Where is Advanced Editor in Power BI?

Trying to find the Advanced Editor in Power BI can feel like a scavenger hunt if you don't know where to look. It’s a powerful feature, but it’s tucked away in an area you might not work in every day. This guide will show you exactly where to find the Advanced Editor and how to start using it to fine-tune your data.

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What Exactly Is the Advanced Editor?

The Advanced Editor is a window in Power BI's Power Query Editor that lets you view and edit the source code for your data transformations. This code is written in a language called "M".

Every time you click a button in the Power Query Editor to perform an action - like removing a column, changing a data type, or filtering rows - Power BI writes a corresponding line of M code in the background. The Advanced Editor gives you direct access to this script. You can review all the steps in one place, make small edits that are difficult to do in the user interface, or even write complex custom transformations from scratch.

Think of the regular Power Query interface as a visual way to build your data recipe, and the Advanced Editor as the written recipe card itself. Sometimes, it's just faster and easier to edit the card directly.

Finding the Advanced Editor: A Step-by-Step Guide

The number one reason people can't find the Advanced Editor is that it doesn't live within the main Power BI Desktop report view. It’s located inside the Power Query Editor. Let's walk through the steps to get there.

Step 1: Open the Power Query Editor

First, you need to leave the main report and dashboarding area and open the Power Query Editor, which is where all data transformation takes place.

1. Open your Power BI Desktop file.
2. On the Home ribbon at the top of the screen, find the "Queries" section.
3. Click the Transform data button. This will launch a new window: the Power Query Editor.

Now that you're in the right place, finding the editor is simple.

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Step 2: Choose Your Query

Along the left side of the Power Query Editor, you’ll see the "Queries" pane. This lists all the data tables you’ve connected to your report. The Advanced Editor is context-specific, meaning it will show the M code for whichever query you have selected. Click on the query whose code you want to view.

Step 3: Open the Advanced Editor

You have two easy ways to open the Advanced Editor once in Power Query and with a query selected:

Method 1: From the "Home" Tab

• Make sure you're on the Home tab of the Power Query Editor's ribbon.
• Look for the "Query" section.
• Click the Advanced Editor button.

Method 2: From the "View" Tab

• Click the View tab on the Power Query Editor's ribbon.
• The very first button on the left will be Advanced Editor. Click it.

Both methods open the same "Advanced Editor" window containing the M code for your query. The interface is simple: a main text area for the code, "Done" and "Cancel" buttons, and a status bar at the bottom that will let you know if you have any syntax errors.

Why Use the Advanced Editor? Practical Examples

So, why would a marketer, sales manager, or business owner want to edit raw code? You don't need to be a developer to get value from it. Here are a few simple but powerful reasons to use the Advanced Editor.

1. Adding Comments to Your Steps

If you have a complex query, you might forget why you made a certain transformation a few months down the road. You can add comments in the Advanced Editor to explain your logic for yourself or your teammates.

You can add a single-line comment using two slashes //, or a multi-line comment by starting with /* and ending with */.

let
    Source = Csv.Document(File.Contents("C:\..."),[...]),
    
    // Converted the "Region" column to uppercase for consistency
    #"Capitalized Text" = Table.TransformColumns(Source,{{"Region", Text.Upper, type text}}),

    /*
      The company decided to filter out all returns after Q2 2023.
      This logic was approved by the finance department on 10/25/2023.
    */
    #"Filtered Rows" = Table.SelectRows(#"Capitalized Text", each [Date] < #date(2023, 7, 1))
in
    #"Filtered Rows"

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2. Making Small, Surgical Edits

Imagine you’ve connected to a CSV file. The file path might be hard-coded into your M query. If you move directories or send the file to a colleague, the query breaks. Instead of re-creating the whole connection, you can just open the Advanced Editor and quickly update the file path in the first line of code.

Before:

let
    Source = Csv.Document(File.Contents("C:\Users\sally\Documents\Old Reports\sales_q3.csv"),...)
in
    Source

After:

let
    Source = Csv.Document(File.Contents("C:\Users\john\Documents\Final Data\sales_q3.csv"),...)
in
    Source

3. Implementing Logic You Can't "Click"

Sometimes you want to do something that isn't available as a button in the user interface. For example, maybe you want to combine cells with a conditional rule.

Let's say you have a "Status" column and a "Notes" column. You want to create a new column that shows the status, but if the status is "On Hold", you want it to show "On Hold - " followed by the notes. You could add a custom step in the Advanced Editor to do this.

    ...
    #"Added Conditional Column" = Table.AddColumn(#"Previous Step", "Display Status", 
        each if [Status] = "On Hold" 
             then "On Hold - " & [Notes] 
             else [Status]),
    ...

Copying and pasting M code snippets like this from tutorials is a great way to start leveraging more advanced M functions without having to learn the language from scratch.

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4. Batch Rename Columns Faster

Got a table with dozens of columns with unhelpful names like "col_01", "col_02"? Renaming them one by one in the UI is tedious. With the Advanced Editor, you can use the Table.RenameColumns function to do them all at once.

let
    Source = YourDataSourceHere,
    #"Renamed Columns" = Table.RenameColumns(Source,{
        {"customer_id", "Customer ID"}, 
        {"first_name", "First Name"},
        {"signup_date", "Signup Date"},
        {"last_purchase_amt", "Last Purchase Amount"}
    })
in
    #"Renamed Columns"

This is much faster and provides a clear record of all the changes you made in a single step.

Common Mistakes When Using the Advanced Editor

As you start working with M code, you might run into a few common gotchas. Here’s what to look out for.

• Forgetting the Commas: Every step (or line) in the let block must end with a comma, except for the very last step right before the in statement. The Advanced Editor's syntax checker will often catch this, but it's the most frequent error.
• M Code is Case-Sensitive: Unlike some programming languages, Table.RenameColumns is not the same as table.renamecolumns. Function names and any column names you reference in your code must match case exactly.
• Messing Up the let/in Structure: The let statement opens the block of steps, and the in statement declares which step's output should be returned as the final result of the query. You need to make sure the step named after in matches the name of your final transformation step exactly.
• Breaking the Step Chain: Each step in Power Query typically uses the output of the previous one. If you rename step 2 "Renamed Column", but step 3 still refers to the old name "Changed Type", your query will break. Ensure each step correctly references the variable name from the line before it.

Final Thoughts

Getting comfortable with the Advanced Editor unlocks a deeper level of control over your data in Power BI. You can move beyond the pre-set buttons to create highly customized, efficient, and well-documented queries that speed up your reporting workflow and make your models easier to maintain.

While mastering Power BI's M code is a valuable skill for complex data prep, at Graphed we know that many marketing and sales teams just need quick answers without becoming data engineers. Sometimes you don't want to spend hours inside a query editor just to build one report. That's why we built Graphed to connect to all your data sources like Google Analytics, Shopify, and Salesforce and let you build real-time dashboards using plain English. It's like having a data analyst on your team who works in seconds, not hours.