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Posted to github@beam.apache.org by GitBox <gi...@apache.org> on 2020/08/03 17:25:02 UTC
[GitHub] [beam] davidcavazos commented on a change in pull request #12437: [BEAM-7390] Add mean code snippets
davidcavazos commented on a change in pull request #12437:
URL: https://github.com/apache/beam/pull/12437#discussion_r464553800
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File path: website/www/site/content/en/documentation/transforms/python/aggregation/mean.md
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@@ -16,23 +16,64 @@ limitations under the License.
-->
# Mean
-<table align="left">
- <a target="_blank" class="button"
- href="https://beam.apache.org/releases/pydoc/current/apache_beam.transforms.combiners.html?highlight=mean#apache_beam.transforms.combiners.Mean">
- <img src="https://beam.apache.org/images/logos/sdks/python.png" width="20px" height="20px"
- alt="Pydoc" />
- Pydoc
- </a>
-</table>
-<br><br>
+{{< localstorage language language-py >}}
+
+{{< button-pydoc path="apache_beam.transforms.combiners" class="Mean" >}}
Transforms for computing the arithmetic mean of the elements in a collection,
or the mean of the values associated with each key in a collection of
key-value pairs.
## Examples
-See [BEAM-7390](https://issues.apache.org/jira/browse/BEAM-7390) for updates.
-## Related transforms
-* [CombineGlobally](/documentation/transforms/python/aggregation/combineglobally) to combine elements.
\ No newline at end of file
+In the following example, we create a pipeline with a `PCollection`.
+Then, we get the element with the maximum value in different ways.
Review comment:
Thanks!
##########
File path: website/www/site/content/en/documentation/transforms/python/aggregation/mean.md
##########
@@ -16,23 +16,64 @@ limitations under the License.
-->
# Mean
-<table align="left">
- <a target="_blank" class="button"
- href="https://beam.apache.org/releases/pydoc/current/apache_beam.transforms.combiners.html?highlight=mean#apache_beam.transforms.combiners.Mean">
- <img src="https://beam.apache.org/images/logos/sdks/python.png" width="20px" height="20px"
- alt="Pydoc" />
- Pydoc
- </a>
-</table>
-<br><br>
+{{< localstorage language language-py >}}
+
+{{< button-pydoc path="apache_beam.transforms.combiners" class="Mean" >}}
Transforms for computing the arithmetic mean of the elements in a collection,
or the mean of the values associated with each key in a collection of
key-value pairs.
## Examples
-See [BEAM-7390](https://issues.apache.org/jira/browse/BEAM-7390) for updates.
-## Related transforms
-* [CombineGlobally](/documentation/transforms/python/aggregation/combineglobally) to combine elements.
\ No newline at end of file
+In the following example, we create a pipeline with a `PCollection`.
+Then, we get the element with the maximum value in different ways.
+
+### Example 1: Maximum element in a PCollection
+
+We use `Mean.Globally()` to get the average of the elements from the *entire* `PCollection`.
+
+{{< highlight py >}}
+{{< code_sample "sdks/python/apache_beam/examples/snippets/transforms/aggregation/mean.py" mean_globally >}}
+{{< /highlight >}}
+
+{{< paragraph class="notebook-skip" >}}
+Output:
+{{< /paragraph >}}
+
+{{< highlight class="notebook-skip" >}}
+{{< code_sample "sdks/python/apache_beam/examples/snippets/transforms/aggregation/mean_test.py" mean_element >}}
+{{< /highlight >}}
+
+{{< buttons-code-snippet
+ py="sdks/python/apache_beam/examples/snippets/transforms/aggregation/mean.py" >}}
+
+### Example 2: Maximum elements for each key
+
+We use `Mean.PerKey()` to get the avareage of the elements for each unique key in a `PCollection` of key-values.
Review comment:
Thanks!
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