[ https://issues.apache.org/jira/browse/ARROW-18137?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Weston Pace resolved ARROW-18137. --------------------------------- Fix Version/s: 11.0.0 Resolution: Fixed Issue resolved by pull request 14482 [https://github.com/apache/arrow/pull/14482] > [Python][Docs] Allow passing no aggregations to TableGroupBy.aggregate > ---------------------------------------------------------------------- > > Key: ARROW-18137 > URL: https://issues.apache.org/jira/browse/ARROW-18137 > Project: Apache Arrow > Issue Type: New Feature > Components: Documentation, Python > Affects Versions: 9.0.0 > Reporter: Jacek Pliszka > Assignee: Jacek Pliszka > Priority: Minor > Labels: pull-request-available > Fix For: 11.0.0 > > Time Spent: 1h 20m > Remaining Estimate: 0h > > If we could allow TableGroupBy.aggregate to accept no aggregation functions > then it would behave like pandas drop_duplicates. > {code:python} > t.group_by(['keys', 'values']).aggregate() > {code} > I did some naive benchmarks and looks like it should be 30% faster than > converting to pandas and deduplicating. This was my naive test: > {code:python} > t.append_column('i', pa.array([1]*len(t),pa.int64())).group_by(['keys', > 'values']).aggregate([("i", "max")]).drop(['i_max']) > {code} > And on small 5M table it took 245ms while 359ms for > t.to_pandas().drop_duplicates() > Actual aggregation without adding dummy column should be even faster still > will allow drop_duplicates functionality until better implementation arrives -- This message was sent by Atlassian Jira (v8.20.10#820010)