docs-v2/content/flux/v0/stdlib/csv/from.md

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---
title: csv.from() function
description: >
`csv.from()` retrieves data from a comma separated value (CSV) data source and
returns a stream of tables.
menu:
flux_v0_ref:
name: csv.from
parent: csv
identifier: csv/from
weight: 101
flux/v0/tags: [csv, inputs]
---
<!------------------------------------------------------------------------------
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To make updates to this documentation, update the function comments above the
function definition in the Flux source code:
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Fluxdoc syntax: https://github.com/influxdata/flux/blob/master/docs/fluxdoc.md
------------------------------------------------------------------------------->
`csv.from()` retrieves data from a comma separated value (CSV) data source and
returns a stream of tables.
##### Function type signature
```js
(?csv: string, ?file: string, ?mode: string) => stream[A] where A: Record
```
{{% caption %}}
For more information, see [Function type signatures](/flux/v0/function-type-signatures/).
{{% /caption %}}
## Parameters
### csv
CSV data.
Supports anonotated CSV or raw CSV. Use `mode` to specify the parsing mode.
### file
File path of the CSV file to query.
The path can be absolute or relative.
If relative, it is relative to the working directory of the `fluxd` process.
The CSV file must exist in the same file system running the `fluxd` process.
### mode
is the CSV parsing mode. Default is `annotations`.
**Available annotation modes**
- **annotations**: Use CSV notations to determine column data types.
- **raw**: Parse all columns as strings and use the first row as the
header row and all subsequent rows as data.
## Examples
- [Query annotated CSV data from file](#query-annotated-csv-data-from-file)
- [Query raw data from CSV file](#query-raw-data-from-csv-file)
- [Query an annotated CSV string](#query-an-annotated-csv-string)
- [Query a raw CSV string](#query-a-raw-csv-string)
### Query annotated CSV data from file
```js
import "csv"
csv.from(file: "path/to/data-file.csv")
```
### Query raw data from CSV file
```js
import "csv"
csv.from(file: "/path/to/data-file.csv", mode: "raw")
```
### Query an annotated CSV string
```js
import "csv"
csvData =
"
#datatype,string,long,dateTime:RFC3339,dateTime:RFC3339,dateTime:RFC3339,string,string,double
#group,false,false,false,false,false,true,true,false
#default,,,,,,,,
,result,table,_start,_stop,_time,region,host,_value
,mean,0,2018-05-08T20:50:00Z,2018-05-08T20:51:00Z,2018-05-08T20:50:00Z,east,A,15.43
,mean,0,2018-05-08T20:50:00Z,2018-05-08T20:51:00Z,2018-05-08T20:51:00Z,east,A,65.15
,mean,1,2018-05-08T20:50:00Z,2018-05-08T20:51:00Z,2018-05-08T20:50:20Z,east,B,59.25
,mean,1,2018-05-08T20:50:00Z,2018-05-08T20:51:00Z,2018-05-08T20:51:20Z,east,B,18.67
,mean,2,2018-05-08T20:50:00Z,2018-05-08T20:51:00Z,2018-05-08T20:50:40Z,east,C,52.62
,mean,2,2018-05-08T20:50:00Z,2018-05-08T20:51:00Z,2018-05-08T20:51:40Z,east,C,82.16
"
csv.from(csv: csvData)
```
{{< expand-wrapper >}}
{{% expand "View example output" %}}
#### Output data
| _start | _stop | _time | *region | *host | _value |
| -------------------- | -------------------- | -------------------- | ------- | ----- | ------- |
| 2018-05-08T20:50:00Z | 2018-05-08T20:51:00Z | 2018-05-08T20:50:00Z | east | A | 15.43 |
| 2018-05-08T20:50:00Z | 2018-05-08T20:51:00Z | 2018-05-08T20:51:00Z | east | A | 65.15 |
| _start | _stop | _time | *region | *host | _value |
| -------------------- | -------------------- | -------------------- | ------- | ----- | ------- |
| 2018-05-08T20:50:00Z | 2018-05-08T20:51:00Z | 2018-05-08T20:50:20Z | east | B | 59.25 |
| 2018-05-08T20:50:00Z | 2018-05-08T20:51:00Z | 2018-05-08T20:51:20Z | east | B | 18.67 |
| _start | _stop | _time | *region | *host | _value |
| -------------------- | -------------------- | -------------------- | ------- | ----- | ------- |
| 2018-05-08T20:50:00Z | 2018-05-08T20:51:00Z | 2018-05-08T20:50:40Z | east | C | 52.62 |
| 2018-05-08T20:50:00Z | 2018-05-08T20:51:00Z | 2018-05-08T20:51:40Z | east | C | 82.16 |
{{% /expand %}}
{{< /expand-wrapper >}}
### Query a raw CSV string
```js
import "csv"
csvData =
"
_start,_stop,_time,region,host,_value
2018-05-08T20:50:00Z,2018-05-08T20:51:00Z,2018-05-08T20:50:00Z,east,A,15.43
2018-05-08T20:50:00Z,2018-05-08T20:51:00Z,2018-05-08T20:50:20Z,east,B,59.25
2018-05-08T20:50:00Z,2018-05-08T20:51:00Z,2018-05-08T20:50:40Z,east,C,52.62
"
csv.from(csv: csvData, mode: "raw")
```
{{< expand-wrapper >}}
{{% expand "View example output" %}}
#### Output data
| _start | _stop | _time | region | host | _value |
| -------------------- | -------------------- | -------------------- | ------- | ----- | ------- |
| 2018-05-08T20:50:00Z | 2018-05-08T20:51:00Z | 2018-05-08T20:50:00Z | east | A | 15.43 |
| 2018-05-08T20:50:00Z | 2018-05-08T20:51:00Z | 2018-05-08T20:50:20Z | east | B | 59.25 |
| 2018-05-08T20:50:00Z | 2018-05-08T20:51:00Z | 2018-05-08T20:50:40Z | east | C | 52.62 |
{{% /expand %}}
{{< /expand-wrapper >}}