Update the aggregate API to take a separate group_by (#9027)

Separate out the `Group_By` from the column definition in `aggregate`.
![image](https://github.com/enso-org/enso/assets/4699705/6b4f03bc-1c4a-4582-b38a-ba528ae94167)

Supports the old API with a warning attached about deprecation:
![image](https://github.com/enso-org/enso/assets/4699705/0cc42ff7-6047-41a5-bb99-c717d06d0d93)

Widgets have been updated with `Group_By` removed from the dropdown.

CHANGELOG.md

@@ -615,6 +615,7 @@
 - [Allow removing rows using a Filter_Condition.][8861]
 - [Added `Table.to_xml`.][8979]
 - [Implemented Write support for `S3_File`.][8921]
+- [Separate `Group_By` from `columns` into new argument on `aggregate`.][9027]
 
 [debug-shortcuts]:
   https://github.com/enso-org/enso/blob/develop/app/gui/docs/product/shortcuts.md#debug
@@ -886,6 +887,7 @@
 [8861]: https://github.com/enso-org/enso/pull/8861
 [8979]: https://github.com/enso-org/enso/pull/8979
 [8921]: https://github.com/enso-org/enso/pull/8921
+[9027]: https://github.com/enso-org/enso/pull/9027
 
 #### Enso Compiler
 

distribution/lib/Standard/Base/0.0.0-dev/src/Errors/Deprecated.enso

@@ -0,0 +1,13 @@
+import project.Data.Text.Text
+
+## A warning that an API is deprecated.
+type Deprecated
+    ## PRIVATE
+    Warning type_name:Text method_name:Text message:Text=""
+
+    ## PRIVATE
+
+       Pretty prints the Deprecated warning.
+    to_display_text : Text
+    to_display_text self =
+        if self.message.is_empty then ("Deprecated: " + self.type_name + "." + self.method_name + " is deprecated.") else self.message

distribution/lib/Standard/Database/0.0.0-dev/src/Data/Table.enso

@@ -6,6 +6,7 @@ import Standard.Base.Errors.Common.Additional_Warnings
 import Standard.Base.Errors.Common.Incomparable_Values
 import Standard.Base.Errors.Common.Index_Out_Of_Bounds
 import Standard.Base.Errors.Common.Type_Error
+import Standard.Base.Errors.Deprecated.Deprecated
 import Standard.Base.Errors.File_Error.File_Error
 import Standard.Base.Errors.Illegal_Argument.Illegal_Argument
 import Standard.Base.Errors.Illegal_State.Illegal_State
@@ -1720,10 +1721,14 @@ type Table
        GROUP Standard.Base.Calculations
        ICON sigma
 
-       Aggregates the rows in a table using any `Group_By` entries in columns.
-       The columns argument specifies which additional aggregations to perform and to return.
+       Aggregates the rows in a table using `group_by` columns.
+       The columns argument specifies which additional aggregations to perform
+       and to return.
 
        Arguments:
+       - group_by: Vector of column identifiers to group by. These will be
+         included at the start of the resulting table. If no columns are
+         specified a single row will be returned with the aggregate columns.
        - columns: Vector of `Aggregate_Column` specifying the aggregated table.
          Expressions can be used within the aggregate column to perform more
          complicated calculations.
@@ -1745,7 +1750,7 @@ type Table
          - If a column index is out of range, a `Missing_Input_Columns` is
            reported according to the `on_problems` setting, unless
            `error_on_missing_columns` is set to `True`, in which case it is
-           raised as an error. Problems resolving `Group_By` columns are
+           raised as an error. Problems resolving `group_by` columns are
            reported as dataflow errors regardless of these settings, as a
            missing grouping will completely change semantics of the query.
          - If a column selector is given as a `Text` and it does not match any
@@ -1753,7 +1758,7 @@ type Table
            `Invalid_Aggregate_Column` error is raised according to the
            `on_problems` settings (unless `error_on_missing_columns` is set to
            `True` in which case it will always be an error). Problems resolving
-           `Group_By` columns are reported as dataflow errors regardless of
+           `group_by` columns are reported as dataflow errors regardless of
            these settings, as a missing grouping will completely change
            semantics of the query.
          - If an aggregation fails, an `Invalid_Aggregation` dataflow error is
@@ -1771,63 +1776,73 @@ type Table
            - If there are more than 10 issues with a single column,
              an `Additional_Warnings`.
 
+       > Example
+         Count all the rows
+
+              table.aggregate columns=[Aggregate_Column.Count]
+
        > Example
          Group by the Key column, count the rows
 
