Yikun opened a new pull request, #36816:
URL: https://github.com/apache/spark/pull/36816
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### What changes were proposed in this pull request?
Add migration guide for pandas 1.4 behavior changes:
* SPARK-39054 https://github.com/apache/spark/pull/36581: In Spark 3.4, if
Pandas on Spark API `Groupby.apply`'s `func` parameter return type is not
specified and `compute.shortcut_limit` is set to `0`, the sampling rows will be
set to 2 (ensure sampling rows always >= 2) to make sure infer schema is
accurate.
* SPARK-38822 https://github.com/apache/spark/pull/36168 In Spark 3.4, if
Pandas on Spark API `Index.insert` is out of bounds, will rasied IndexError
with `index {} is out of bounds for axis 0 with size {}` to follow pandas 1.4
behavior.
* SPARK-38857 https://github.com/apache/spark/pull/36159 In Spark 3.4, the
series name will be preserved in Pandas on Spark API `Series.mode` to follow
pandas 1.4 behavior.
* SPARK-38859 https://github.com/apache/spark/pull/36142 In Spark 3.4, the
Pandas on Spark API `Index.__setitem__` will first to check `value` type is
`Column` to avoid raise unexpected error in `is_list_like` like `Cannot convert
column into bool: please use '&' for 'and', '|' for 'or', '~' for 'not' when
building DataFrame boolean expressions.`.
* SPARK-38820 https://github.com/apache/spark/pull/36357 In Spark 3.4, the
Pandas on Spark API `astype('category')` will also refresh `categories.dtype`
according to original data `dtype` to follow pandas 1.4 behavior.
* SPARK-38947 https://github.com/apache/spark/pull/36464 In Spark 3.4, the
Pandas on Spark API supports groupby positional indexing in `GroupBy.head` and
`GroupBy.tail` to follow pandas 1.4. Negative arguments now work correctly and
result in ranges relative to the end and start of each group, Previously,
negative arguments returned empty frames.
* SPARK-39317 https://github.com/apache/spark/pull/36699 In Spark 3.4, the
infer schema process of `groupby.apply` in Pandas on Spark, will first infer
the pandas type to ensure the accuracy of the pandas `dtype` as much as
possible.
* SPARK-39314 https://github.com/apache/spark/pull/36711 In Spark 3.4, the
`Series.concat` sort parameter will be respected to follow pandas 1.4 behaviors.
For other test only fixes, I don't add migration doc: SPARK-38821
SPARK-39053 SPARK-38982
### Why are the changes needed?
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### Does this PR introduce _any_ user-facing change?
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### How was this patch tested?
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