Mode of a dataset calculator
In 1, 2, 2, 3 and 4 the mode is 2, reached twice, and a frequency table shows how often each value appears. When several values tie at the top count, all of them are returned as modes. Free in your browser.
- Free
- Runs in your browser
- No sign-up
- Your data stays on your device
Run — free
Worked example
- Numbers
- 1, 2, 2, 3, 4
- Quantity
- 5
- Modes
- 2
- Calculation mode
- 2
- Mode count
- 1
The mode of a dataset is the value that appears most often. When one number clearly dominates the frequency table, that single value is the mode. When two or more numbers share the same highest frequency, the dataset is multimodal and every tied value is a mode. This capability takes a non-empty list of finite numbers and returns the mode or all tied modes, together with mode count, peak frequency, unimodal and multimodal flags, and a full frequency table.
What the mode of a dataset means and when it is unique or tied
In descriptive statistics the mode answers a simple question: which value shows up most often in this list? Unlike the mean, which uses every observation and can be dragged by extremes, and unlike the median, which only cares about order, the mode looks only at frequencies. Build a count for each distinct number; the highest count is the mode frequency; every value that reaches that count is a mode.
Classic unimodal classroom example: the list one, two, two, three, four has mode two with frequency two because two is the only value that appears twice. Multimodal example: one, one, two, two, three has modes one and two, each with frequency two; three appears once and is not a mode. When every value appears exactly once, every value is tied at frequency one, so this calculator reports the full set as tied modes rather than inventing a single winner.
A single-element list has that element as the unique mode with frequency one. Prefer mode when the data are discrete or categorical-like numbers, when you care about the most common sensor reading, quiz choice, or product size, or when the distribution is strongly peaked and the mean would hide that peak. Prefer mean or median for continuous centers of mass; this page is specifically the mode-of-dataset calculator for people who searched for the most frequent value alone.
What you can do with it
Most common operational reading
Highlight the most frequent sensor code, quiz choice, or pack size in a batch without installing a full stats library in every service.
Teaching unimodal versus multimodal sets
Show live how two values can share peak frequency, returning both modes and a clear frequency table for the class.
FAQ
What happens if the list is empty?
There is no mode of an empty sample; failed validation is not charged.
Are non-numeric entries allowed?
Only finite numbers (or numeric strings that parse cleanly) are accepted.
Is the mode of dataset calculator free?
The browser tool is free and runs locally.
What if every value appears only once?
Then every value ties at frequency one, so the calculator returns the whole set as tied modes instead of picking the first number. A list with a single value has that value as its one mode.
What does the frequency table show?
It lists each distinct value with the number of times it appears, sorted by value. You can see at a glance how close the other values come to the mode.
Related tools
For developers — API access
Everything on this page is available programmatically. This section is for teams who want to wire it into their own systems; everyone else can just use the tool above.
API endpoint
Prefer to automate it? One authenticated POST creates the task; the result comes back by webhook or a signed link. The same capability also runs here on the web, by email and from Telegram — and soon from our app too.
Call it from your stack
curl -X POST https://api.kit.forhosting.com/stat/mode-value \
-H "Authorization: Bearer $KIT_KEY" \
-H "Content-Type: application/json" \
-d '{"numbers":[1,2,2,3,4]}'const res = await fetch("https://api.kit.forhosting.com/stat/mode-value", {
method: "POST",
headers: {
"Authorization": `Bearer ${process.env.KIT_KEY}`,
"Content-Type": "application/json"
},
body: JSON.stringify({
"numbers": [
1,
2,
2,
3,
4
]
})
});
const { task_id } = await res.json();import os, requests
res = requests.post(
"https://api.kit.forhosting.com/stat/mode-value",
headers={"Authorization": f"Bearer {os.environ['KIT_KEY']}"},
json={
"numbers": [
1,
2,
2,
3,
4
]
},
)
task_id = res.json()["task_id"]<?php
$res = file_get_contents("https://api.kit.forhosting.com/stat/mode-value", false, stream_context_create([
"http" => [
"method" => "POST",
"header" => "Authorization: Bearer " . getenv("KIT_KEY") . "\r\nContent-Type: application/json",
"content" => '{"numbers":[1,2,2,3,4]}',
],
]));
$task = json_decode($res, true);body := bytes.NewBufferString(`{"numbers":[1,2,2,3,4]}`)
req, _ := http.NewRequest("POST", "https://api.kit.forhosting.com/stat/mode-value", body)
req.Header.Set("Authorization", "Bearer "+os.Getenv("KIT_KEY"))
req.Header.Set("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)Example request
{
"numbers": [
1,
2,
2,
3,
4
]
}Example response
{
"task_id": "tsk_a1b2c3d4e5f6a1b2c3d4e5f6",
"type": "stat.mode_value",
"status": "queued",
"_links": {
"result": "/tasks/tsk_…/result"
}
}The API is asynchronous: the call returns a task_id immediately and the result arrives by webhook. Polling is capped at 1 req/s per task.