-              table.aggregate [Aggregate_Column.Group_By "Key", Aggregate_Column.Count]
+              table.aggregate ["Key"] [Aggregate_Column.Count]
+    @group_by Widget_Helpers.make_column_name_vector_selector
     @columns Widget_Helpers.make_aggregate_column_vector_selector
-    aggregate : Vector Aggregate_Column -> Boolean -> Problem_Behavior -> Table ! No_Output_Columns | Invalid_Aggregate_Column | Invalid_Column_Names | Duplicate_Output_Column_Names | Floating_Point_Equality | Invalid_Aggregation | Unquoted_Delimiter | Additional_Warnings
-    aggregate self columns (error_on_missing_columns=False) (on_problems=Report_Warning) =
-        validated = Aggregate_Column_Helper.prepare_aggregate_columns self.column_naming_helper columns self error_on_missing_columns=error_on_missing_columns
-        key_columns = validated.key_columns
-        key_problems = key_columns.flat_map internal_column->
-            column = self.make_column internal_column
-            case column.value_type.is_floating_point of
-                True -> [Floating_Point_Equality.Error column.name]
-                False -> []
-        on_problems.attach_problems_before validated.problems+key_problems <|
-            resolved_aggregates = validated.valid_columns
-            key_expressions = key_columns.map .expression
-            new_ctx = self.context.set_groups key_expressions
-            problem_builder = Problem_Builder.new
-            ## TODO [RW] here we will perform as many fetches as there are
-               aggregate columns, but technically we could perform just one
-               fetch fetching all column types - TODO we should do that. We can
-               do it here by creating a builder that will gather all requests
-               from the executed callbacks and create Lazy references that all
-               point to a single query.
-               See #6118.
-            infer_from_database_callback expression =
-                SQL_Type_Reference.new self.connection self.context expression
-            dialect = self.connection.dialect
-            type_mapping = dialect.get_type_mapping
-            infer_return_type op_kind columns expression =
-                type_mapping.infer_return_type infer_from_database_callback op_kind columns expression
-            results = resolved_aggregates.map p->
-                agg = p.second
-                new_name = p.first
-                result = Aggregate_Helper.make_aggregate_column self agg new_name dialect infer_return_type problem_builder
-                ## If the `result` did contain an error, we catch it to be
-                   able to store it in a vector and then we will partition the
-                   created columns and failures.
-                result.catch Any error->
-                    DB_Wrapped_Error.Value error
+    aggregate : Vector (Integer | Text | Regex | Aggregate_Column) | Text | Integer | Regex -> Vector Aggregate_Column -> Boolean -> Problem_Behavior -> Table ! No_Output_Columns | Invalid_Aggregate_Column | Invalid_Column_Names | Duplicate_Output_Column_Names | Floating_Point_Equality | Invalid_Aggregation | Unquoted_Delimiter | Additional_Warnings
+    aggregate self group_by=[] columns=[] (error_on_missing_columns=False) (on_problems=Report_Warning) =
+        normalized_group_by = Vector.unify_vector_or_element group_by
+        if normalized_group_by.is_empty && columns.is_empty then Error.throw (No_Output_Columns.Error "At least one column must be specified.") else
+            validated = Aggregate_Column_Helper.prepare_aggregate_columns self.column_naming_helper normalized_group_by columns self error_on_missing_columns=error_on_missing_columns
 
-            partitioned = results.partition (_.is_a DB_Wrapped_Error)
+            key_columns = validated.key_columns
+            key_problems = key_columns.flat_map internal_column->
+                column = self.make_column internal_column
+                case column.value_type.is_floating_point of
+                    True -> [Floating_Point_Equality.Error column.name]
+                    False -> []
+            on_problems.attach_problems_before validated.problems+key_problems <|
+                resolved_aggregates = validated.valid_columns
+                key_expressions = key_columns.map .expression
+                new_ctx = self.context.set_groups key_expressions
+                problem_builder = Problem_Builder.new
+                ## TODO [RW] here we will perform as many fetches as there are
+                   aggregate columns, but technically we could perform just one
+                   fetch fetching all column types - TODO we should do that. We can
+                   do it here by creating a builder that will gather all requests
+                   from the executed callbacks and create Lazy references that all
+                   point to a single query.
+                   See #6118.
+                infer_from_database_callback expression =
+                    SQL_Type_Reference.new self.connection self.context expression
+                dialect = self.connection.dialect
+                type_mapping = dialect.get_type_mapping
+                infer_return_type op_kind columns expression =
+                    type_mapping.infer_return_type infer_from_database_callback op_kind columns expression
+                results = resolved_aggregates.map p->
+                    agg = p.second
+                    new_name = p.first
+                    result = Aggregate_Helper.make_aggregate_column self agg new_name dialect infer_return_type problem_builder
+                    ## If the `result` did contain an error, we catch it to be
+                       able to store it in a vector and then we will partition the
+                       created columns and failures.
+                    result.catch Any error->(DB_Wrapped_Error.Value error)
 
-            ## When working on join we may encounter further issues with having
-               aggregate columns exposed directly, it may be useful to re-use
-               the `lift_aggregate` method to push the aggregates into a
-               subquery.
-            new_columns = partitioned.second
-            problem_builder.attach_problems_before on_problems <|
-                problems = partitioned.first.map .value
-                on_problems.attach_problems_before problems <|
-                    handle_no_output_columns =
-                        first_problem = if problems.is_empty then Nothing else problems.first
-                        Error.throw (No_Output_Columns.Error first_problem)
-                    if new_columns.is_empty then handle_no_output_columns else
-                        self.updated_context_and_columns new_ctx new_columns subquery=True
+                partitioned = results.partition (_.is_a DB_Wrapped_Error)
+
+                ## When working on join we may encounter further issues with having
+                   aggregate columns exposed directly, it may be useful to re-use
+                   the `lift_aggregate` method to push the aggregates into a
+                   subquery.
+                new_columns = partitioned.second
+                problem_builder.attach_problems_before on_problems <|
+                    problems = partitioned.first.map .value
+                    on_problems.attach_problems_before problems <|
+                        handle_no_output_columns =
+                            first_problem = if problems.is_empty then Nothing else problems.first
+                            Error.throw (No_Output_Columns.Error first_problem)
+                        if new_columns.is_empty then handle_no_output_columns else
+                            result = self.updated_context_and_columns new_ctx new_columns subquery=True
+                            if validated.old_style.not then result else
+                                Warning.attach (Deprecated.Warning "Standard.Database.Data.Aggregate_Column.Aggregate_Column" "Group_By" "Deprecated: `Group_By` constructor has been deprecated, use the `group_by` argument instead.") result
 
