then I spent a bit of time muttering unladylike language under my breath.

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