Power Query M Language Tips
M Language is the backbone of Power Query, enabling users to clean, filter, and structure data efficiently. These tips help improve query performance, maintainability, and accuracy.
1. Use Let-In Structure for Readability
The let…in structure improves code organization by defining steps sequentially.
let Source = Excel.CurrentWorkbook(){[Name="Sales"]}[Content], FilteredRows = Table.SelectRows(Source, each [Revenue] > 1000) in FilteredRows Tip: Assign meaningful names to each step for better readability.
2. Optimize Performance with Query Folding
Query folding pushes transformations to the data source, improving efficiency. To ensure query folding:
- Filter data at the earliest step.
- Use built-in transformations instead of custom M code.
- Right-click a step and select “View Native Query” to check if query folding is happening.
let FilteredData = Table.SelectRows(Source, each [OrderDate] >= #date(2023, 1, 1)) in FilteredData Tip: Avoid breaking query folding by using unsupported operations too early.
3. Reduce Data Load for Faster Queries
- Remove Unnecessary Columns: Keep only relevant columns.
- Filter Data Early: Exclude unwanted rows at the source.
- Limit Rows: Use Table.FirstN() for testing.
let TrimmedData = Table.RemoveColumns(Source, {"UnnecessaryColumn"}) in TrimmedData Tip: Avoid loading entire tables when only a subset is needed.
4. Use Variables to Simplify Calculations
Define variables in let statements to store reusable calculations.
let BasePrice = 100, Discount = 0.1, FinalPrice = BasePrice * (1 - Discount) in FinalPrice Tip: Variables improve efficiency by avoiding redundant calculations.
5. Handle Errors Gracefully
Use try…otherwise to prevent query failures when errors occur.
let SafeDivide = (x as number, y as number) => try x / y otherwise null in SafeDivide(10, 0) Tip: Replace errors with default values or log them for debugging.
6. Use Custom Functions for Reusability
Create reusable M functions to simplify repetitive tasks.
let Capitalize = (text as text) => let FirstLetter = Text.Upper(Text.Start(text, 1)), Rest = Text.Lower(Text.Middle(text, 1)) in FirstLetter & Rest in Capitalize("power query") Tip: Store functions in separate queries and reference them when needed.
7. Convert Data Types Early
Set correct data types at the earliest step to prevent conversion errors.
let ConvertedTable = Table.TransformColumnTypes(Source, {{"Date", type date}, {"Revenue", type number}}) in ConvertedTable Tip: Avoid using “Any” type, as it can cause unexpected errors.
8. Use Table.Buffer() for Large Datasets
Table.Buffer() stores data in memory to prevent repeated evaluations.
let BufferedTable = Table.Buffer(Source) in BufferedTable Tip: Use this only when needed, as it increases memory usage.
9. Avoid Complex Nested Functions
Break down complex logic into multiple steps for better readability and performance.
Before (Nested Functions):
Table.SelectRows(Table.TransformColumnTypes(Source, {{"Revenue", type number}}), each [Revenue] > 1000) After (Step-by-Step):
let Converted = Table.TransformColumnTypes(Source, {{"Revenue", type number}}), Filtered = Table.SelectRows(Converted, each [Revenue] > 1000) in Filtered Tip: Breaking down logic improves maintainability and debugging.
10. Use List Functions for Advanced Transformations
Power Query supports powerful list functions for data manipulation.
- List.Generate() – Create dynamic sequences.
- List.Distinct() – Remove duplicates.
- List.Transform() – Apply a function to each list item.
let Numbers = List.Generate(() => 1, each _ <= 10, each _ + 1) in Numbers Tip: Lists are useful for dynamic date ranges and iterative calculations.
Conclusion
Mastering M Language in Power Query improves data transformation efficiency, enhances performance, and simplifies complex logic. By following these tips—optimizing query folding, reducing data load, using custom functions, and handling errors—you can create more powerful and efficient Power BI and Excel queries.
