How to handle missing data in a CSV

A blank cell means the field was not provided. It is not the same as zero, "N/A", or a space. Filling it automatically invents a fact. Cleaning a CSV should show where the gaps are and leave the filling decision to you.

Three different blanks

• A blank cell inside a useful row. The row stays. The quality summary counts the gap on that column.
• An empty row. Every cell is blank or only spaces. That row is a candidate for removal, after a preview.
• An empty column. The header may say Unused, or it may be blank, and no data row has a value. Removal is also previewed.

How to review gaps

Use the row filter "Blank cells" in the CSV viewer to scroll only the rows that contain a gap. The per-column notes tell you whether a column is mostly empty or only missing a few values. A column that is empty because the export failed is a different problem from a column that is optional.

CleanCSV does not impute, forward-fill, or replace blanks with zero. If you need a sentinel such as NA, use find and replace on purpose and read the preview count first.

Spaces are not missing until you say so

A cell that is three spaces is not an empty string. Empty-row removal treats it as blank because trimming leaves nothing. Other operations do not. Trim first if you want those cells to become truly empty, then look at the blank-cell count again.