Drop constant columns from a CSV

About this tool

Constant Column Dropper finds the zero-variance columns in a CSV or delimited table — the ones that carry a single repeated value down every data row, or that contain nothing at all — and removes them.

Constancy is measured as one distinct value, not as a statistical variance of zero. That matters: the distinct-value rule works on text columns (country = US in every row) as well as numbers, and it handles blank cells without special-casing. Columns like this add no information to a model, a pivot, or a report — they just make the table wider.

Set Dominance below 100 to also catch near-constant columns: at 95, a column whose most common value covers 95% or more of the rows is flagged too. Everything runs locally in your browser — your data is never uploaded.

Worked example

Input:

id,country,score,notes
1,US,10,
2,US,20,
3,US,30,
4,US,40,

Default report:

Scanned 4 columns across 4 data rows (dominance 100%).
Found 2 constant columns; 2 columns remain.

Constant columns (dropped):
  "country" (col 2)  =  "US" in 4/4 rows (100%)
  "notes" (col 4)  =  all cells are empty

Use output=csv to get the table with those columns removed.

With Output = Cleaned CSV, the result is:

id,score
1,10
2,20
3,30
4,40

JSON metrics returns the same verdict per column plus the numbers behind it — distinct_values, top_value, top_count and top_share_percent — so you can script the decision instead of eyeballing it.

Options

• First row is a header — on by default. The header row is excluded from the value counts and preserved in cleaned CSV output.
• Delimiter — comma, tab, semicolon, or pipe. Output uses the same one.
• Dominance threshold — 100 (default) drops only strictly constant columns. Lower it to drop near-constant ones: 95 means "at least 95% of the rows say the same thing". The range is 50–100.
• Empty cells — Count as a value (default) means a column of values plus blanks is not constant; Skip when counting ignores blanks first, so a column that is gold, blank, gold counts as constant. A column that is entirely empty is dropped either way.
• Ignore case — on by default, so a column of YES / yes counts as constant.
• Ignore whitespace — on by default, so US and US are the same value.
• Never drop these columns — comma-separated column names or 1-based column numbers to protect. A protected column stays in the output and is listed separately in the report.
• Output — human report, cleaned CSV, or JSON metrics.

Limits and edge cases

• The last column standing is never removed silently: if every column would be dropped, Cleaned CSV returns an error naming the count instead of emitting an empty table. Switch to the report to see what happened, or protect a column.
• A column that is entirely empty is always dropped, whichever empty-cell mode is selected — there is no value in it to keep.
• Case and whitespace normalization affect the comparison only. Cells are written to the cleaned CSV exactly as you pasted them.
• Ragged rows are allowed: the table is as wide as its widest row, and missing cells are counted as empty.
• A header row alone, with no data rows, is an error — there is nothing to measure.
• This is a paste-sized page. Multi-hundred-megabyte files belong in a data pipeline, not a browser tab.

FAQ