Excel Clean Up with Power Query: Say Goodbye to Messy Data Forever

Bottom Line: Learn how Power Query can be used to quickly clean up messy data.

Skill Level: Beginner

Whether you're dealing with messy spreadsheets or CSV files, the process of cleaning up data can be daunting.

Fortunately, Excel provides powerful tools like Power Query to streamline this task. In this guide, we'll walk you through the process of data cleanup using Excel, focusing on the invaluable Power Query feature.

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You can download the example files from our full Power Query guide linked here.

Why Data Cleanup Matters

Before diving into the details, let's understand why data cleanup is essential.

Messy data can lead to inaccuracies, hinder analysis, and make it challenging to derive meaningful insights. Whether you're working with task lists, sales data, or any other dataset, a clean and organized structure is the foundation for effective data analysis.

Using Power Query for Data Cleanup

One of Excel's hidden gems for data cleanup is Power Query. In the provided example, we have a daily task list in CSV format that needs refinement. Here's a step-by-step guide:

1. Importing Data

Begin by navigating to the “Data” tab and selecting “From Text/CSV.”

Use the From Text/CSV button in Excel to clean up messy data with Power Query

Locate your file and hit “Import.” Once imported, click “Transform Data” to open the Power Query editor.

transform data with power query to clean up messy excel data

2. Removing Unnecessary Columns

Identify columns that are surplus to your requirements. In this example, the shipping address information is unnecessary. Select the relevant columns, right-click, and choose “Remove Columns.”

3. Eliminating Blank Rows

Cleanse your dataset further by removing any blank rows. A clutter-free dataset ensures accurate analysis and visualization.

Check out our tutorial on other ways to eliminate blank rows here.

4. Sorting Data

Organize your data according to your needs. In our example, the boss wants the data sorted by customer name. Utilize the sorting options in the Power Query editor to achieve this.

5. Closing and Loading the Data

Once your data is refined, close the Power Query editor and load the results into a new sheet in the workbook. This ensures a neat and organized presentation of your cleaned-up data.

Don't forget to click Close & Load to save your cleaned up data in Excel and load it into your original workbook

Automating the Process with Power Query

One of the standout features of Power Query is its ability to automate the cleanup process.

Simply refreshing the query reruns all the defined steps, making it a breeze to update your data regularly.

This is particularly handy for tasks like daily updates or handling dynamic datasets.


Mastering data cleanup with Excel, especially with the help of Power Query, empowers you to efficiently manage and analyze your data.

Don't forget to check out our full guide and download the example files here.

Will you be using Power Query to clean up your data? Let us know in the comments below.


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