Power Query is a powerful tool for transforming and analyzing data, but like any data processing tool, it can sometimes encounter errors. Whether it’s due to invalid data types, missing values, or API connection issues, handling errors effectively is essential to maintaining accurate and reliable reports.

In this blog, we’ll explore various techniques for error handling in Power Query, including how to debug errors, apply error-prevention strategies, and fix common issues that arise when working with data.

1. Types of Errors in Power Query

Before diving into error-handling techniques, it’s helpful to understand the common types of errors you might encounter in Power Query:

a) Data Type Errors

• Occur when Power Query is unable to convert a value to the expected data type (e.g., trying to convert text to a number).
• Example: “We couldn’t convert to Number.”

b) Missing Data Errors (Null Values)

• Caused by missing or incomplete data, which can affect calculations or transformations.
• Example: “The column contains blank values.”

c) API or Web Connection Errors

• Happen when connecting to APIs or web sources due to authentication issues, timeouts, or rate limits.
• Example: “The connection was refused by the server.”

d) Formula Syntax Errors

• Result from incorrect formulas or M code expressions.
• Example: “Token Literal Expected.”

2. Debugging Errors in Power Query

Debugging is a critical part of error handling. Power Query provides several tools and features to help you identify and resolve errors quickly.

a) Identify the Error Source

1. Error Indicator: When Power Query encounters an error, it displays an “Error” message in the affected rows.
2. View Error Details: Click on the “Error” message to see more details about the error, including its source and a description.
3. Step-by-Step Analysis: Errors are often introduced at a specific transformation step. Use the Applied Steps pane to identify the step where the error occurred.

b) Enable “Keep Errors” and “Remove Errors” Options

• Keep Errors: This option allows you to isolate error rows for further inspection. To use it:
  • Select the column with errors.
  • Go to Home > Keep Rows > Keep Errors.
• Remove Errors: This option lets you remove error rows if they are not critical to your analysis.

c) Check Data Types

Ensure that columns have the correct data types (e.g., text, number, date). Incorrect data types are a common cause of errors in Power Query.

3. Error-Handling Techniques in Power Query

Power Query provides built-in functions and techniques to handle errors gracefully and prevent them from breaking your queries.

a) Using the Try...Otherwise Function

The Try...Otherwise function allows you to catch errors and provide an alternative value if an error occurs.

Syntax:

vbnetCopyEdit= Try [Your Expression] Otherwise [Alternative Value]  

Example:

If you’re dividing two numbers and want to handle division by zero errors:

vbnetCopyEdit= Try [Sales Amount] / [Units Sold] Otherwise 0  

This expression will return 0 instead of an error if [Units Sold] is 0.

b) Replacing Errors with a Default Value

You can replace errors in a specific column with a default value using the Replace Errors option:

1. Select the column with errors.
2. Right-click and choose Replace Errors.
3. Enter the value you want to use as a replacement (e.g., 0 for numeric errors).

c) Handling Null Values

Null values can cause errors in calculations. To handle null values:

• Use the Fill Down or Fill Up options to propagate existing values.
• Replace null values with default values (e.g., 0 or “Unknown”) using Replace Values.

4. Common Error Scenarios and How to Fix Them

Scenario 1: Data Type Conversion Errors

Problem:

You’re trying to convert a text column to a number, but some values contain non-numeric characters.

Solution:

1. Use the Remove Errors option to eliminate non-numeric values.
2. Use the Try...Otherwise function to handle invalid conversions: pgsqlCopyEdit= Try Number.From([Column]) Otherwise null

Scenario 2: API Connection Errors

Problem:

Your API connection fails due to an invalid key or rate limit.

Solution:

1. Check the API key and endpoint URL.
2. Implement retry logic using the Try...Otherwise function to handle temporary connection issues. csharpCopyEdit= Try Web.Contents("https://api.example.com/data") Otherwise null

Scenario 3: Missing Data (Null Values)

Problem:

Null values in your dataset are causing errors in calculations.

Solution:

• Replace null values with default values (e.g., 0 for numeric columns).
• Use conditional logic to handle null values: sqlCopyEdit= if [Column] = null then "Unknown" else [Column]

5. Best Practices for Error Handling in Power Query

To minimize errors and improve query performance, follow these best practices:

a) Validate Data Before Applying Transformations

Check for null values, incorrect data types, and duplicate rows before performing calculations.

b) Use Conditional Logic

Use if...then...else statements or the Try...Otherwise function to handle potential errors in your queries.

c) Keep Your Queries Modular

Break complex queries into smaller, modular queries. This makes it easier to debug and isolate errors.

d) Document Your Queries

Add comments to your M code to explain complex logic and error-handling techniques.

6. Conclusion

Error handling is an essential skill for anyone working with Power Query. By understanding common error types, using built-in debugging tools, and applying error-handling functions like Try...Otherwise, you can create more robust and error-resistant queries.

Whether you’re dealing with messy data, API connections, or complex calculations, the techniques covered in this blog will help you debug and fix issues efficiently, ensuring that your Power Query workflows run smoothly.

Ready to take your Power Query skills to the next level? Check out our other Power Query tutorials for more tips, tricks, and advanced techniques!