---
title: InfluxQL aggregate functions
description: Use InfluxQL aggregate functions to aggregate your time series data.
url: https://docs.influxdata.com/influxdb3/core/reference/influxql/functions/aggregates/
estimated_tokens: 5796
product: InfluxDB 3 Core
version: core
publisher: InfluxData
canonical: https://docs.influxdata.com/influxdb3/core/reference/influxql/functions/aggregates/
date: '2025-01-13T07:21:11-07:00'
lastmod: '2025-01-13T07:21:11-07:00'
---

Use aggregate functions to assess, aggregate, and return values in your data.
Aggregate functions return one row containing the aggregate values from each InfluxQL group.

*Examples use the sample data set provided in the[Get started with InfluxDB tutorial](/influxdb3/core/get-started/write/#construct-line-protocol).*

* [COUNT()](#count)
* [DISTINCT()](#distinct)
* [INTEGRAL()](#integral)
* [MEAN()](#mean)
* [MEDIAN()](#median)
* [MODE()](#mode)
* [SPREAD()](#spread)
* [STDDEV()](#stddev)
* [SUM()](#sum)

## COUNT()

Returns the number of non-null [field values](/influxdb3/core/reference/glossary/#field-value).

```sql
COUNT(field_expression)
```

#### Arguments

* **field\_expression**: Expression to identify one or more fields to operate on.
  Can be a [field key](/influxdb3/core/reference/glossary/#field-key),
  constant, regular expression, or wildcard (`*`).
  Supports all field types.

#### Examples

[](#count-the-number-of-non-null-values-in-a-field)

Count the number of non-null values in a field

```sql
SELECT COUNT(temp) FROM home
```

name: home

|        time        |count|
|--------------------|-----|
|1970-01-01T00:00:00Z| 26  |

[](#count-the-number-of-non-null-values-in-each-field)

Count the number of non-null values in each field

```sql
SELECT COUNT(*) FROM home
```

name: home

|        time        |count\_co|count\_hum|count\_temp|
|--------------------|---------|----------|-----------|
|1970-01-01T00:00:00Z|   26    |    26    |    26     |

[](#count-the-number-of-non-null-values-in-fields-where-the-field-key-matches-a-regular-expression)

Count the number of non-null values in fields where the field key matches a regular expression

```sql
SELECT COUNT(/^[th]/) FROM home
```

name: home

|        time        |count\_hum|count\_temp|
|--------------------|----------|-----------|
|1970-01-01T00:00:00Z|    26    |    26     |

[](#count-distinct-values-for-a-field)

Count distinct values for a field

InfluxQL supports nesting [`DISTINCT()`](#distinct) in `COUNT()`.

```sql
SELECT COUNT(DISTINCT(co)) FROM home
```

name: home

|        time        |count|
|--------------------|-----|
|1970-01-01T00:00:00Z| 12  |

[](#count-the-number-of-non-null-field-values-within-time-windows-grouped-by-time)

Count the number of non-null field values within time windows (grouped by time)

```sql
SELECT
  COUNT(temp)
FROM home
WHERE
  room = 'Kitchen'
  AND time >= '2022-01-01T08:00:00Z'
  AND time <= '2022-01-01T20:00:00Z'
GROUP BY time(6h)
```

name: home

|        time        |count|
|--------------------|-----|
|2022-01-01T06:00:00Z|  4  |
|2022-01-01T12:00:00Z|  6  |
|2022-01-01T18:00:00Z|  3  |

## DISTINCT()

Returns the list of unique [field values](/influxdb3/core/reference/glossary/#field-value).

```sql
DISTINCT(field_key)
```

#### Arguments

* **field\_key**: Field key to return distinct values from.
  Supports all field types.

#### Notable behaviors

* InfluxQL supports nesting `DISTINCT()` with [`COUNT()`](#count-distinct-values-for-a-field).

