HyukjinKwon opened a new pull request, #53958:
URL: https://github.com/apache/spark/pull/53958
### What changes were proposed in this pull request?
Add support for keyword arguments in `GroupedData.agg()` to allow a more
Pythonic syntax for specifying column-to-aggregation-function mappings.
### Why are the changes needed?
Currently, users must use dictionary syntax `agg({"age": "min"})` to specify
aggregations. Keyword arguments provide a more intuitive and Pythonic
alternative: `agg(age="min", salary="max")`, which is consistent with other
Python APIs and reduces verbosity.
### Does this PR introduce _any_ user-facing change?
Yes. Users can now use keyword arguments for aggregations:
Before:
```python
df.groupBy("name").agg({"age": "min", "salary": "max"})
```
After (new syntax):
```python
df.groupBy("name").agg(age="min", salary="max")
```
### How was this patch tested?
Unittest added.
### Was this patch authored or co-authored using generative AI tooling?
No.
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