CSV Sample
Grab a random, systematic, top/bottom-N, or stratified subset of your CSV rows. Runs entirely in your browser, no upload, no sign-up.
CSV sample
Pull a smaller, representative subset of rows out of a big CSV — for a quick look, a test fixture, a survey draw, or a spot check. Pick a method, a size, and (for random draws) a seed. Everything runs in your browser; nothing is uploaded.
Methods
- random — a uniform random draw of rows. Reproducible: the same seed always produces the same sample; change the seed for a different draw.
- systematic — every k-th row after a seeded random start, where k ≈ rows ÷ size. Spreads the sample evenly across the file.
- top — the first N data rows (like
head). - bottom — the last N data rows (like
tail). - stratified — split the rows into groups by the stratify column, then sample each group in proportion to its size so every group stays represented.
Size
Set sample size to a row count (e.g. 10), or set percent to a share of the
rows (e.g. 25 for 25%). Percent wins whenever it's above 0. Either way the result is
capped at the number of rows available, so asking for more rows than exist returns them
all.
Worked example
Input CSV (4 data rows):
name,group
Alice,east
Bob,west
Carol,east
Dan,west
Stratified, size 2, stratify column group, seed 1 → one row from east and
one from west (proportional to the two equal groups), e.g.:
name,group
Alice,east
Bob,west
Top, size 3 → the header plus the first three rows (Alice, Bob, Carol).
Limits & edge cases
- The header row (when first row is a header is on) is always kept and never counted toward the sample size.
- Selected rows are returned in their original file order (top/bottom preserve order too), so a random sample of a sorted file is still sorted.
- Sampling is without replacement — no row appears twice; one sample per run.
- Delimiter is one of comma, tab, semicolon, or pipe; the output uses the same one.
- Rows with a differing number of fields are tolerated.
FAQ
Is my data uploaded anywhere?
No. The sampling runs locally in your browser with WebAssembly — the CSV never leaves your machine.
Why does the same input always give the same "random" sample?
Random and stratified draws use a seeded pseudo-random generator, so results are reproducible — handy for sharing or re-running an analysis. To get a different draw, change the seed value (any whole number).
How does stratified sampling decide how many rows per group?
It allocates each group a share proportional to its size (largest-remainder rounding), so the sample keeps the same group balance as the full file. For example, from 90 rows in group A and 10 in group B, a size-10 stratified sample takes about 9 from A and 1 from B.
Can I sample without a header row?
Yes — turn first row is a header off. Then refer to the stratify column by its
1-based index (e.g. 2 for the second column) instead of a name, and every row is
treated as data.
What if I ask for more rows than the file has?
You get all of them. The size (or percent) is capped at the number of available data rows, so nothing is duplicated or invented.
Developer & Automation Access
Run it from the terminal
Same engine as this page, headless — via the gizza CLI:
gizza tool csv-sample "name,group
Alice,east
Bob,west
Carol,east
Dan,west"New to the CLI? Get gizza →
Open it by URL
Pre-fill and auto-run this tool with query parameters — the names match the API/CLI:
https://gizza.ai/tools/csv-sample/?data=name%2Cgroup%0AAlice%2Ceast%0ABob%2Cwest%0ACarol%2Ceast%0ADan%2Cwest&method=random&n=10&percent=0&stratify_column=group&seed=42&header=true&delimiter=commaMachine-readable descriptor: tool.json — title + parameters JSON Schema for agents.