DOC: ecosystem.rst: Koalas #26425
DOC: ecosystem.rst: Koalas #26425
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Codecov Report
@@ Coverage Diff @@
## master #26425 +/- ##
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- Coverage 91.69% 91.69% -0.01%
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Files 174 174
Lines 50741 50741
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- Hits 46529 46525 -4
- Misses 4212 4216 +4
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1 similar comment
Codecov Report
@@ Coverage Diff @@
## master #26425 +/- ##
==========================================
- Coverage 91.69% 91.69% -0.01%
==========================================
Files 174 174
Lines 50741 50741
==========================================
- Hits 46529 46525 -4
- Misses 4212 4216 +4
Continue to review full report at Codecov.
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Codecov Report
@@ Coverage Diff @@
## master #26425 +/- ##
==========================================
- Coverage 91.73% 91.72% -0.01%
==========================================
Files 174 174
Lines 50741 50741
==========================================
- Hits 46548 46544 -4
- Misses 4193 4197 +4
Continue to review full report at Codecov.
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I see that you took the description from Koalas documentation, but it sounds more like a sales speech than a useful description (e.g. be more productive when interacting with big data).
Also, I think we can safely assume that users checking this documentation know what pandas is (and probably spark).
Can you please rephrases, being concise on what Koalas does. Also, didn't check Koalas, but I doubt it implements the full pandas API with spark as a backend. Please add what users can expect in terms of stability and completeness of the API.
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Sure, will do. Thanks! |
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| Koalas provides a familiar pandas DataFrame interface on top of Apache Spark. It enables users to leverage multi-cores on one machine or a cluster of machines to speed up or scale their DataFrame code. | ||
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@datapythonista, how does it looks like?
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That is much better in my opinion. Let's see if anyone else has feedback, but I think this gives much more relevant information to the readers than before. Thanks!
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| Koalas provides a familiar pandas DataFrame interface on top of Apache Spark. It enables users to leverage multi-cores on one machine or a cluster of machines to speed up or scale their DataFrame code. | ||
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That is much better in my opinion. Let's see if anyone else has feedback, but I think this gives much more relevant information to the readers than before. Thanks!
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Thank you, @datapythonista, @WillAyd and @TomAugspurger for your guidance and approval. |
git diff upstream/master -u -- "*.py" | flake8 --diffI (almost) copied and pasted from its README.md.