#### Examples

[](#list-the-distinct-field-values)

List the distinct field values

```sql
SELECT DISTINCT(co) FROM home
```

name: home

|        time        |distinct|
|--------------------|--------|
|1970-01-01T00:00:00Z|   0    |
|1970-01-01T00:00:00Z|   1    |
|1970-01-01T00:00:00Z|   3    |
|1970-01-01T00:00:00Z|   4    |
|1970-01-01T00:00:00Z|   7    |
|1970-01-01T00:00:00Z|   5    |
|1970-01-01T00:00:00Z|   9    |
|1970-01-01T00:00:00Z|   18   |
|1970-01-01T00:00:00Z|   14   |
|1970-01-01T00:00:00Z|   22   |
|1970-01-01T00:00:00Z|   17   |
|1970-01-01T00:00:00Z|   26   |

## INTEGRAL()

Returns the area under the curve for queried [field values](/influxdb3/core/reference/glossary/#field-value)and converts those results into the summed area per **unit** of time.

> [!Important]
> * `INTEGRAL()` does not support [`fill()`](/influxdb3/core/reference/influxql/group-by/#group-by-time-and-fill-gaps).
> * `INTEGRAL()` supports int64 and float64 field value [data types](/influxdb3/core/reference/glossary/#data-type).

```sql
INTEGRAL(field_expression[, unit])
```

#### Arguments

* **field\_expression**: Expression to identify one or more fields to operate on.
  Can be a [field key](/influxdb3/core/reference/glossary/#field-key),
  constant, regular expression, or wildcard (`*`).
* **unit**: Unit of time to use when calculating the integral.
  Default is `1s` (one second).

#### Examples

[](#calculate-the-integral-for-a-field)

Calculate the integral for a field

```sql
SELECT
  INTEGRAL(co)
FROM home
WHERE room = 'Kitchen'
```

name: home

|        time        |integral|
|--------------------|--------|
|1970-01-01T00:00:00Z| 266400 |

[](#calculate-the-integral-for-a-field-and-specify-the-unit-option)

Calculate the integral for a field and specify the unit option

```sql
SELECT
  INTEGRAL(co, 1h)
FROM home
WHERE room = 'Kitchen'
```

name: home

|        time        |integral|
|--------------------|--------|
|1970-01-01T00:00:00Z|   74   |

[](#calculate-the-integral-for-_each_-field-and-specify-the-unit-option)

Calculate the integral for *each* field and specify the unit option

Return the area under the curve (in minutes) for the field values associated
with each field key that stores numeric values in the `h2o_feet` measurement.
The `h2o_feet` measurement has on numeric field: `water_level`.

```sql
SELECT
  INTEGRAL(*, 1h)
FROM home
WHERE room = 'Kitchen'
```

name: home

|        time        |integral\_co|integral\_hum|integral\_temp|
|--------------------|------------|-------------|--------------|
|1970-01-01T00:00:00Z|     74     |     435     |    272.25    |

[](#calculate-the-integral-for-the-field-keys-that-matches-a-regular-expression)

Calculate the integral for the field keys that matches a regular expression

```sql
SELECT
  INTEGRAL(/^[th]/, 1h)
FROM home
WHERE room = 'Kitchen'
```

name: home

|        time        |integral\_hum|integral\_temp|
|--------------------|-------------|--------------|
|1970-01-01T00:00:00Z|     435     |    272.25    |

[](#calculate-the-integral-for-a-field-grouping-by-time)

Calculate the integral for a field grouping by time

```sql
SELECT
  INTEGRAL(co, 1h)
FROM home
WHERE
  room = 'Kitchen'
  AND time >= '2022-01-01T08:00:00Z'
  AND time <= '2022-01-01T20:00:00Z'
GROUP BY time(6h)
```

name: home

|        time        |integral|
|--------------------|--------|
|2022-01-01T06:00:00Z|   0    |
|2022-01-01T12:00:00Z|   30   |
|2022-01-01T18:00:00Z|   44   |

## MEAN()

Returns the arithmetic mean (average) of [field values](/influxdb3/core/reference/glossary/#field-value).

```sql
MEAN(field_expression)
```

#### Arguments

* **field\_expression**: Expression to identify one or more fields to operate on.
  Can be a [field key](/influxdb3/core/reference/glossary/#field-key),
  constant, regular expression, or wildcard (`*`).
  Supports **numeric fields**.

