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Posted to github@arrow.apache.org by "AlenkaF (via GitHub)" <gi...@apache.org> on 2023/03/28 11:35:48 UTC
[GitHub] [arrow] AlenkaF opened a new pull request, #34759: GH-34579: [Python][Docs] TableGroupBy.aggregate options
AlenkaF opened a new pull request, #34759:
URL: https://github.com/apache/arrow/pull/34759
### Rationale for this change
Add more information and examples to `pa.TableGroupBy.aggregate` method to make it clearer to use.
### What changes are included in this PR?
Changes in the `pa.TableGroupBy.aggregate` docstrings include:
- link to https://arrow.apache.org/docs/python/compute.html#grouped-aggregations
- extra examples
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[GitHub] [arrow] jorisvandenbossche merged pull request #34759: GH-34579: [Python][Docs] TableGroupBy.aggregate options
Posted by "jorisvandenbossche (via GitHub)" <gi...@apache.org>.
jorisvandenbossche merged PR #34759:
URL: https://github.com/apache/arrow/pull/34759
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[GitHub] [arrow] github-actions[bot] commented on pull request #34759: GH-34579: [Python][Docs] TableGroupBy.aggregate options
Posted by "github-actions[bot] (via GitHub)" <gi...@apache.org>.
github-actions[bot] commented on PR #34759:
URL: https://github.com/apache/arrow/pull/34759#issuecomment-1488120128
Revision: 4b3161b4c0d3539c9ef01859d737393f4e430676
Submitted crossbow builds: [ursacomputing/crossbow @ actions-2d3b2209d1](https://github.com/ursacomputing/crossbow/branches/all?query=actions-2d3b2209d1)
|Task|Status|
|----|------|
|preview-docs|[](https://github.com/ursacomputing/crossbow/actions/runs/4551630836/jobs/8025935557)|
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[GitHub] [arrow] AlenkaF commented on pull request #34759: GH-34579: [Python][Docs] TableGroupBy.aggregate options
Posted by "AlenkaF (via GitHub)" <gi...@apache.org>.
AlenkaF commented on PR #34759:
URL: https://github.com/apache/arrow/pull/34759#issuecomment-1488353836
Generated docs for the change in this PR can be viewed here: http://crossbow.voltrondata.com/pr_docs/34759/python/generated/pyarrow.TableGroupBy.html#pyarrow.TableGroupBy.aggregate
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[GitHub] [arrow] AlenkaF commented on pull request #34759: GH-34579: [Python][Docs] TableGroupBy.aggregate options
Posted by "AlenkaF (via GitHub)" <gi...@apache.org>.
AlenkaF commented on PR #34759:
URL: https://github.com/apache/arrow/pull/34759#issuecomment-1488115883
@github-actions crossbow submit preview-docs
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[GitHub] [arrow] ursabot commented on pull request #34759: GH-34579: [Python][Docs] TableGroupBy.aggregate options
Posted by "ursabot (via GitHub)" <gi...@apache.org>.
ursabot commented on PR #34759:
URL: https://github.com/apache/arrow/pull/34759#issuecomment-1489037296
Benchmark runs are scheduled for baseline = 2c9340dd1795bedcc6a43975e26580b4f27912ad and contender = 24ba1cf75c01040b279514ecc063975de272b766. 24ba1cf75c01040b279514ecc063975de272b766 is a master commit associated with this PR. Results will be available as each benchmark for each run completes.
