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https://issues.apache.org/jira/browse/BEAM-12074?focusedWorklogId=608160&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-608160
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ASF GitHub Bot logged work on BEAM-12074:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 07/Jun/21 23:27
Start Date: 07/Jun/21 23:27
Worklog Time Spent: 10m
Work Description: TheNeuralBit commented on a change in pull request
#14961:
URL: https://github.com/apache/beam/pull/14961#discussion_r647005303
##########
File path: sdks/python/apache_beam/dataframe/frames.py
##########
@@ -127,6 +127,16 @@ def wrapper(self, *args, **kwargs):
return frame_base.with_docs_from(base)(wrapper)
+# Docstring to use for head and tail (commonly used to peek at datasets)
+_PEEK_METHOD_EXPLANATION = (
+ "because it is `order-sensitive
<https://s.apache.org/dataframe-order-sensitive-operations>`_.\n\n"
+ "If you'd like to use it to peek at a large dataset, interactive Beam's "
+ ":func:`ib.collect
<apache_beam.runners.interactive.interactive_beam.collect>` "
+ "with ``n`` specified may be a useful alternative.\n\n"
+ "Also consider using :meth:`DeferredDataFrame.nlargest` if you're "
+ "interested in finding the top-N elements in a dataset.")
Review comment:
Yeah `sample` is the last operation I feel like is a must-have for GA.
I've just been thinking about it so far. I'd like to discuss some of the
hangups in-person. A preview:
- Making `frac` work is trivial since you can just do `frac` on each
partition.
- I'm not sure about the right way to make `n` work though (which we should
figure out, since it's the most natural alternative to head).
- I think we can support `weights` by doing a little extra work to adjust
the weights within each partition.
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Issue Time Tracking
-------------------
Worklog Id: (was: 608160)
Time Spent: 17h 10m (was: 17h)
> Add API Documentation for the DataFrame API
> -------------------------------------------
>
> Key: BEAM-12074
> URL: https://issues.apache.org/jira/browse/BEAM-12074
> Project: Beam
> Issue Type: Improvement
> Components: sdk-py-core
> Reporter: Brian Hulette
> Assignee: Brian Hulette
> Priority: P2
> Labels: dataframe-api, stale-P2
> Time Spent: 17h 10m
> Remaining Estimate: 0h
>
> For the most part this can be pulled directly from pandas methods, but we
> should add specific notes about any divergences that the Beam DataFrame API
> has from pandas.
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