#### Examples

[](#calculate-the-mean-value-of-a-field)

Calculate the mean value of a field

```sql
SELECT MEAN(temp) FROM home
```

name: home

|        time        |       mean       |
|--------------------|------------------|
|1970-01-01T00:00:00Z|22.396153846153844|

[](#calculate-the-mean-value-of-each-field)

Calculate the mean value of each field

```sql
SELECT MEAN(*) FROM home
```

name: home

|        time        |    mean\_co     |mean\_hum|    mean\_temp    |
|--------------------|-----------------|---------|------------------|
|1970-01-01T00:00:00Z|5.269230769230769|  36.15  |22.396153846153844|

[](#calculate-the-mean-value-of-fields-where-the-field-key-matches-a-regular-expression)

Calculate the mean value of fields where the field key matches a regular expression

```sql
SELECT MEAN(/^[th]/) FROM home
```

name: home

|        time        |mean\_hum|    mean\_temp    |
|--------------------|---------|------------------|
|1970-01-01T00:00:00Z|  36.15  |22.396153846153844|

[](#calculate-the-mean-value-of-a-field-within-time-windows-grouped-by-time)

Calculate the mean value of a field within time windows (grouped by time)

```sql
SELECT
  MEAN(temp)
FROM home
WHERE
  room = 'Kitchen'
  AND time >= '2022-01-01T08:00:00Z'
  AND time <= '2022-01-01T20:00:00Z'
GROUP BY time(6h)
```

name: home

|        time        |       mean       |
|--------------------|------------------|
|2022-01-01T06:00:00Z|      22.275      |
|2022-01-01T12:00:00Z|22.649999999999995|
|2022-01-01T18:00:00Z|23.033333333333335|

## MEDIAN()

Returns the middle value from a sorted list of [field values](/influxdb3/core/reference/glossary/#field-value).

```sql
MEDIAN(field_expression)
```

#### Arguments

* **field\_expression**: Expression to identify one or more fields to operate on.
  Can be a [field key](/influxdb3/core/reference/glossary/#field-key),
  constant, regular expression, or wildcard (`*`).
  Supports **numeric fields**.

#### Notable behaviors

* `MEDIAN()` is nearly equivalent to[`PERCENTILE(field_key, 50)`](/influxdb3/core/reference/influxql/functions/selectors/#percentile),
  except `MEDIAN()` returns the average of the two middle field values if the
  field contains an even number of values.

#### Examples

[](#calculate-the-median-value-of-a-field)

Calculate the median value of a field

```sql
SELECT MEDIAN(temp) FROM home
```

name: home

|        time        |median|
|--------------------|------|
|1970-01-01T00:00:00Z|22.45 |

[](#calculate-the-median-value-of-each-field)

Calculate the median value of each field

```sql
SELECT MEDIAN(*) FROM home
```

name: home

|        time        |median\_co|median\_hum|median\_temp|
|--------------------|----------|-----------|------------|
|1970-01-01T00:00:00Z|    1     |   36.05   |   22.45    |

[](#calculate-the-median-value-of-fields-where-the-field-key-matches-a-regular-expression)

Calculate the median value of fields where the field key matches a regular expression

```sql
SELECT MEDIAN(/^[th]/) FROM home
```

name: home

|        time        |median\_hum|median\_temp|
|--------------------|-----------|------------|
|1970-01-01T00:00:00Z|   36.05   |   22.45    |

[](#calculate-the-median-value-of-a-field-within-time-windows-grouped-by-time)