     ## GROUP Standard.Base.Calculations
        ICON dataframe_map_row
@@ -1939,7 +1954,7 @@ type Table
             A  | Example | France
     @group_by Widget_Helpers.make_column_name_vector_selector
     @name_column Widget_Helpers.make_column_name_selector
-    @values (Widget_Helpers.make_aggregate_column_selector include_group_by=False)
+    @values Widget_Helpers.make_aggregate_column_selector
     cross_tab : Vector (Integer | Text | Regex | Aggregate_Column) | Text | Integer | Regex -> (Text | Integer) -> Aggregate_Column | Vector Aggregate_Column -> Problem_Behavior -> Table ! Missing_Input_Columns | Invalid_Aggregate_Column | Floating_Point_Equality | Invalid_Aggregation | Unquoted_Delimiter | Additional_Warnings | Invalid_Column_Names
     cross_tab self group_by name_column values=Aggregate_Column.Count (on_problems=Report_Warning) =
         ## Avoid unused arguments warning. We cannot rename arguments to `_`,

distribution/lib/Standard/Database/0.0.0-dev/src/Internal/IR/Context.enso

@@ -64,7 +64,7 @@ type Context
        - groups: a list of grouping expressions, for each entry a GROUP BY is
          added, the resulting query can then directly include only the
          grouped-by columns or aggregate expressions.
-       - limit: an optional maximum number of elements that the equery should
+       - limit: an optional maximum number of elements that the query should
          return.
     Value (from_spec : From_Spec) (where_filters : Vector SQL_Expression) (orders : Vector Order_Descriptor) (groups : Vector SQL_Expression) (limit : Nothing | Integer) (distinct_on : Nothing | Vector SQL_Expression)
 

distribution/lib/Standard/Database/0.0.0-dev/src/Internal/Upload_Table.enso

@@ -228,8 +228,8 @@ type Non_Unique_Key_Recipe
    Creates a `Non_Unique_Key` error containing information about an
    example group violating the uniqueness constraint.
 raise_duplicated_primary_key_error source_table primary_key original_panic =
-    agg = source_table.aggregate [Aggregate_Column.Count]+(primary_key.map Aggregate_Column.Group_By)
-    filtered = agg.filter column=0 (Filter_Condition.Greater than=1)
+    agg = source_table.aggregate primary_key [Aggregate_Column.Count]
+    filtered = agg.filter column=-1 (Filter_Condition.Greater than=1)
     materialized = filtered.read max_rows=1 warn_if_more_rows=False
     case materialized.row_count == 0 of
         ## If we couldn't find a duplicated key, we give up the translation and
@@ -239,8 +239,8 @@ raise_duplicated_primary_key_error source_table primary_key original_panic =
         True -> Panic.throw original_panic
         False ->
             row = materialized.first_row.to_vector
-            example_count = row.first
-            example_entry = row.drop 1
+            example_count = row.last
+            example_entry = row.drop (Last 1)
             Error.throw (Non_Unique_Key.Error primary_key example_entry example_count)
 
 ## PRIVATE
@@ -619,15 +619,15 @@ check_duplicate_key_matches_for_delete target_table tmp_table key_columns allow_
    Checks if any rows identified by `key_columns` have more than one match between two tables.
 check_multiple_rows_match left_table right_table key_columns ~continuation =
     joined = left_table.join right_table on=key_columns join_kind=Join_Kind.Inner
-    counted = joined.aggregate [Aggregate_Column.Count]+(key_columns.map (Aggregate_Column.Group_By _))
-    duplicates = counted.filter 0 (Filter_Condition.Greater than=1)
+    counted = joined.aggregate key_columns [Aggregate_Column.Count]
+    duplicates = counted.filter -1 (Filter_Condition.Greater than=1)
     example = duplicates.read max_rows=1 warn_if_more_rows=False
     case example.row_count == 0 of
         True -> continuation
         False ->
             row = example.first_row . to_vector
-            offending_key = row.drop 1
-            count = row.first
+            offending_key = row.drop (Last 1)
+            count = row.last
             Error.throw (Multiple_Target_Rows_Matched_For_Update.Error offending_key count)
 
 ## PRIVATE

distribution/lib/Standard/Table/0.0.0-dev/src/Data/Aggregate_Column.enso

@@ -4,11 +4,11 @@ import project.Data.Sort_Column.Sort_Column
 
 ## Defines an Aggregate Column
 type Aggregate_Column
-    ## Specifies a column to group the rows by.
+    ## PRIVATE
+       Specifies a column to group the rows by. Deprecated but used internally.
 