Pricing
Published price — no tokens, no invented credits. A failed task is never charged.
Errors
| HTTP | Code | Meaning |
|---|---|---|
401 | unauthorized | Missing or invalid API key. |
402 | insufficient_balance | Your balance doesn't cover the task price. |
404 | unknown_type | That task type doesn't exist. |
429 | rate_limited | Too many requests. Use the webhook instead of polling. |
Technical notes
Empty lists and non-numeric entries are rejected with invalid_input and are never charged.
What the mode of a dataset means and when it is unique or tied
Always reject an empty list: there is no most frequent value in a sample of size zero, and fabricating a zero mode from no data misleads students and pipelines.
How to call the API and what the response contains
Numeric strings inside the array are coerced when they parse as ordinary decimal or scientific literals; a comma, semicolon or whitespace separated string is also accepted for simple text forms. Use it from homework checkers, spreadsheet enrichment, quality-control dashboards that highlight the most common defect code, inventory tools that need the most common pack size, or any workflow that wants only the mode without installing a full statistics package or computing mean and median you do not need. Send a JSON body with one required field named numbers: a non-empty array of finite numbers. Aliases values, data and list are accepted and behave the same. On success the response includes count as the sample size n, modes as the ascending sorted array of every value at peak frequency, mode as a single number when the list is unimodal or the same array when multimodal, mode_count as how many values share the peak, mode_frequency as that peak frequency, is_unimodal and is_multimodal as booleans, and frequency_table as an array of objects each with value and frequency sorted by value so you can inspect the full breakdown. Failed validation—missing numbers, an empty list, non-numeric or non-finite entries, or a list longer than one hundred thousand values—returns invalid_input and is never charged. Pricing is a flat $0.002 per successful request with unit item.
Practical tips, limits, and how this differs from mean-median-mode pages
When teaching, pair a unimodal example such as one two two three four with a bimodal example such as one one two two three so students see both a scalar mode and a modes array of ties. For all-unique lists, show that every value is returned as a tied mode at frequency one rather than silently picking the first element. Sibling pages that compute mean, median and mode together target a different search intent; this calculator is for people who specifically want the mode of a dataset, the most frequent value, or all multimodal ties without extra summary statistics. Keep lists within the published size cap so interactive Worker and browser paths stay fast; one hundred thousand finite numbers is ample for classroom sets and most operational samples. IEEE floating-point equality is used as-is: two values that differ only past binary precision count as distinct, so round measurements to a shared decimal place before calling if your instrument noise would otherwise split one true bin into many near-misses. Failed tasks that return invalid_input do not consume prepaid balance, which keeps exploratory scripts cheap while students type empty arrays or paste labels by mistake. Prefer sending the raw list once and reading modes plus the frequency table from one response instead of building ad-hoc counters in every language: one contract, one charge unit, identical results in browser and API at $0.002 per success.
Integration use cases
Homework and exam answer keys
Give students a short numeric sample; check their hand-computed mode and multimodal ties against a deterministic browser or API result.
Technical questions
What does this mode of dataset calculator return?
For a non-empty numeric list it returns count, modes (sorted), mode (scalar if unimodal else the modes array), mode_count, mode_frequency, is_unimodal, is_multimodal, and frequency_table.
What if several values appear equally often?
All values tied at the highest frequency are returned in modes (sorted ascending). mode is that full array when multimodal; mode_count is greater than one.