Calculate the median value of a field within time windows (grouped by time)

```sql
SELECT
  MEDIAN(temp)
FROM home
WHERE
  room = 'Kitchen'
  AND time >= '2022-01-01T08:00:00Z'
  AND time <= '2022-01-01T20:00:00Z'
GROUP BY time(6h)
```

name: home

|        time        |      median      |
|--------------------|------------------|
|2022-01-01T06:00:00Z|22.549999999999997|
|2022-01-01T12:00:00Z|       22.7       |
|2022-01-01T18:00:00Z|       23.1       |

## MODE()

Returns the most frequent value in a list of[field values](/influxdb3/core/reference/glossary/#field-value).

```sql
MODE(field_expression)
```

#### Arguments

* **field\_expression**: Expression to identify one or more fields to operate on.
  Can be a [field key](/influxdb3/core/reference/glossary/#field-key),
  constant, regular expression, or wildcard (`*`).
  Supports all field types.

#### Notable behaviors

* `MODE()` returns the field value with the earliest[timestamp](/influxdb3/core/reference/glossary/#timestamp)if there’s a tie between two or more values for the maximum number of occurrences.

#### Examples

[](#calculate-the-mode-value-of-a-field)

Calculate the mode value of a field

```sql
SELECT MODE(co) FROM home
```

name: home

|        time        |mode|
|--------------------|----|
|1970-01-01T00:00:00Z| 0  |

[](#calculate-the-mode-value-of-each-field)

Calculate the mode value of each field

```sql
SELECT MODE(*) FROM home
```

name: home

|        time        |mode\_co|mode\_hum|mode\_temp|
|--------------------|--------|---------|----------|
|1970-01-01T00:00:00Z|   0    |   36    |   22.7   |

[](#calculate-the-mode-of-field-keys-that-match-a-regular-expression)

Calculate the mode of field keys that match a regular expression

```sql
SELECT MODE(/^[th]/) FROM home
```

name: home

|        time        |mode\_hum|mode\_temp|
|--------------------|---------|----------|
|1970-01-01T00:00:00Z|   36    |   22.7   |

[](#calculate-the-mode-a-field-within-time-windows-grouped-by-time)

Calculate the mode a field within time windows (grouped by time)

```sql
SELECT
  MODE(co)
FROM home
WHERE
  room = 'Kitchen'
  AND time >= '2022-01-01T08:00:00Z'
  AND time <= '2022-01-01T20:00:00Z'
GROUP BY time(6h)
```

name: home

|        time        |mode|
|--------------------|----|
|2022-01-01T06:00:00Z| 0  |
|2022-01-01T12:00:00Z| 1  |
|2022-01-01T18:00:00Z| 18 |

## SPREAD()

Returns the difference between the minimum and maximum[field values](/influxdb3/core/reference/glossary/#field-value).

```sql
SPREAD(field_expression)
```

#### Arguments

* **field\_expression**: Expression to identify one or more fields to operate on.
  Can be a [field key](/influxdb3/core/reference/glossary/#field-key),
  constant, regular expression, or wildcard (`*`).
  Supports **numeric fields**.

#### Examples

[](#calculate-the-spread-of-a-field)

Calculate the spread of a field

```sql
SELECT SPREAD(temp) FROM home
```

name: home

|        time        |      spread      |
|--------------------|------------------|
|1970-01-01T00:00:00Z|2.3000000000000007|

[](#calculate-the-spread-of-each-field)

Calculate the spread of each field

```sql
SELECT SPREAD(*) FROM home
```

name: home

|        time        |spread\_co|spread\_hum|   spread\_temp   |
|--------------------|----------|-----------|------------------|
|1970-01-01T00:00:00Z|    26    |     1     |2.3000000000000007|

[](#calculate-the-spread-of-field-keys-that-match-a-regular-expression)

Calculate the spread of field keys that match a regular expression

```sql
SELECT SPREAD(/^[th]/) FROM home
```

name: home

|        time        |spread\_hum|   spread\_temp   |
|--------------------|-----------|------------------|
|1970-01-01T00:00:00Z|     1     |2.3000000000000007|

[](#calculate-the-spread-of-a-field-within-time-windows-grouped-by-time)