        Arguments:
-       - column: the column (specified by name, expression or index) to group
-         by.
+       - column: the column (either name, expression or index) to group by.
        - new_name: name of new column.
     Group_By (column:Text|Integer|Any) (new_name:Text="") # Any needed because of 6866
 

distribution/lib/Standard/Table/0.0.0-dev/src/Data/Table.enso

@@ -10,6 +10,7 @@ import Standard.Base.Errors.Common.Index_Out_Of_Bounds
 import Standard.Base.Errors.Common.No_Such_Method
 import Standard.Base.Errors.Common.Out_Of_Memory
 import Standard.Base.Errors.Common.Type_Error
+import Standard.Base.Errors.Deprecated.Deprecated
 import Standard.Base.Errors.File_Error.File_Error
 import Standard.Base.Errors.Illegal_Argument.Illegal_Argument
 import Standard.Base.Errors.Unimplemented.Unimplemented
@@ -658,10 +659,14 @@ type Table
        GROUP Standard.Base.Calculations
        ICON sigma
 
-       Aggregates the rows in a table using any `Group_By` entries in columns.
-       The columns argument specifies which additional aggregations to perform and to return.
+       Aggregates the rows in a table using `group_by` columns.
+       The columns argument specifies which additional aggregations to perform
+       and to return.
 
        Arguments:
+       - group_by: Vector of column identifiers to group by. These will be
+         included at the start of the resulting table. If no columns are
+         specified a single row will be returned with the aggregate columns.
        - columns: Vector of `Aggregate_Column` specifying the aggregated table.
          Expressions can be used within the aggregate column to perform more
          complicated calculations.
@@ -681,7 +686,7 @@ type Table
          - If a column index is out of range, a `Missing_Input_Columns` is
            reported according to the `on_problems` setting, unless
            `error_on_missing_columns` is set to `True`, in which case it is
-           raised as an error. Problems resolving `Group_By` columns are
+           raised as an error. Problems resolving `group_by` columns are
            reported as dataflow errors regardless of these settings, as a
            missing grouping will completely change semantics of the query.
          - If a column selector is given as a `Text` and it does not match any
@@ -689,7 +694,7 @@ type Table
            `Invalid_Aggregate_Column` problem is raised according to the
            `on_problems` settings (unless `error_on_missing_columns` is set to
            `True` in which case it will always be an error). Problems resolving
-           `Group_By` columns are reported as dataflow errors regardless of
+           `group_by` columns are reported as dataflow errors regardless of
            these settings, as a missing grouping will completely change
            semantics of the query.
          - If an aggregation fails, an `Invalid_Aggregation` dataflow error is
@@ -707,22 +712,31 @@ type Table
            - If there are more than 10 issues with a single column,
              an `Additional_Warnings`.
 
+       > Example
+         Count all the rows
+
+              table.aggregate columns=[Aggregate_Column.Count]
+
        > Example
          Group by the Key column, count the rows
 
-              table.aggregate [Aggregate_Column.Group_By "Key", Aggregate_Column.Count]
+              table.aggregate ["Key"] [Aggregate_Column.Count]
+    @group_by Widget_Helpers.make_column_name_vector_selector
     @columns Widget_Helpers.make_aggregate_column_vector_selector
-    aggregate : Vector Aggregate_Column -> Boolean -> Problem_Behavior -> Table ! No_Output_Columns | Invalid_Aggregate_Column | Invalid_Column_Names | Duplicate_Output_Column_Names | Floating_Point_Equality | Invalid_Aggregation | Unquoted_Delimiter | Additional_Warnings
-    aggregate self columns (error_on_missing_columns=False) (on_problems=Report_Warning) =
-        validated = Aggregate_Column_Helper.prepare_aggregate_columns self.column_naming_helper columns self error_on_missing_columns=error_on_missing_columns
+    aggregate : Vector (Integer | Text | Regex | Aggregate_Column) | Text | Integer | Regex -> Vector Aggregate_Column -> Boolean -> Problem_Behavior -> Table ! No_Output_Columns | Invalid_Aggregate_Column | Invalid_Column_Names | Duplicate_Output_Column_Names | Floating_Point_Equality | Invalid_Aggregation | Unquoted_Delimiter | Additional_Warnings
+    aggregate self group_by=[] columns=[] (error_on_missing_columns=False) (on_problems=Report_Warning) =
+        normalized_group_by = Vector.unify_vector_or_element group_by
+        if normalized_group_by.is_empty && columns.is_empty then Error.throw (No_Output_Columns.Error "At least one column must be specified.") else
+            validated = Aggregate_Column_Helper.prepare_aggregate_columns self.column_naming_helper normalized_group_by columns self error_on_missing_columns=error_on_missing_columns
 