Conbench compare runs links:
[Finished :arrow_down:0.0% :arrow_up:0.0%] [ec2-t3-xlarge-us-east-2](https://conbench.ursa.dev/compare/runs/7de9f55bb95e404c9bb07ec95edf6648...12cc70195283455b85ee6dfee92d555e/)
[Failed :arrow_down:0.8% :arrow_up:1.57%] [test-mac-arm](https://conbench.ursa.dev/compare/runs/ac5d5deb91404233be108cf347dd9ea0...73c07ce7c0554d13a81515856991737b/)
[Finished :arrow_down:0.0% :arrow_up:0.0%] [ursa-i9-9960x](https://conbench.ursa.dev/compare/runs/abe49752e46c474383c1bbe4338cbd0e...c6815716b5e342968f63d3255dfdf216/)
[Finished :arrow_down:0.25% :arrow_up:0.0%] [ursa-thinkcentre-m75q](https://conbench.ursa.dev/compare/runs/edc63e1a607e45b8af0f8cff72319eba...e6a4a34e7e6349019c4153a559ab5b27/)
Buildkite builds:
[Finished] [`24ba1cf7` ec2-t3-xlarge-us-east-2](https://buildkite.com/apache-arrow/arrow-bci-benchmark-on-ec2-t3-xlarge-us-east-2/builds/2592)
[Failed] [`24ba1cf7` test-mac-arm](https://buildkite.com/apache-arrow/arrow-bci-benchmark-on-test-mac-arm/builds/2622)
[Finished] [`24ba1cf7` ursa-i9-9960x](https://buildkite.com/apache-arrow/arrow-bci-benchmark-on-ursa-i9-9960x/builds/2590)
[Finished] [`24ba1cf7` ursa-thinkcentre-m75q](https://buildkite.com/apache-arrow/arrow-bci-benchmark-on-ursa-thinkcentre-m75q/builds/2613)
[Finished] [`2c9340dd` ec2-t3-xlarge-us-east-2](https://buildkite.com/apache-arrow/arrow-bci-benchmark-on-ec2-t3-xlarge-us-east-2/builds/2591)
[Finished] [`2c9340dd` test-mac-arm](https://buildkite.com/apache-arrow/arrow-bci-benchmark-on-test-mac-arm/builds/2621)
[Finished] [`2c9340dd` ursa-i9-9960x](https://buildkite.com/apache-arrow/arrow-bci-benchmark-on-ursa-i9-9960x/builds/2589)
[Finished] [`2c9340dd` ursa-thinkcentre-m75q](https://buildkite.com/apache-arrow/arrow-bci-benchmark-on-ursa-thinkcentre-m75q/builds/2612)
Supported benchmarks:
ec2-t3-xlarge-us-east-2: Supported benchmark langs: Python, R. Runs only benchmarks with cloud = True
test-mac-arm: Supported benchmark langs: C++, Python, R
ursa-i9-9960x: Supported benchmark langs: Python, R, JavaScript
ursa-thinkcentre-m75q: Supported benchmark langs: C++, Java
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[GitHub] [arrow] jorisvandenbossche commented on a diff in pull request #34759: GH-34579: [Python][Docs] TableGroupBy.aggregate options
Posted by "jorisvandenbossche (via GitHub)" <gi...@apache.org>.
jorisvandenbossche commented on code in PR #34759:
URL: https://github.com/apache/arrow/pull/34759#discussion_r1150583383
##########
python/pyarrow/table.pxi:
##########
@@ -5515,6 +5515,9 @@ list[tuple(str, str, FunctionOptions)]
column names, for unary, nullary and n-ary aggregation functions
respectively.
+ For the list of function names and respective aggregation
+ function options see: :ref:`py-grouped-aggrs`.
Review Comment:
```suggestion
function options see :ref:`py-grouped-aggrs`.
```
##########
python/pyarrow/table.pxi:
##########
@@ -5527,20 +5530,58 @@ list[tuple(str, str, FunctionOptions)]
... pa.array(["a", "a", "b", "b", "c"]),
... pa.array([1, 2, 3, 4, 5]),
... ], names=["keys", "values"])
+
+ Sum the column "values" over the grouped column "keys":
+
>>> t.group_by("keys").aggregate([("values", "sum")])
pyarrow.Table
values_sum: int64
keys: string
----
values_sum: [[3,7,5]]
keys: [["a","b","c"]]
+
+ Count the rows over the grouped column "keys":
+
>>> t.group_by("keys").aggregate([([], "count_all")])
pyarrow.Table
count_all: int64
keys: string
----
count_all: [[2,2,1]]
keys: [["a","b","c"]]
+
+ Do multiple aggregations:
+
+ >>> t.group_by("keys").aggregate([
+ ... ("values", "sum"),
+ ... ("keys", "count")
+ ... ])
+ pyarrow.Table
+ values_sum: int64
+ keys_count: int64
+ keys: string
+ ----
+ values_sum: [[3,7,5]]
+ keys_count: [[2,2,1]]
+ keys: [["a","b","c"]]
+
+ Count the number of non-null values for column "values"
+ over the grouped column "keys":
+
+ >>> import pyarrow.compute as pc
+ >>> t.group_by(["keys"]).aggregate([
+ ... ("values", "count", pc.CountOptions(mode="all"))
Review Comment:
```suggestion
... ("values", "count", pc.CountOptions(mode="only_valid"))
```
If you want the "number of non-null values" as mentioned above, you need this option (which is actually the default, but OK to show it explicitly I think)
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