[Bug]: DataFrame API skew() and kurtosis() raise UnboundLocalError when all the data is in one partition #41283

What happened?

On master (d7d31e9), Series.skew() and Series.kurtosis() / kurt() in the DataFrame API (also reached through DataFrame.skew(), DataFrame.kurt() and agg('skew')) fail with UnboundLocalError: cannot access local variable 'combined_n' where it is not associated with a value when one partition holds all the values. combine_moments in dataframe/frames.py assigns combined_n only when it merges two non-empty partitions, but the final formula always reads it.

Example: to_dataframe(p | beam.Create([beam.Row(x=float(i * i)) for i in range(6)])).x.skew() fails on the default runner and on the FnApiRunner; pandas returns 0.9191843544212499 (skew) and -0.25414322711619963 (kurtosis) for the same values. With fewer than 3 values (skew) or 4 (kurtosis), or with all-equal values, the function returns before the formula, so those cases do not fail.

Expected: the same result as pandas. I plan to fix it by using the accumulated count n, which equals combined_n after every merge.

Issue Priority

Priority: 2 (default / most bugs should be filed as P2)

Issue Components

• Component: Python SDK
• Component: Java SDK
• Component: Go SDK
• Component: Typescript SDK
• Component: IO connector
• Component: Beam YAML
• Component: Beam examples
• Component: Beam playground
• Component: Beam katas
• Component: Website
• Component: Infrastructure
• Component: Spark Runner
• Component: Flink Runner
• Component: Prism Runner
• Component: Hazelcast Jet Runner
• Component: Google Cloud Dataflow Runner