---
title: tdigest() | Tiger Data Docs
description: Aggregate data in a `tdigest` for further calculation of percentile estimates
---

Since [1.0.0](https://github.com/timescale/timescaledb-toolkit/releases/tag/1.0.0)

This is the first step for calculating approximate percentiles with the `tdigest` algorithm. Use `tdigest` to create an intermediate aggregate from your raw data. This intermediate form can then be used by one or more accessors in this group to compute final results.

Optionally, multiple such intermediate aggregate objects can be combined using [`rollup()`](/docs/reference/toolkit/percentile-approximation/tdigest/rollup/index.md) before an accessor is applied.

## Samples

Given a table called `samples`, with a column called `data`, build a `tdigest` using the `data` column. Use 100 buckets for the approximation.

```
SELECT tdigest(100, data) FROM samples;
```

## Arguments

The syntax is:

```
tdigest(
  buckets INTEGER,
  value DOUBLE PRECISION
) RETURNS TDigest
```

| Name    | Type             | Default | Required | Description                                                                                                          |
| ------- | ---------------- | ------- | -------- | -------------------------------------------------------------------------------------------------------------------- |
| buckets | INTEGER          | -       | ✔        | Number of buckets in the digest. Increasing this provides more accurate quantile estimates, but requires more memory |
| value   | DOUBLE PRECISION | -       | ✔        | Column of values to aggregate for the `tdigest` object                                                               |

## Returns

| Column  | Type    | Description                                                                                  |
| ------- | ------- | -------------------------------------------------------------------------------------------- |
| tdigest | TDigest | A percentile estimator object created to calculate percentiles using the `tdigest` algorithm |