-        on_problems.attach_problems_before validated.problems <| Illegal_Argument.handle_java_exception <|
-            java_key_columns = validated.key_columns.map .java_column
-            Java_Problems.with_problem_aggregator on_problems java_problem_aggregator->
-                index = self.java_table.indexFromColumns java_key_columns java_problem_aggregator
-                new_columns = validated.valid_columns.map c->(Aggregate_Column_Helper.java_aggregator c.first c.second)
-                java_table = index.makeTable new_columns
-                Table.Value java_table
+            on_problems.attach_problems_before validated.problems <| Illegal_Argument.handle_java_exception <|
+                java_key_columns = validated.key_columns.map .java_column
+                Java_Problems.with_problem_aggregator on_problems java_problem_aggregator->
+                    index = self.java_table.indexFromColumns java_key_columns java_problem_aggregator
+                    new_columns = validated.valid_columns.map c->(Aggregate_Column_Helper.java_aggregator c.first c.second)
+                    java_table = index.makeTable new_columns
+                    if validated.old_style.not then Table.Value java_table else
+                        Warning.attach (Deprecated.Warning "Standard.Database.Data.Aggregate_Column.Aggregate_Column" "Group_By" "Deprecated: `Group_By` constructor has been deprecated, use the `group_by` argument instead.") (Table.Value java_table)
 
     ## ALIAS sort
        GROUP Standard.Base.Selections
@@ -2448,7 +2462,7 @@ type Table
             A  | Example | France
     @group_by Widget_Helpers.make_column_name_vector_selector
     @name_column Widget_Helpers.make_column_name_selector
-    @values (Widget_Helpers.make_aggregate_column_selector include_group_by=False)
+    @values Widget_Helpers.make_aggregate_column_selector
     cross_tab : Vector (Integer | Text | Regex | Aggregate_Column) | Text | Integer | Regex -> (Text | Integer) -> Aggregate_Column | Vector Aggregate_Column -> Problem_Behavior -> Table ! Missing_Input_Columns | Invalid_Aggregate_Column | Floating_Point_Equality | Invalid_Aggregation | Unquoted_Delimiter | Additional_Warnings | Invalid_Column_Names
     cross_tab self group_by name_column values=Aggregate_Column.Count (on_problems=Report_Warning) = Out_Of_Memory.handle_java_exception "cross_tab" <|
         columns_helper = self.columns_helper

distribution/lib/Standard/Table/0.0.0-dev/src/Internal/Aggregate_Column_Helper.enso

@@ -1,5 +1,6 @@
 from Standard.Base import all hiding First, Last
 import Standard.Base.Data.Vector.No_Wrap
+import Standard.Base.Errors.Illegal_Argument.Illegal_Argument
 from Standard.Base.Runtime import assert
 
 import project.Data.Aggregate_Column.Aggregate_Column
@@ -31,69 +32,76 @@ polyglot java import org.enso.table.aggregations.StandardDeviation as StandardDe
 polyglot java import org.enso.table.aggregations.Sum as SumAggregator
 
 ## Result type for aggregate_columns validation
-   - key_columns: Vector of Columns from the table to group by
-   - valid_columns: Table structure to build as pairs of unique column name and Aggregate_Column
-   - problems: Set of any problems when validating the input
+   - key_columns: Vector of Columns from the table to group by.
+   - valid_columns: Table structure to build as pairs of unique column name and Aggregate_Column.
+   - problems: Set of any problems when validating the input.
+   - old_style: Boolean indicating if the input was in the old style.
 type Validated_Aggregate_Columns
     ## PRIVATE
-    Value (key_columns:(Vector Column)) (valid_columns:(Vector (Pair Text Aggregate_Column))) (problems:(Vector Any))
+    Value (key_columns:(Vector Column)) (valid_columns:(Vector (Pair Text Aggregate_Column))) (problems:(Vector Any)) (old_style:Boolean)
 
 ## PRIVATE
    Prepares an aggregation input for further processing:
    - resolves the column descriptors, reporting any issues,
    - ensures that the output names are unique,
    - finds the key columns.
-prepare_aggregate_columns : Column_Naming_Helper -> Vector Aggregate_Column -> Table -> Boolean -> Validated_Aggregate_Columns
-prepare_aggregate_columns naming_helper aggregates table error_on_missing_columns =
+prepare_aggregate_columns : Column_Naming_Helper -> Vector (Integer | Text | Regex | Aggregate_Column) | Text | Integer | Regex -> Vector Aggregate_Column -> Table -> Boolean -> Validated_Aggregate_Columns
+prepare_aggregate_columns naming_helper group_by aggregates table error_on_missing_columns =
     is_a_key c = case c of
         Aggregate_Column.Group_By _ _ -> True
         _ -> False
 
-    keys = aggregates.filter is_a_key
-    # Key resolution always errors on missing, regardless of any settings.
-    keys_problem_builder = Problem_Builder.new error_on_missing_columns=True
-    resolved_keys = keys.map (resolve_aggregate table keys_problem_builder)
+    ## Resolve old style aggregate into new style
+    old_style = aggregates.is_empty && group_by.any (g-> g.is_a Aggregate_Column)
+    if old_style.not && group_by.any is_a_key then Error.throw (Invalid_Aggregation.Error "`columns` should not contain a `Group_By`.") else
+        keys = if old_style then group_by.filter is_a_key else group_by.map (Aggregate_Column.Group_By _ "")
 
