What this answers

This tool answers "how much of my data is actually missing, and does it concentrate in specific columns or specific rows?" before any analysis, since missing data left unexamined can silently bias every downstream calculation.

How it is calculated

Every cell that is blank after trimming whitespace counts as missing. For each column, this calculator reports the count and percentage of missing cells. Separately, it counts how many rows are completely filled in with no missing cells at all, the subset of your data a complete-case analysis would actually use.

Worked example

For a small table with age, income, and region columns where one row is missing an age, another is missing an income, and a third is missing a region, each column shows exactly 1 missing value out of the total rows, and only the rows with no blanks at all count toward the complete-row total, immediately showing how much data a naive drop-any-missing-row approach would discard.

Assumption audit

Calculated from your data: the missing count and percentage for every column, and the number and percentage of fully complete rows.

Evidence to review: whether missingness concentrates in specific columns, specific rows, or looks scattered; a pattern concentrated in one column often has a different, more investigatable cause than scattered missingness.

You must verify: why the data is missing before choosing how to handle it; this summary cannot distinguish data missing completely at random from data missing for a reason connected to the value itself, a distinction that changes which handling approach is appropriate.

What this result does not mean

This summary describes the pattern of missingness, not its cause or its impact on any specific analysis; a small overall missing percentage can still matter greatly if it concentrates in a key variable, and a large percentage may matter little if it falls in a variable you were not planning to use.

Limitations

This calculator performs no imputation and makes no recommendation about which rows or columns to drop; that decision depends on context this pattern summary alone cannot supply. It also requires every row to have the same number of columns as the header row.