docs-v2/content/shared/influxdb-v2/tools/notebooks/clean-data.md

Learn how to create a notebook that normalizes data. Data normalization is the process of modifying or cleaning data to make it easier to work with. Examples include adjusting numeric values to a uniform scale and modifying strings.

Walk through the following example to create a notebook that queries NOAA NDBC sample data, normalizes degree-based wind directions to cardinal directions, and then writes the normalized data to a bucket.

{{< show-in "cloud,cloud-serverless" >}}

[!Important] Note: Using sample data counts towards your total InfluxDB Cloud usage. {{< /show-in >}}

1. Create a new notebook.

2. In the Build a Query cell:

   1. In the FROM column under {{% caps %}}Sample{{% /caps %}}, select NOAA National Buoy Data.
   2. In the next FILTER column, select _measurement from the drop-down list and select the ndbc measurement in the list of measurements.
   3. In the next FILTER column, select _field from the drop-down list, and select the wind_dir_degt field from the list of fields.

3. Click {{% icon "notebook-add-cell" %}} after your Build a Query cell to add a new cell and select {{% caps %}}Flux Script{{% /caps %}}.

4. In the Flux script cell:

   1. Define a custom function (cardinalDir()) that converts a numeric degree value to a cardinal direction (N, NNE, NE, etc.).

   2. Use __PREVIOUS_RESULT__ to load the output of the previous notebook cell into the Flux script.

   3. Use map() to iterate over each input row, update the field key to wind_dir_cardinal, and normalize the _value column to a cardinal direction using the custom cardinalDir() function.

   4. Use to() to write the normalized data back to InfluxDB. Specify an existing bucket to write to or create a new bucket.

      import "array"
      
      cardinalDir = (d) => {
          _cardinal = if d >= 348.7 or d < 11.25 then "N"
          else if d >= 11.25 and d < 33.75 then "NNE"
          else if d >= 33.75 and d < 56.25 then "NE"
          else if d >= 56.25 and d < 78.75 then "ENE"
          else if d >= 78.75 and d < 101.25 then "E"
          else if d >= 101.25 and d < 123.75 then "ESE"
          else if d >= 123.75 and d < 146.25 then "SE"
          else if d >= 146.25 and d < 168.75 then "SSE"
          else if d >= 168.75 and d < 191.25 then "S"
          else if d >= 191.25 and d < 213.75 then "SSW"
          else if d >= 213.75 and d < 236.25 then "SW"
          else if d >= 236.25 and d < 258.75 then "WSW"
          else if d >= 258.75 and d < 281.25 then "W"
          else if d >= 281.25 and d < 303.75 then "WNW"
          else if d >= 303.75 and d < 326.25 then "NW"
          else if d >= 326.25 and d < 348.75 then "NNW"
          else ""
      
          return _cardinal
      }
      
      __PREVIOUS_RESULT__
          |> map(fn: (r) => ({r with
              _field: "wind_dir_cardinal",
              _value: cardinalDir(d: r._value),
          }))
          |> to(bucket: "example-bucket")
      

{{% show-in "v2" %}} 4. Click {{% icon "notebook-add-cell" %}} after your Flux Script cell to add a new cell and select {{% caps %}}Output to Bucket{{% /caps %}}. Select a bucket from the {{% icon "bucket" %}} Choose a bucket drop-down list. {{% /show-in %}}

5. (Optional) Click {{% icon "notebook-add-cell" %}} and select Note to add a cell containing notes about what this notebook does. For example, the cell might say, "This notebook converts decimal degree wind direction values to cardinal directions." {{% show-in "v2" %}}
6. Click Preview in the upper left to verify that your notebook runs and previews the output. {{% /show-in %}}
7. Click Run to run the notebook and write the normalized data to your bucket.

Continuously run a notebook

To continuously run your notebook, export the notebook as a task:

1. Click {{% icon "notebook-add-cell" %}} to add a new cell and then select {{% caps %}}Task{{% /caps %}}.

2. Provide the following:

   • Every: Interval that the task should run at.
   • Offset: (Optional) Time to wait after the defined interval to execute the task. This allows the task to capture late-arriving data.

3. Click {{% icon "export" %}} Export as Task.