Missing Data Checker
Count and chart missing values per variable and find incomplete rows in a dataset.
Blank cells always count as missing. Add codes such as -99 or 999 if your dataset uses them.
Missing data report
Continue your work
- CSV Descriptive Statistics — Summarize the complete values.
- Outlier Detector — Screen the same data for outliers.
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Clear instructions
Find steps, examples and limitations below.
Use online
Open the tool in a supported web browser.
Free to use
No sign-up required. Tool-specific limits may apply.
How to use the Missing Data Checker
Count and chart missing values per variable and find incomplete rows in a dataset.
- 1 Upload or paste your dataset.
- 2 Add any codes your data uses for missing values, such as -99 or 999.
- 3 Sort variables by missingness and download the report.
Example and practical tips
In a 16-row dataset, BMI is missing for 2 people (12.5%) and only 12 rows (75%) are complete cases.
Frequently asked questions
What counts as missing?
Blank cells always count. By default NA, N/A, NaN, null, None, “.”, “-”, “?” and #N/A count too, and you can edit the list.
How much missing data is too much?
There is no fixed cut-off, but more than 5–10% on a key variable deserves attention and possibly multiple imputation.
Report an issue
Something broken or not quite right? Tell us and we will look into it.