Calculate the spread of a field within time windows (grouped by time)

```sql
SELECT
  SPREAD(co)
FROM home
WHERE
  room = 'Kitchen'
  AND time >= '2022-01-01T08:00:00Z'
  AND time <= '2022-01-01T20:00:00Z'
GROUP BY time(6h)
```

name: home

|        time        |spread|
|--------------------|------|
|2022-01-01T06:00:00Z|  0   |
|2022-01-01T12:00:00Z|  9   |
|2022-01-01T18:00:00Z|  8   |

## STDDEV()

Returns the standard deviation of [field values](/influxdb3/core/reference/glossary/#field-value).

```sql
STDDEV(field_expression)
```

#### Arguments

* **field\_expression**: Expression to identify one or more fields to operate on.
  Can be a [field key](/influxdb3/core/reference/glossary/#field-key),
  constant, regular expression, or wildcard (`*`).
  Supports **numeric fields**.

#### Examples

[](#calculate-the-standard-deviation-of-a-field)

Calculate the standard deviation of a field

```sql
SELECT STDDEV(temp) FROM home
```

name: home

|        time        |      stddev      |
|--------------------|------------------|
|1970-01-01T00:00:00Z|0.5553238833191091|

[](#calculate-the-standard-deviation-of-each-field)

Calculate the standard deviation of each field

```sql
SELECT STDDEV(*) FROM home
```

name: home

|        time        |   stddev\_co    |    stddev\_hum    |   stddev\_temp   |
|--------------------|-----------------|-------------------|------------------|
|1970-01-01T00:00:00Z|7.774613519951676|0.25495097567963926|0.5553238833191091|

[](#calculate-the-standard-deviation-of-fields-where-the-field-key-matches-a-regular-expression)

Calculate the standard deviation of fields where the field key matches a regular expression

```sql
SELECT STDDEV(/^[th]/) FROM home
```

name: home

|        time        |    stddev\_hum    |   stddev\_temp   |
|--------------------|-------------------|------------------|
|1970-01-01T00:00:00Z|0.25495097567963926|0.5553238833191091|

[](#calculate-the-standard-deviation-of-a-field-within-time-windows-grouped-by-time)

Calculate the standard deviation of a field within time windows (grouped by time)

```sql
SELECT
  STDDEV(co)
FROM home
WHERE
  room = 'Kitchen'
  AND time >= '2022-01-01T08:00:00Z'
  AND time <= '2022-01-01T20:00:00Z'
GROUP BY time(6h)
```

name: home

|        time        |      stddev      |
|--------------------|------------------|
|2022-01-01T06:00:00Z|        0         |
|2022-01-01T12:00:00Z|3.6742346141747673|
|2022-01-01T18:00:00Z|        4         |

## SUM()

Returns the sum of [field values](/influxdb3/core/reference/glossary/#field-value).

```sql
SUM(field_expression)
```

#### Arguments

* **field\_expression**: Expression to identify one or more fields to operate on.
  Can be a [field key](/influxdb3/core/reference/glossary/#field-key),
  constant, regular expression, or wildcard (`*`).
  Supports **numeric fields**.

#### Examples

[](#calculate-the-sum-of-values-in-a-field)

Calculate the sum of values in a field

```sql
SELECT SUM(co) FROM home
```

name: home

|        time        |sum|
|--------------------|---|
|1970-01-01T00:00:00Z|137|

[](#calculate-the-sum-of-values-in-each-field)

Calculate the sum of values in each field

```sql
SELECT SUM(*) FROM home
```

name: home

|        time        |sum\_co|sum\_hum|sum\_temp|
|--------------------|-------|--------|---------|
|1970-01-01T00:00:00Z|  137  | 939.9  |  582.3  |

[](#calculate-the-sum-of-values-for-fields-where-the-field-key-matches-a-regular-expression)

