---
title: InfluxQL miscellaneous functions
description: Use InfluxQL miscellaneous functions to perform different operations in InfluxQL queries.
url: https://docs.influxdata.com/influxdb3/core/reference/influxql/functions/misc/
estimated_tokens: 988
product: InfluxDB 3 Core
version: core
publisher: InfluxData
canonical: https://docs.influxdata.com/influxdb3/core/reference/influxql/functions/misc/
date: '2025-01-13T07:21:11-07:00'
lastmod: '2025-01-13T07:21:11-07:00'
---

Use InfluxQL miscellaneous functions to perform different operations in
InfluxQL queries.

* [fill()](#fill)

## fill()

Fills *null* field values returned from empty time windows in `GROUP BY time()`queries with a specified fill value.

*Supported only in the [`GROUP BY` clause](/influxdb3/core/reference/influxql/group-by/).*

```sql
fill(behavior)
```

#### Arguments

* **behavior**: Defines the behavior of the fill operation.
  If no `FILL` clause is included, the default behavior is `fill(null)`.

  The following options are available:

  * **numeric literal**: Replaces null values with the specified numeric literal.
  * **linear**: Uses linear interpolation between existing values to replace null values.
  * **none**: Removes rows with null field values.
  * **null**: Keeps null values and associated timestamps.
  * **previous**: Replaces null values with the most recent non-null value.

#### Examples

The following example uses the[Bitcoin price sample dataset](/influxdb3/core/reference/sample-data/#bitcoin-price-data).

#### fill(numeric\_literal) ####

```sql
SELECT
  MEAN(price)
FROM bitcoin
WHERE
  code = 'USD'
  AND time >= '2023-05-01T00:00:00Z'
  AND time < '2023-05-01T02:00:00Z'
GROUP BY
  time(30m)
  fill(0)
```

name: bitcoin

|        time        |   mean   |
|--------------------|----------|
|2023-05-01T00:00:00Z|29319.9092|
|2023-05-01T00:30:00Z|29307.4416|
|2023-05-01T01:00:00Z|    0     |
|2023-05-01T01:30:00Z|29263.2886|

```sql
SELECT
  MEAN(price)
FROM bitcoin
WHERE
  code = 'USD'
  AND time >= '2023-05-01T00:00:00Z'
  AND time < '2023-05-01T02:00:00Z'
GROUP BY
  time(30m)
  fill(linear)
```

name: bitcoin

|        time        |   mean   |
|--------------------|----------|
|2023-05-01T00:00:00Z|29319.9092|
|2023-05-01T00:30:00Z|29307.4416|
|2023-05-01T01:00:00Z|29285.3651|
|2023-05-01T01:30:00Z|29263.2886|

```sql
SELECT
  MEAN(price)
FROM bitcoin
WHERE
  code = 'USD'
  AND time >= '2023-05-01T00:00:00Z'
  AND time < '2023-05-01T02:00:00Z'
GROUP BY
  time(30m)
  fill(none)
```

name: bitcoin

|        time        |   mean   |
|--------------------|----------|
|2023-05-01T00:00:00Z|29319.9092|
|2023-05-01T00:30:00Z|29307.4416|
|2023-05-01T01:30:00Z|29263.2886|

```sql
SELECT
  MEAN(price)
FROM bitcoin
WHERE
  code = 'USD'
  AND time >= '2023-05-01T00:00:00Z'
  AND time < '2023-05-01T02:00:00Z'
GROUP BY
  time(30m)
  fill(null)
```

name: bitcoin

|        time        |   mean   |
|--------------------|----------|
|2023-05-01T00:00:00Z|29319.9092|
|2023-05-01T00:30:00Z|29307.4416|
|2023-05-01T01:00:00Z|          |
|2023-05-01T01:30:00Z|29263.2886|

```sql
SELECT
  MEAN(price)
FROM bitcoin
WHERE
  code = 'USD'
  AND time >= '2023-05-01T00:00:00Z'
  AND time < '2023-05-01T02:00:00Z'
GROUP BY
  time(30m)
  fill(previous)
```

name: bitcoin

|        time        |   mean   |
|--------------------|----------|
|2023-05-01T00:00:00Z|29319.9092|
|2023-05-01T00:30:00Z|29307.4416|
|2023-05-01T01:00:00Z|29307.4416|
|2023-05-01T01:30:00Z|29263.2886|
| time | mean |
| --- | --- |
| time | mean |
| 2023-05-01T00:00:00Z | 29319.9092 |
| 2023-05-01T00:30:00Z | 29307.4416 |
| 2023-05-01T01:00:00Z | 0 |
| 2023-05-01T01:30:00Z | 29263.2886 |

| time | mean |
| --- | --- |
| time | mean |
| 2023-05-01T00:00:00Z | 29319.9092 |
| 2023-05-01T00:30:00Z | 29307.4416 |
| 2023-05-01T01:00:00Z | 29285.3651 |
| 2023-05-01T01:30:00Z | 29263.2886 |

| time | mean |
| --- | --- |
| time | mean |
| 2023-05-01T00:00:00Z | 29319.9092 |
| 2023-05-01T00:30:00Z | 29307.4416 |
| 2023-05-01T01:30:00Z | 29263.2886 |

| time | mean |
| --- | --- |
| time | mean |
| 2023-05-01T00:00:00Z | 29319.9092 |
| 2023-05-01T00:30:00Z | 29307.4416 |
| 2023-05-01T01:00:00Z |  |
| 2023-05-01T01:30:00Z | 29263.2886 |

| time | mean |
| --- | --- |
| time | mean |
| 2023-05-01T00:00:00Z | 29319.9092 |
| 2023-05-01T00:30:00Z | 29307.4416 |
| 2023-05-01T01:00:00Z | 29307.4416 |
| 2023-05-01T01:30:00Z | 29263.2886 |