Clean and normalize a table
Clean cells, remove empty rows and duplicates, then fill missing values.
What does this template do?
Clean cells, remove empty rows and duplicates, then fill missing values.
This template goes one step beyond plain cleaning: after removing spaces, empty rows and duplicates, it fills the empty cells of one column with a default value. The table becomes consistent, which avoids blank cells in a chart, a filter or an import.
Pipeline steps
This template automatically chains 6 steps in the Workspace. You can review every setting before running it.
- 1Import a spreadsheet
- 2Trim whitespace
- 3Remove empty rows
- 4Remove duplicate rows
- 5Fill empty values
- 6Export the table
Why the steps come in this order
Filling comes last. Before deduplication, it would make rows that differed only by an empty cell identical and merge them by mistake. Before removing empty rows, it would fill rows that should not exist at all.
When should you use this template?
- Write “Not specified” in a “Country” column before a pivot table.
- Replace missing amounts with 0 before computing a total.
- Harmonise a file assembled from several sources before importing it.
Local processing in your browser
When the selected modules support local processing, your files stay on your device while the Pipeline runs.
Settings to check
- Column to fill and replacement value: required, one column per run.
- The cleaning steps apply to the whole table, without settings.
- Export: XLSX by default, CSV or JSON as alternatives.
Example
- Before
- 480 rows, including 12 empty ones, 9 duplicates and 37 empty cells in the “Country” column.
- After
- 459 unique rows with “Country” filled everywhere, the 37 gaps reading “Not specified”.
Limits to know
- Only one column is filled; add a step in the Workspace to handle others.
- The same value is used everywhere: there is no average and no copy of the previous value.
- A default value hides missing information: keep it explicit (“Unknown” rather than a real-looking value).