content/flux/v0/stdlib/experimental/count.md
experimental.count() returns the number of records in each input table.
The count is returned in the _value column and counts both null and non-null records.
experimental.count() returns 0 for empty tables.
To keep empty tables in your data, set the following parameters when using
the following functions:
filter(onEmpty: "keep")
window(createEmpty: true)
aggregateWindow(createEmpty: true)
(<-tables: stream[{A with _value: B}]) => stream[{A with _value: int}]
{{% caption %}} For more information, see Function type signatures. {{% /caption %}}
Input data. Default is piped-forward data (<-).
import "experimental"
import "sampledata"
sampledata.int()
|> experimental.count()
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| _time | _value | *tag |
|---|---|---|
| 2021-01-01T00:00:00Z | -2 | t1 |
| 2021-01-01T00:00:10Z | 10 | t1 |
| 2021-01-01T00:00:20Z | 7 | t1 |
| 2021-01-01T00:00:30Z | 17 | t1 |
| 2021-01-01T00:00:40Z | 15 | t1 |
| 2021-01-01T00:00:50Z | 4 | t1 |
| _time | _value | *tag |
|---|---|---|
| 2021-01-01T00:00:00Z | 19 | t2 |
| 2021-01-01T00:00:10Z | 4 | t2 |
| 2021-01-01T00:00:20Z | -3 | t2 |
| 2021-01-01T00:00:30Z | 19 | t2 |
| 2021-01-01T00:00:40Z | 13 | t2 |
| 2021-01-01T00:00:50Z | 1 | t2 |
| *tag | _value |
|---|---|
| t1 | 6 |
| *tag | _value |
|---|---|
| t2 | 6 |
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