-    ## Since `keys_problem_builder` has `error_on_missing_columns` set to `True`,
-       any missing columns will be reported as errors. Therefore, we can assume
-       that all the columns were present.
-    keys_problem_builder.attach_problems_before Problem_Behavior.Report_Error <|
-        assert (resolved_keys.contains Nothing . not)
-        problem_builder = Problem_Builder.new error_on_missing_columns=error_on_missing_columns
-        valid_resolved_aggregate_columns = aggregates.map on_problems=No_Wrap (resolve_aggregate table problem_builder) . filter x-> x.is_nothing.not
+        # Key resolution always errors on missing, regardless of any settings.
+        keys_problem_builder = Problem_Builder.new error_on_missing_columns=True
+        resolved_keys = keys.map (resolve_aggregate table keys_problem_builder)
 
-        # Grouping Key
-        key_columns = resolved_keys.map .column
-        unique_key_columns = key_columns.distinct (on = .name)
+        ## Since `keys_problem_builder` has `error_on_missing_columns` set to `True`,
+           any missing columns will be reported as errors. Therefore, we can assume
+           that all the columns were present.
+        keys_problem_builder.attach_problems_before Problem_Behavior.Report_Error <|
+            assert (resolved_keys.contains Nothing . not)
+            problem_builder = Problem_Builder.new error_on_missing_columns=error_on_missing_columns
+            columns = if old_style then group_by else keys+aggregates
+            valid_resolved_aggregate_columns = columns.map on_problems=No_Wrap (resolve_aggregate table problem_builder) . filter x-> x.is_nothing.not
 
-        # Resolve Names
-        unique = naming_helper.create_unique_name_strategy
-        ## First pass ensures the custom names specified by the user are unique.
-           The second pass resolves the default names, ensuring that they do not
-           clash with the user-specified names (ensuring that user-specified names
-           take precedence).
-        pass_1 = valid_resolved_aggregate_columns.map on_problems=No_Wrap c-> if c.new_name == "" then "" else
-            # Verify if the user-provided name is valid and if not, throw an error.
-            naming_helper.ensure_name_is_valid c.new_name <|
-                unique.make_unique c.new_name
-        renamed_columns = pass_1.map_with_index i->name->
-            agg = valid_resolved_aggregate_columns.at i
-            new_name = if name != "" then name else unique.make_unique (default_aggregate_column_name agg)
-            Pair.new new_name agg
+            # Grouping Key
+            key_columns = resolved_keys.map .column
+            unique_key_columns = key_columns.distinct (on = .name)
 
-        # Build Problems Output
-        case renamed_columns.is_empty of
-            True ->
-                ## First, we try to raise any warnings that may have caused the
-                   lack of columns, promoted to errors.
-                problem_builder.attach_problems_before Problem_Behavior.Report_Error <|
-                    ## If none were found, we raise a generic error (this may
-                       happen primarily when an empty list is provided to the
-                       aggregate method).
-                    Error.throw No_Output_Columns.Error
-            False ->
-                problem_builder.report_unique_name_strategy unique
-                Validated_Aggregate_Columns.Value unique_key_columns renamed_columns problem_builder.get_problemset_throwing_distinguished_errors
+            # Resolve Names
+            unique = naming_helper.create_unique_name_strategy
+
+            ## First pass ensures the custom names specified by the user are unique.
+               The second pass resolves the default names, ensuring that they do not
+               clash with the user-specified names (ensuring that user-specified names
+               take precedence).
+            pass_1 = valid_resolved_aggregate_columns.map on_problems=No_Wrap c-> if c.new_name == "" then "" else
+                # Verify if the user-provided name is valid and if not, throw an error.
+                naming_helper.ensure_name_is_valid c.new_name <|
+                    unique.make_unique c.new_name
+            renamed_columns = pass_1.map_with_index i->name->
+                agg = valid_resolved_aggregate_columns.at i
+                new_name = if name != "" then name else unique.make_unique (default_aggregate_column_name agg)
+                Pair.new new_name agg
+
+            # Build Problems Output
+            case renamed_columns.is_empty of
+                True ->
+                    ## First, we try to raise any warnings that may have caused the
+                       lack of columns, promoted to errors.
+                    problem_builder.attach_problems_before Problem_Behavior.Report_Error <|
+                        ## If none were found, we raise a generic error (this may
+                           happen primarily when an empty list is provided to the
+                           aggregate method).
+                        Error.throw No_Output_Columns.Error
+                False ->
+                    problem_builder.report_unique_name_strategy unique
+                    Validated_Aggregate_Columns.Value unique_key_columns renamed_columns problem_builder.get_problemset_throwing_distinguished_errors old_style
 
 ## PRIVATE
    Defines the default name of an `Aggregate_Column`.

distribution/lib/Standard/Table/0.0.0-dev/src/Internal/Table_Helpers.enso

@@ -230,7 +230,7 @@ type Table_Column_Helper
             Blank_Selector.All_Cells -> Aggregate_Column.Minimum _
         aggregates = blanks.map blanks_col-> col_aggregate blanks_col.name
 
