How to Combine CSV Files from a Folder in Power Query
You are using Power Query to combine data from multiple CSV files in a folder. Each file has the same structure. You want to append all rows into a single table. Which Power Query function should you use?
Quick Answer
The answer is the Combine Files transformation from the folder connector. This is correct because when you connect to a folder containing multiple CSV files with identical structures, Power Query automatically generates a 'Combine Files' step that uses the Table.Combine function under the hood to append all rows into a single unified table. On the Microsoft Power BI Data Analyst PL-300 exam, this tests your understanding of the folder connector workflow and how Power Query handles bulk data ingestion—a common trap is confusing this with the Merge Queries function, which joins columns rather than appending rows. To combine csv files from a folder in Power Query, always look for the automatic 'Combine Files' prompt after selecting the folder; this is the exam’s preferred method for appending identically structured files. Memory tip: think "Folder first, then Combine" to avoid manually writing M code for Table.Combine.
⚠ Common exam trap
Many candidates confuse 'Append Queries' (which is a manual, query-level operation) with the automated 'Combine Files' feature that the folder connector provides, leading them to pick Option B instead of recognizing that the folder connector's built-in combine functionality is the correct and intended method for this scenario.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Combine Files from the folder connector.
The 'Combine Files' transformation in Power Query is specifically designed to import and append multiple CSV files from a folder into a single table. When you connect to a folder using the 'From Folder' connector, Power Query automatically generates a 'Combine Files' step that uses the 'Table.Combine' function under the hood, which appends all rows from identically structured files into one unified table.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Group By.
Why it's wrong here
Group By aggregates rows, it does not combine files.
- ✗
Append Queries.
Why it's wrong here
Append Queries combines tables already loaded into the Power Query Editor, not files from a folder. The scenario requires reading and merging raw CSV files directly from a folder source, which is achieved by the Combine Files transform that automatically invokes a sample file and applies the same steps to all files. Append Queries is tempting because it correctly merges rows from multiple tables, and would be the right choice if the CSV files were first individually imported as separate queries before appending.
- ✗
Merge Queries as new.
Why it's wrong here
Merge Queries joins tables horizontally based on a key, not vertically.
- ✓
Combine Files from the folder connector.
Why this is correct
The folder connector with Combine Files automatically appends all CSV files.
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Same concept, more angles
3 more ways this is tested on PL-300
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. You are using Power Query Editor to combine multiple CSV files from a folder. Each file has the same structure except that some files have an extra column 'Region' that is not present in others. You need to merge all files into one table, ensuring that the 'Region' column appears for all rows, with nulls where missing. Which combine files option should you select?
medium- A.Use 'Combine & Load' and then manually add the missing column.
- B.Use 'Sample File' and then refresh.
- ✓ C.Use 'Combine & Transform' and then edit the function to include all columns.
- D.Use 'Append Queries' after loading each file separately.
Why C: Power Query's 'Combine & Transform' generates a function that you can edit to explicitly include all columns from all files, even those that appear only in some files. By modifying the function to reference all columns (e.g., using `Table.ColumnNames` or a custom column list), the resulting merged table will contain the 'Region' column with null values for rows from files that lack it. This approach handles schema drift automatically without manual post-processing.
Variation 2. You have a Power Query transformation that combines data from multiple Excel files in a folder. Each file has a different structure. You need to identify which TWO actions will help standardize the data before combining. (Choose two.)
medium- A.Filter out rows with null values.
- B.Merge all files into one table before cleaning.
- ✓ C.Use the Combine Files function and select a sample file to define the transformation.
- ✓ D.Promote the first row as headers in each file.
- E.Remove all columns except the ones you need from a single file.
Why C: The Combine Files function in Power Query allows you to select a sample file to define a single transformation logic that is then applied to all files in the folder. This is essential when files have different structures, as it standardizes the data by using the sample file's schema as a template, ensuring consistent column names, data types, and transformations across all files.
Variation 3. You are reviewing a Power Query query that combines data from multiple CSV files in a folder. The query uses the 'Combine Files' function. Which TWO actions can you take to improve the performance of this query?
medium- A.Load all data to the data model without filtering.
- ✓ B.Disable the 'Promote Headers' step if the headers are not needed.
- C.Increase the scheduled refresh frequency.
- ✓ D.Filter the folder to include only relevant files before combining.
- E.Enable 'Fast Combine' in the Power Query options.
Why B: Disabling the 'Promote Headers' step reduces the number of transformations applied to each file during the combine operation. When headers are not needed, skipping this step avoids an extra row promotion and type detection pass, which can significantly reduce query execution time, especially when combining many files.
JA
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Senior Network & Security Engineer · founder of Courseiva
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