IQR Outlier Trimmer
Remove the rows whose chosen column falls outside the Tukey fences Q1 − k·IQR … Q3 + k·IQR — or clip them, flag them, or just read the quartile stats. Runs entirely in your browser, nothing is uploaded.
About this tool
The interquartile range (IQR) method — Tukey's fences — is the textbook way to decide which rows of a dataset are outliers without assuming the data is normally distributed. For the column you pick it computes the first quartile Q1, the third quartile Q3 and IQR = Q3 − Q1, then treats any value below
Q1 − k · IQR (lower fence)
or above
Q3 + k · IQR (upper fence)
as an outlier. k = 1.5 is Tukey's classic mild fence (the whisker length of a box
plot); k = 3 keeps only the extreme outliers. Whole rows are then removed, so the
result is still a valid table you can paste straight back into a spreadsheet.
A worked example
Input (with price as the analysed column, k = 1.5):
name,price
a,10
b,11
c,12
d,13
e,100
The five prices sort to 10 11 12 13 100, giving Q1 = 11, Q3 = 13, IQR = 2 and
fences 11 − 1.5·2 = 8 … 13 + 1.5·2 = 16. Only 100 is outside, so its row goes:
name,price
a,10
b,11
c,12
d,13
Switch Output to the report and you get the same numbers written out — quartiles, both fences, and how many rows were flagged — instead of the table.
The four actions
- Remove — drop the outlier rows (the default; this is the "trim").
- Keep only them — the inverse selection, so you can eyeball what would be dropped before committing to it.
- Clip (winsorize) — leave every row in place but clamp each out-of-fence cell to
its own fence, so
100becomes16in the example above. Useful when losing rows would break a paired dataset. - Flag — append an
outliercolumn oftrue/falseand drop nothing.
Choosing columns
Leave Columns blank and every column whose values are all numeric is fenced; name one (or several, comma-separated) to be explicit. Columns are matched by header name, or by 1-based index when the header option is off. With more than one column selected, any means a row goes as soon as one of its cells is out of fence, all means every selected cell must be.
Limits
- Up to 5,000 data rows per run — split larger files into batches.
- Quartiles need at least one numeric value in the column; with a single value the IQR is 0, so the fences collapse onto that value and nothing is trimmed.
- Blank and non-numeric cells never take part in the quartile maths. Whether their rows survive is the Blank / non-numeric cells setting.
- Only the IQR method is offered here. For z-score or modified-z-score (MAD) detection over a list of numbers, use the outlier-detector tool; to see the box plot the fences come from, use the box-plot chart tool.
FAQ
Is my data uploaded anywhere?
No. The whole calculation is compiled to WebAssembly and runs inside your browser tab — the CSV never leaves your device, and the page works offline once loaded.
Which quartile definition does it use?
By default linear interpolation between order statistics — what
numpy.percentile, pandas.quantile and Excel's QUARTILE.INC do. Two other
conventions are selectable, because textbooks disagree: exclusive (Moore &
McCabe / TI-83) splits the sorted values at the median and leaves the median out of
both halves when the count is odd, and inclusive (Tukey's hinges) puts the
median in both halves. On an odd-length dataset they can give different quartiles —
1…9 gives Q1 = 3, Q3 = 7 under linear and Q1 = 2.5, Q3 = 7.5 under exclusive —
so pick the one your reference tool uses.
Why does my row survive even though the value looks extreme?
The fences are derived from the data itself, so a "big" number is only an outlier
relative to that column's spread. If a quarter of the values are large, the IQR is
large too and the fences move out with it. Lower k toward 0 to tighten them, or
switch to the report output to see exactly where the fences landed.
Can I trim on more than one column at once?
Yes — list them comma-separated. Each column gets its own quartiles and its own fences (they are never pooled), and the any / all setting decides whether one out-of-fence cell is enough to drop the row or whether every selected cell has to be out of fence.
What happens to the header row and to other delimiters?
With first row is a header on, that row is copied through untouched and is never fence-tested; its names are what the Columns box matches. Tab-, semicolon- and pipe-separated files are supported, and the output is written back with the same delimiter, quoting only the fields that need it.
Developer & Automation Access
Run it from the terminal
Same engine as this page, headless — via the gizza CLI:
gizza tool iqr-outlier-trimmer "name,price
a,10
b,11
c,12
d,13
e,100"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/iqr-outlier-trimmer/?data=name%2Cprice%0Aa%2C10%0Ab%2C11%0Ac%2C12%0Ad%2C13%0Ae%2C100&columns=price&k=1.5&action=remove&output=csv&header=true&delimiter=comma&quartile_method=linear&match_mode=any&non_numeric=keepMachine-readable descriptor: tool.json — title + parameters JSON Schema for agents.