-        aggregate_result = just_indicators.aggregate aggregates on_problems=Problem_Behavior.Report_Error
+        aggregate_result = just_indicators.aggregate columns=aggregates on_problems=Problem_Behavior.Report_Error
         materialized_result = self.materialize <| aggregate_result.catch Any error->
             msg = "Unexpected dataflow error has been thrown in an `select_blank_columns_helper`. This is a bug in the Table library. The unexpected error was: "+error.to_display_text
             Panic.throw (Illegal_State.Error message=msg cause=error)

distribution/lib/Standard/Table/0.0.0-dev/src/Internal/Widget_Helpers.enso

@@ -16,13 +16,12 @@ from project.Extensions.Table_Conversions import all
 
 ## PRIVATE
    Make an aggregate column selector.
-make_aggregate_column_selector : Table -> Display -> Boolean -> Widget
-make_aggregate_column_selector table display=Display.Always include_group_by=True =
+make_aggregate_column_selector : Table -> Display -> Widget
+make_aggregate_column_selector table display=Display.Always =
     col_names_selector = make_column_name_selector table display=Display.Always
     column_widget = ["column", col_names_selector]
 
     fqn = Meta.get_qualified_type_name Aggregate_Column
-    group_by = if include_group_by then [Option "Group By" fqn+".Group_By" [column_widget]] else []
     count = Option "Count" fqn+".Count"
 
     ## Currently can't support nested vector editors so using single picker
@@ -56,7 +55,7 @@ make_aggregate_column_selector table display=Display.Always include_group_by=Tru
     maximum = Option "Maximum" fqn+".Maximum" [column_widget]
     minimum = Option "Minimum" fqn+".Minimum" [column_widget]
 
-    Single_Choice display=display values=(group_by+[count, count_distinct, first, last, count_not_nothing, count_nothing, count_not_empty, count_empty, concatenate, shortest, longest, sum, average, median, percentile, mode, standard_deviation, maximum, minimum])
+    Single_Choice display=display values=[count, count_distinct, first, last, count_not_nothing, count_nothing, count_not_empty, count_empty, concatenate, shortest, longest, sum, average, median, percentile, mode, standard_deviation, maximum, minimum]
 
 ## PRIVATE
    Make an Aggregate_Column list editor
@@ -64,7 +63,7 @@ make_aggregate_column_vector_selector : Table -> Display -> Widget
 make_aggregate_column_vector_selector table display=Display.Always =
     item_editor = make_aggregate_column_selector table display=Display.Always
     # TODO this is a workaround for a dropdown issue
-    Vector_Editor item_editor=item_editor item_default="(Aggregate_Column.Group_By)" display=display
+    Vector_Editor item_editor=item_editor item_default="(Aggregate_Column.Count)" display=display
 
 ## PRIVATE
    Make a column name selector.

distribution/lib/Standard/Visualization/0.0.0-dev/src/AI.enso

@@ -10,13 +10,13 @@ Table.build_ai_prompt self =
     aggs = ["Count","Average","Sum","Median","First","Last","Maximum","Minimum"]
     joins = ["Inner","Left_Outer","Right_Outer","Full","Left_Exclusive","Right_Exclusive"]
     examples = """
-        Table["id","category","Unit Price","Stock"];goal=get product count by category==>>`aggregate [Aggregate_Column.Group_By "category", Aggregate_Column.Count Nothing]`
+        Table["id","category","Unit Price","Stock"];goal=get product count by category==>>`aggregate ["category"] [Aggregate_Column.Count]`
         Table["ID","Unit Price","Stock"];goal=order by how many items are available==>>`order_by ["Stock"]`
         Table["Name","Enrolled Year"];goal=select people who enrolled between 2015 and 2018==>>`filter_by_expression "[Enrolled Year] >= 2015 && [Enrolled Year] <= 2018`
         Table["Number of items","client name","city","unit price"];goal=compute the total value of each order==>>`set "[Number of items] * [unit price]" "total value"`
-        Table["Number of items","client name","CITY","unit price","total value"];goal=compute the average order value by city==>>`aggregate [Aggregate_Column.Group_By "CITY", Aggregate_Column.Average "total value"]`
+        Table["Number of items","client name","CITY","unit price","total value"];goal=compute the average order value by city==>>`aggregate ["CITY"] [Aggregate_Column.Average "total value"]`
         Table["Area Code", "number"];goal=get full phone numbers==>>`set "'+1 (' + [Area Code] + ') ' + [number]" "full phone number"`
-        Table["Name","Grade","Subject"];goal=rank students by their average grade==>>`aggregate [Aggregate_Column.Group_By "Name", Aggregate_Column.Average "Grade" "Average Grade"] . order_by [Sort_Column.Name "Average Grade" Sort_Direction.Descending]`
+        Table["Name","Grade","Subject"];goal=rank students by their average grade==>>`aggregate ["Name"] [Aggregate_Column.Average "Grade" "Average Grade"] . order_by [Sort_Column.Name "Average Grade" Sort_Direction.Descending]`
         Table["Country","Prime minister name","2018","2019","2020","2021"];goal=pivot yearly GDP values to rows==>>`transpose ["Country", "Prime minister name"] "Year" "GDP"`
         Table["Size","Weight","Width","stuff","thing"];goal=only select size and thing of each record==>>`select_columns ["Size", "thing"]`
         Table["ID","Name","Count"];goal=join it with var_17==>>`join var_17 Join_Kind.Inner`

