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How to Write Power Query M Code with ChatGPT

How to Write Power Query M Code with ChatGPT
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What Is Power Query M Code?

What Is Power Query M Code?

Power Query M is a formula language used in Microsoft Excel and Power BI to import, clean, reshape, and transform data. ChatGPT can help you write M code by converting plain English instructions into practical queries. This makes data preparation easier, especially for beginners unfamiliar with M syntax and functions.

Prepare Your Data Requirements

Prepare Your Data Requirements

Before using ChatGPT, identify your data source, column names, and desired output. Explain whether you are working with Excel files, CSV datasets, databases, or Power BI queries. Clearly describe the transformation you need, such as removing duplicates, filtering records, replacing values, or combining multiple tables for analysis.

Write Effective Prompts

Write Effective Prompts

Give ChatGPT specific instructions about your data and expected results. For example, ask it to remove duplicate rows based on an Employee ID column and explain the generated M code. Include sample column names, data types, and conditions. Detailed prompts generally produce more relevant, usable code for your workflow.

Generate M Code with ChatGPT

Generate M Code with ChatGPT

Ask ChatGPT to create Power Query M code for your transformation requirements. For example, request code that filters sales records where the amount exceeds 10,000. ChatGPT can generate the query, explain individual steps, and suggest improvements. Always verify the output against your dataset before using it in production.

Apply Code in Power Query

Apply Code in Power Query

Open Power Query Editor in Excel or Power BI. Select Advanced Editor, review the existing query, and insert or modify the generated M code. Ensure the source step references the correct table or file. Click Done, inspect the preview, and confirm that the transformed data matches your requirements.

Debug Errors and Improve Code

Debug Errors and Improve Code

If your query produces an error, share the error message and relevant M code with ChatGPT. Ask it to identify the cause and suggest a corrected version. Common issues include incorrect column names, incompatible data types, missing values, and syntax mistakes. Test each correction to ensure the results remain accurate.

Validate and Optimize Your Queries

Validate and Optimize Your Queries

ChatGPT can help simplify repetitive transformations and improve query readability. However, generated code may contain incorrect assumptions or inefficient steps. Validate row counts, data types, duplicates, and calculated values before publishing reports. For sensitive datasets, avoid sharing confidential information. Use ChatGPT as a coding assistant, not a replacement for testing.

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