Fill null values in data
See the equivalent InfluxDB v2 documentation: Fill null values in data.
Use the fill() function
to replace null values with:
data
|> fill(usePrevious: true)
// OR
data
|> fill(value: 0.0)
Fill empty windows of time
The fill() function does not fill empty windows of time.
It only replaces null values in existing data.
Filling empty windows of time requires time interpolation
(see influxdata/flux#2428).
Fill with the previous value
To fill null values with the previous non-null value, set the usePrevious parameter to true.
Values remain null if there is no previous non-null value in the table.
data
|> fill(usePrevious: true)
Given the following input:
| _time | _value |
|---|---|
| 2020-01-01T00:01:00Z | null |
| 2020-01-01T00:02:00Z | 0.8 |
| 2020-01-01T00:03:00Z | null |
| 2020-01-01T00:04:00Z | null |
| 2020-01-01T00:05:00Z | 1.4 |
fill(usePrevious: true) returns:
| _time | _value |
|---|---|
| 2020-01-01T00:01:00Z | null |
| 2020-01-01T00:02:00Z | 0.8 |
| 2020-01-01T00:03:00Z | 0.8 |
| 2020-01-01T00:04:00Z | 0.8 |
| 2020-01-01T00:05:00Z | 1.4 |
Fill with a specified value
To fill null values with a specified value, use the value parameter to specify the fill value.
The fill value must match the data type
of the column.
data
|> fill(value: 0.0)
Given the following input:
| _time | _value |
|---|---|
| 2020-01-01T00:01:00Z | null |
| 2020-01-01T00:02:00Z | 0.8 |
| 2020-01-01T00:03:00Z | null |
| 2020-01-01T00:04:00Z | null |
| 2020-01-01T00:05:00Z | 1.4 |
fill(value: 0.0) returns:
| _time | _value |
|---|---|
| 2020-01-01T00:01:00Z | 0.0 |
| 2020-01-01T00:02:00Z | 0.8 |
| 2020-01-01T00:03:00Z | 0.0 |
| 2020-01-01T00:04:00Z | 0.0 |
| 2020-01-01T00:05:00Z | 1.4 |
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