chungg commented on a change in pull request #11624:
URL: https://github.com/apache/arrow/pull/11624#discussion_r750400880
##########
File path: python/pyarrow/table.pxi
##########
@@ -2192,6 +2192,83 @@ cdef class Table(_PandasConvertible):
return table
+ def group_by(self, keys, columns, aggregations):
+ """
+ Perform a group by aggregation over the columns of the table.
+
+ Parameters
+ ----------
+ keys : str or list[str]
+ Name of the columns that should be used as the grouping key.
+ columns : list of str
+ Names of the columns that contain values for the aggregations.
+ aggregations : str or list[str] or list of tuple(str, FunctionOptions)
+ Name of the hash aggregation function, or list of aggregation
+ function names or list of aggregation function names together
+ with their options.
+
+ Returns
+ -------
+ Table
+ Results of the aggregation functions.
+ """
+ if isinstance(aggregations, str):
+ aggregations = [aggregations]
+
+ if isinstance(keys, str):
+ keys = [keys]
+
+ aggrs = []
+ for aggr in aggregations:
+ if isinstance(aggr, str):
+ aggr = (aggr, None)
+ if not aggr[0].startswith("hash_"):
+ aggr = ("hash_" + aggr[0], aggr[1])
+ aggrs.append(aggr)
+
+ # Build unique names for aggregation result columns
+ # so that it's obvious what they refer to.
+ column_names = []
+ for value_name, (aggr_name, _) in zip(columns, aggrs):
+ column_names.append(aggr_name.replace("hash", value_name))
+ for key_name in keys:
+ column_names.append(key_name)
Review comment:
nit
```suggestion
# Build unique names for aggregation result columns
# so that it's obvious what they refer to.
column_names = [aggr_name.replace("hash", value_name)
for value_name, (aggr_name, _) in zip(columns,
aggrs)] + keys
```
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