To handle dynamic column names in Power Query without breaking your transformation steps, several techniques are available to reference column positions and headers or to create a flexible transformation process through list functions. Here are three main approaches:
1. Column Indexing Instead of Hard-Coded Names
Use column positions instead of directly hard-coding column names. Use either Table.ColumnNames or Table.SelectColumns. For example, if you always need the first column regardless of its name:
let
Source = YourDataSource,
ColumnNames = Table.ColumnNames(Source),
FirstColumnName = ColumnNames{0},
TransformedTable = Table.SelectColumns(Source, {FirstColumnName})
in
TransformedTable
This ensures that even if the column name changes, Power Query will still retrieve the first column.
2. Rename Columns Dynamically Using a Mapping Table
If column names change but follow a predictable pattern, you can create a mapping table to standardize names dynamically:
let
Source = YourDataSource,
OldNames = Table.ColumnNames(Source),
NewNames = {"StandardColumn1", "StandardColumn2", "StandardColumn3"},
RenamedColumns = Table.RenameColumns(Source, List.Zip({OldNames, NewNames}))
in
RenamedColumns
This approach ensures that regardless of the source column names, they are renamed consistently based on your predefined structure.
3. Handle Unknown or Extra Columns Dynamically
If new columns are added unpredictably, you can dynamically transform only the required columns using a filter:
let
Source = YourDataSource,
RequiredColumns = {"ColumnA", "ColumnB", "ColumnC"},
ExistingColumns = List.Intersect({Table.ColumnNames(Source), RequiredColumns}),
FilteredTable = Table.SelectColumns(Source, ExistingColumns)
in
FilteredTable
This ensures that Power Query only processes columns that exist while ignoring new or missing columns.