---
title: Find percentile and quantile values
description: Use the quantile() function to return all values within the q quantile or percentile of input data.
url: https://docs.influxdata.com/influxdb/cloud/query-data/flux/percentile-quantile/
estimated_tokens: 1265
product: InfluxDB Cloud (TSM)
version: cloud
publisher: InfluxData
canonical: https://docs.influxdata.com/influxdb/cloud/query-data/flux/percentile-quantile/
date: '2025-04-02T15:54:32-06:00'
lastmod: '2025-04-02T15:54:32-06:00'
---

Use the [`quantile()` function](/flux/v0/stdlib/universe/quantile/)to return a value representing the `q` quantile or percentile of input data.

## Percentile versus quantile

Percentiles and quantiles are very similar, differing only in the number used to calculate return values.
A percentile is calculated using numbers between `0` and `100`.
A quantile is calculated using numbers between `0.0` and `1.0`.
For example, the **`0.5` quantile** is the same as the **50th percentile**.

## Select a method for calculating the quantile

Select one of the following methods to calculate the quantile:

* [estimate\_tdigest](#estimate_tdigest)
* [exact\_mean](#exact_mean)
* [exact\_selector](#exact_selector)

### estimate\_tdigest

**(Default)** An aggregate method that uses a [t-digest data structure](https://github.com/tdunning/t-digest)to compute a quantile estimate on large data sources.
Output tables consist of a single row containing the calculated quantile.

If calculating the `0.5` quantile or 50th percentile:

**Given the following input table:**

|       \_time       |\_value|
|--------------------|-------|
|2020-01-01T00:01:00Z|  1.0  |
|2020-01-01T00:02:00Z|  1.0  |
|2020-01-01T00:03:00Z|  2.0  |
|2020-01-01T00:04:00Z|  3.0  |

**`estimate_tdigest` returns:**

|\_value|
|-------|
|  1.5  |

### exact\_mean

An aggregate method that takes the average of the two points closest to the quantile value.
Output tables consist of a single row containing the calculated quantile.

If calculating the `0.5` quantile or 50th percentile:

**Given the following input table:**

|       \_time       |\_value|
|--------------------|-------|
|2020-01-01T00:01:00Z|  1.0  |
|2020-01-01T00:02:00Z|  1.0  |
|2020-01-01T00:03:00Z|  2.0  |
|2020-01-01T00:04:00Z|  3.0  |

**`exact_mean` returns:**

|\_value|
|-------|
|  1.5  |

### exact\_selector

A selector method that returns the data point for which at least `q` points are less than.
Output tables consist of a single row containing the calculated quantile.

If calculating the `0.5` quantile or 50th percentile:

**Given the following input table:**

|       \_time       |\_value|
|--------------------|-------|
|2020-01-01T00:01:00Z|  1.0  |
|2020-01-01T00:02:00Z|  1.0  |
|2020-01-01T00:03:00Z|  2.0  |
|2020-01-01T00:04:00Z|  3.0  |

**`exact_selector` returns:**

|       \_time       |\_value|
|--------------------|-------|
|2020-01-01T00:02:00Z|  1.0  |

> [!Note]
> The examples below use the [example data variable](/influxdb/cloud/query-data/flux/#example-data-variable).

## Find the value representing the 99th percentile

Use the default method, `"estimate_tdigest"`, to return all rows in a table that
contain values in the 99th percentile of data in the table.

```js
data
    |> quantile(q: 0.99)
```

## Find the average of values closest to the quantile

Use the `exact_mean` method to return a single row per input table containing the
average of the two values closest to the mathematical quantile of data in the table.
For example, to calculate the `0.99` quantile:

```js
data
    |> quantile(q: 0.99, method: "exact_mean")
```

## Find the point with the quantile value

Use the `exact_selector` method to return a single row per input table containing the
value that `q * 100`% of values in the table are less than.
For example, to calculate the `0.99` quantile:

```js
data
    |> quantile(q: 0.99, method: "exact_selector")
```

## Use quantile() with aggregateWindow()

[`aggregateWindow()`](/flux/v0/stdlib/universe/aggregatewindow/)segments data into windows of time, aggregates data in each window into a single
point, and then removes the time-based segmentation.
It is primarily used to [downsample data](/influxdb/cloud/process-data/common-tasks/downsample-data/).

To specify the [quantile calculation method](#select-a-method-for-calculating-the-quantile) in`aggregateWindow()`, use the [full function syntax](/flux/v0/stdlib/universe/aggregatewindow/#specify-parameters-of-the-aggregate-function):

```js
data
    |> aggregateWindow(
        every: 5m,
        fn: (tables=<-, column) => tables
            |> quantile(q: 0.99, method: "exact_selector"),
    )
```

#### Related

* [quantile() function](/flux/v0/stdlib/universe/quantile/)

[query](/influxdb/cloud/tags/query/)[percentile](/influxdb/cloud/tags/percentile/)[quantile](/influxdb/cloud/tags/quantile/)
| _time | _value |
| --- | --- |
| _time | _value |
| 2020-01-01T00:01:00Z | 1.0 |
| 2020-01-01T00:02:00Z | 1.0 |
| 2020-01-01T00:03:00Z | 2.0 |
| 2020-01-01T00:04:00Z | 3.0 |

| _value |
| --- |
| _value |
| 1.5 |

| _time | _value |
| --- | --- |
| _time | _value |
| 2020-01-01T00:01:00Z | 1.0 |
| 2020-01-01T00:02:00Z | 1.0 |
| 2020-01-01T00:03:00Z | 2.0 |
| 2020-01-01T00:04:00Z | 3.0 |

| _value |
| --- |
| _value |
| 1.5 |

| _time | _value |
| --- | --- |
| _time | _value |
| 2020-01-01T00:01:00Z | 1.0 |
| 2020-01-01T00:02:00Z | 1.0 |
| 2020-01-01T00:03:00Z | 2.0 |
| 2020-01-01T00:04:00Z | 3.0 |

| _time | _value |
| --- | --- |
| _time | _value |
| 2020-01-01T00:02:00Z | 1.0 |