Calculate the sum of values for fields where the field key matches a regular expression

```sql
SELECT SUM(/^[th]/) FROM home
```

name: home

|        time        |sum\_hum|sum\_temp|
|--------------------|--------|---------|
|1970-01-01T00:00:00Z| 939.9  |  582.3  |

[](#calculate-the-sum-of-values-in-a-field-within-time-windows-grouped-by-time)

Calculate the sum of values in a field within time windows (grouped by time)

```sql
SELECT
  SUM(co)
FROM home
WHERE
  room = 'Kitchen'
  AND time >= '2022-01-01T08:00:00Z'
  AND time <= '2022-01-01T20:00:00Z'
GROUP BY time(6h)
```

name: home

|        time        |sum|
|--------------------|---|
|2022-01-01T06:00:00Z| 0 |
|2022-01-01T12:00:00Z|21 |
|2022-01-01T18:00:00Z|66 |

#### Related

* [Aggregate data with InfluxQL](/influxdb3/core/query-data/influxql/aggregate-select/)
| time | count |
| --- | --- |
| time | count |
| 1970-01-01T00:00:00Z | 26 |

| time | count_co | count_hum | count_temp |
| --- | --- | --- | --- |
| time | count_co | count_hum | count_temp |
| 1970-01-01T00:00:00Z | 26 | 26 | 26 |

| time | count_hum | count_temp |
| --- | --- | --- |
| time | count_hum | count_temp |
| 1970-01-01T00:00:00Z | 26 | 26 |

| time | count |
| --- | --- |
| time | count |
| 1970-01-01T00:00:00Z | 12 |

| time | count |
| --- | --- |
| time | count |
| 2022-01-01T06:00:00Z | 4 |
| 2022-01-01T12:00:00Z | 6 |
| 2022-01-01T18:00:00Z | 3 |

| time | distinct |
| --- | --- |
| time | distinct |
| 1970-01-01T00:00:00Z | 0 |
| 1970-01-01T00:00:00Z | 1 |
| 1970-01-01T00:00:00Z | 3 |
| 1970-01-01T00:00:00Z | 4 |
| 1970-01-01T00:00:00Z | 7 |
| 1970-01-01T00:00:00Z | 5 |
| 1970-01-01T00:00:00Z | 9 |
| 1970-01-01T00:00:00Z | 18 |
| 1970-01-01T00:00:00Z | 14 |
| 1970-01-01T00:00:00Z | 22 |
| 1970-01-01T00:00:00Z | 17 |
| 1970-01-01T00:00:00Z | 26 |

| time | integral |
| --- | --- |
| time | integral |
| 1970-01-01T00:00:00Z | 266400 |

| time | integral |
| --- | --- |
| time | integral |
| 1970-01-01T00:00:00Z | 74 |

| time | integral_co | integral_hum | integral_temp |
| --- | --- | --- | --- |
| time | integral_co | integral_hum | integral_temp |
| 1970-01-01T00:00:00Z | 74 | 435 | 272.25 |

| time | integral_hum | integral_temp |
| --- | --- | --- |
| time | integral_hum | integral_temp |
| 1970-01-01T00:00:00Z | 435 | 272.25 |

| time | integral |
| --- | --- |
| time | integral |
| 2022-01-01T06:00:00Z | 0 |
| 2022-01-01T12:00:00Z | 30 |
| 2022-01-01T18:00:00Z | 44 |

| time | mean |
| --- | --- |
| time | mean |
| 1970-01-01T00:00:00Z | 22.396153846153844 |

| time | mean_co | mean_hum | mean_temp |
| --- | --- | --- | --- |
| time | mean_co | mean_hum | mean_temp |
| 1970-01-01T00:00:00Z | 5.269230769230769 | 36.15 | 22.396153846153844 |

| time | mean_hum | mean_temp |
| --- | --- | --- |
| time | mean_hum | mean_temp |
| 1970-01-01T00:00:00Z | 36.15 | 22.396153846153844 |

| time | mean |
| --- | --- |
| time | mean |
| 2022-01-01T06:00:00Z | 22.275 |
| 2022-01-01T12:00:00Z | 22.649999999999995 |
| 2022-01-01T18:00:00Z | 23.033333333333335 |

