docs-v2/content/v2.0/reference/flux/stdlib/contrib/rows/map.md

title	description	menu	weight	v2.0/tags	related
rows.map() function	The `rows.map()` function is an alternate implementation of [`map()`](/v2.0/reference/flux/stdlib/built-in/transformations/map/) that is faster, but more limited than `map()`.	v2_0_ref name parent rows.map Rows	202	functions package map	/v2.0/reference/flux/stdlib/built-in/transformations/map/

The rows.map() function is an alternate implementation of map() that is faster, but more limited than map(). rows.map() cannot modify groups keys and, therefore, does not need to regroup tables. Attempts to change columns in the group key are ignored.

Function type: Transformation

import "contrib/jsternberg/rows"

rows.map( fn: (r) => ({_value: r._value * 100.0}))

Parameters

fn

A single argument function to apply to each record. The return value must be a record.

Data type: Function

{{% note %}} Use the with operator to preserve columns not in the group and not explicitly mapped in the operation. {{% /note %}}

Examples

• Perform mathemtical operations on column values
• Preserve all columns in the operation
• Attempt to remap columns in the group key

---

Perform mathemtical operations on column values

The following example returns the square of each value in the _value column:

import "contrib/jsternberg/rows"

data
  |> rows.map(fn: (r) ({ _value: r._value * r._value }))

{{% note %}}

Important notes

The _time column is dropped because:

• It's not in the group key.
• It's not explicitly mapped in the operation.
• The with operator was not used to include existing columns. {{% /note %}}

{{< flex >}} {{% flex-content %}}

Input tables

Group key: tag,_field

tag	_field	_time	_value
tag1	foo	0001	1.9
tag1	foo	0002	2.4
tag1	foo	0003	2.1

tag	_field	_time	_value
tag2	bar	0001	3.1
tag2	bar	0002	3.8
tag2	bar	0003	1.7
{{% /flex-content %}}

{{% flex-content %}}

Output tables

Group key: tag,_field

tag	_field	_value
tag1	foo	3.61
tag1	foo	5.76
tag1	foo	4.41

tag	_field	_value
tag2	bar	9.61
tag2	bar	14.44
tag2	bar	2.89
{{% /flex-content %}}
{{< /flex >}}

---

Preserve all columns in the operation

Use the with operator in your mapping operation to preserve all columns, including those not in the group key, without explicitly remapping them.

import "contrib/jsternberg/rows"

data
  |> rows.map(fn: (r) ({ r with _value: r._value * r._value }))

{{% note %}}

Important notes

• The mapping operation remaps the _value column.
• The with operator preserves all other columns not in the group key (_time). {{% /note %}}

{{< flex >}} {{% flex-content %}}

Input tables

Group key: tag,_field

tag	_field	_time	_value
tag1	foo	0001	1.9
tag1	foo	0002	2.4
tag1	foo	0003	2.1

tag	_field	_time	_value
tag2	bar	0001	3.1
tag2	bar	0002	3.8
tag2	bar	0003	1.7
{{% /flex-content %}}

{{% flex-content %}}

Output tables

Group key: tag,_field

tag	_field	_time	_value
tag1	foo	0001	3.61
tag1	foo	0002	5.76
tag1	foo	0003	4.41

tag	_field	_time	_value
tag2	bar	0001	9.61
tag2	bar	0002	14.44
tag2	bar	0003	2.89
{{% /flex-content %}}
{{< /flex >}}

---

Attempt to remap columns in the group key

import "contrib/jsternberg/rows"

data
  |> rows.map(fn: (r) ({ r with tag: "tag3" }))

{{% note %}}

Important notes

• Remapping the tag column to "tag3" is ignored because tag is part of the group key.
• The with operator preserves columns not in the group key (_time and _value). {{% /note %}}

{{< flex >}} {{% flex-content %}}

Input tables

Group key: tag,_field

tag	_field	_time	_value
tag1	foo	0001	1.9
tag1	foo	0002	2.4
tag1	foo	0003	2.1

tag	_field	_time	_value
tag2	bar	0001	3.1
tag2	bar	0002	3.8
tag2	bar	0003	1.7
{{% /flex-content %}}

{{% flex-content %}}

Output tables

Group key: tag,_field

tag	_field	_time	_value
tag1	foo	0001	1.9
tag1	foo	0002	2.4
tag1	foo	0003	2.1

tag	_field	_time	_value
tag2	bar	0001	3.1
tag2	bar	0002	3.8
tag2	bar	0003	1.7
{{% /flex-content %}}
{{< /flex >}}

---

{{% note %}}

Package author and maintainer

Github: @jsternberg
InfluxDB Slack: @Jonathan Sternberg {{% /note %}}