| time | median |
| --- | --- |
| time | median |
| 1970-01-01T00:00:00Z | 22.45 |

| time | median_co | median_hum | median_temp |
| --- | --- | --- | --- |
| time | median_co | median_hum | median_temp |
| 1970-01-01T00:00:00Z | 1 | 36.05 | 22.45 |

| time | median_hum | median_temp |
| --- | --- | --- |
| time | median_hum | median_temp |
| 1970-01-01T00:00:00Z | 36.05 | 22.45 |

| time | median |
| --- | --- |
| time | median |
| 2022-01-01T06:00:00Z | 22.549999999999997 |
| 2022-01-01T12:00:00Z | 22.7 |
| 2022-01-01T18:00:00Z | 23.1 |

| time | mode |
| --- | --- |
| time | mode |
| 1970-01-01T00:00:00Z | 0 |

| time | mode_co | mode_hum | mode_temp |
| --- | --- | --- | --- |
| time | mode_co | mode_hum | mode_temp |
| 1970-01-01T00:00:00Z | 0 | 36 | 22.7 |

| time | mode_hum | mode_temp |
| --- | --- | --- |
| time | mode_hum | mode_temp |
| 1970-01-01T00:00:00Z | 36 | 22.7 |

| time | mode |
| --- | --- |
| time | mode |
| 2022-01-01T06:00:00Z | 0 |
| 2022-01-01T12:00:00Z | 1 |
| 2022-01-01T18:00:00Z | 18 |

| time | spread |
| --- | --- |
| time | spread |
| 1970-01-01T00:00:00Z | 2.3000000000000007 |

| time | spread_co | spread_hum | spread_temp |
| --- | --- | --- | --- |
| time | spread_co | spread_hum | spread_temp |
| 1970-01-01T00:00:00Z | 26 | 1 | 2.3000000000000007 |

| time | spread_hum | spread_temp |
| --- | --- | --- |
| time | spread_hum | spread_temp |
| 1970-01-01T00:00:00Z | 1 | 2.3000000000000007 |

| time | spread |
| --- | --- |
| time | spread |
| 2022-01-01T06:00:00Z | 0 |
| 2022-01-01T12:00:00Z | 9 |
| 2022-01-01T18:00:00Z | 8 |

| time | stddev |
| --- | --- |
| time | stddev |
| 1970-01-01T00:00:00Z | 0.5553238833191091 |

| time | stddev_co | stddev_hum | stddev_temp |
| --- | --- | --- | --- |
| time | stddev_co | stddev_hum | stddev_temp |
| 1970-01-01T00:00:00Z | 7.774613519951676 | 0.25495097567963926 | 0.5553238833191091 |

| time | stddev_hum | stddev_temp |
| --- | --- | --- |
| time | stddev_hum | stddev_temp |
| 1970-01-01T00:00:00Z | 0.25495097567963926 | 0.5553238833191091 |

| time | stddev |
| --- | --- |
| time | stddev |
| 2022-01-01T06:00:00Z | 0 |
| 2022-01-01T12:00:00Z | 3.6742346141747673 |
| 2022-01-01T18:00:00Z | 4 |

| time | sum |
| --- | --- |
| time | sum |
| 1970-01-01T00:00:00Z | 137 |

| time | sum_co | sum_hum | sum_temp |
| --- | --- | --- | --- |
| time | sum_co | sum_hum | sum_temp |
| 1970-01-01T00:00:00Z | 137 | 939.9 | 582.3 |

| time | sum_hum | sum_temp |
| --- | --- | --- |
| time | sum_hum | sum_temp |
| 1970-01-01T00:00:00Z | 939.9 | 582.3 |

| time | sum |
| --- | --- |
| time | sum |
| 2022-01-01T06:00:00Z | 0 |
| 2022-01-01T12:00:00Z | 21 |
| 2022-01-01T18:00:00Z | 66 |