test/Benchmarks/src/Table/Add_Row_Number.enso

@@ -48,6 +48,6 @@ collect_benches = Bench.build builder->
             group_builder.specify "Sort_Table" <|
                 data.table.order_by "X"
             group_builder.specify "Group_And_Sort" <|
-                data.table.aggregate [Aggregate_Column.Group_By "X", Aggregate_Column.Last "Y" order_by="Y"]
+                data.table.aggregate ["X"] [Aggregate_Column.Last "Y" order_by="Y"]
 
 main = collect_benches . run_main

test/Benchmarks/src/Table/Aggregate.enso

@@ -1,7 +1,6 @@
 from Standard.Base import all hiding First, Last
 
-from Standard.Table import Table
-from Standard.Table.Data.Aggregate_Column.Aggregate_Column import all
+from Standard.Table import Table, Aggregate_Column
 
 from Standard.Test import Bench, Faker
 
@@ -34,67 +33,67 @@ collect_benches = Bench.build builder->
 
     builder.group "Table_Aggregate" options group_builder->
         group_builder.specify "Count_table" <|
-            data.table.aggregate [Count]
+            data.table.aggregate [Aggregate_Column.Count]
 
         group_builder.specify "Max_table" <|
-            data.table.aggregate [Maximum "ValueWithNothing"]
+            data.table.aggregate [Aggregate_Column.Maximum "ValueWithNothing"]
 
         group_builder.specify "Sum_table" <|
-            data.table.aggregate [Sum "ValueWithNothing"]
+            data.table.aggregate [Aggregate_Column.Sum "ValueWithNothing"]
 
         group_builder.specify "Count_Distinct_table" <|
-            data.table.aggregate [Count_Distinct "Index"]
+            data.table.aggregate [Aggregate_Column.Count_Distinct "Index"]
 
         group_builder.specify "StDev_table" <|
-            data.table.aggregate [Standard_Deviation "Value"]
+            data.table.aggregate [Aggregate_Column.Standard_Deviation "Value"]
 
         group_builder.specify "Median_table" <|
-            data.table.aggregate [Median "Value"]
+            data.table.aggregate [Aggregate_Column.Median "Value"]
 
         group_builder.specify "Mode_table" <|
-            data.table.aggregate [Mode "Index"]
+            data.table.aggregate [Aggregate_Column.Mode "Index"]
 
         group_builder.specify "Count_grouped" <|
-            data.table.aggregate [Group_By "Index", Count]
+            data.table.aggregate ["Index"] [Aggregate_Column.Count]
 
         group_builder.specify "Max_grouped" <|
-            data.table.aggregate [Group_By "Index", Maximum "ValueWithNothing"]
+            data.table.aggregate ["Index"] [Aggregate_Column.Maximum "ValueWithNothing"]
 
         group_builder.specify "Sum_grouped" <|
-            data.table.aggregate [Group_By "Index", Sum "ValueWithNothing"]
+            data.table.aggregate ["Index"] [Aggregate_Column.Sum "ValueWithNothing"]
 
         group_builder.specify "Count_Distinct_grouped" <|
-            data.table.aggregate [Group_By "Index", Count_Distinct "Code"]
+            data.table.aggregate ["Index"] [Aggregate_Column.Count_Distinct "Code"]
 
         group_builder.specify "StDev_grouped" <|
-            data.table.aggregate [Group_By "Index", Standard_Deviation "Value"]
+            data.table.aggregate ["Index"] [Aggregate_Column.Standard_Deviation "Value"]
 
         group_builder.specify "Median_grouped" <|
-            data.table.aggregate [Group_By "Index", Median "Value"]
+            data.table.aggregate ["Index"] [Aggregate_Column.Median "Value"]
 
         group_builder.specify "Mode_grouped" <|
-            data.table.aggregate [Group_By "Index", Mode "Index"]
+            data.table.aggregate ["Index"] [Aggregate_Column.Mode "Index"]
 
         group_builder.specify "Count_2_level_groups" <|
-            data.table.aggregate [Group_By "Index", Group_By "Flag", Count]
+            data.table.aggregate ["Index", "Flag"] [Aggregate_Column.Count]
 
         group_builder.specify "Max_2_level_groups" <|
-            data.table.aggregate [Group_By "Index", Group_By "Flag", Maximum "ValueWithNothing"]
+            data.table.aggregate ["Index", "Flag"] [Aggregate_Column.Maximum "ValueWithNothing"]
 
         group_builder.specify "Sum_2_level_groups" <|
-            data.table.aggregate [Group_By "Index", Group_By "Flag", Sum "ValueWithNothing"]
+            data.table.aggregate ["Index", "Flag"] [Aggregate_Column.Sum "ValueWithNothing"]
 
         group_builder.specify "Count_Distinct_2_level_groups" <|
-            data.table.aggregate [Group_By "Index", Group_By "Flag", Count_Distinct "Code"]
+            data.table.aggregate ["Index", "Flag"] [Aggregate_Column.Count_Distinct "Code"]
 
         group_builder.specify "StDev_2_level_groups" <|
-            data.table.aggregate [Group_By "Index", Group_By "Flag", Standard_Deviation "Value"]
+            data.table.aggregate ["Index", "Flag"] [Aggregate_Column.Standard_Deviation "Value"]
 
         group_builder.specify "Median_2_level_groups" <|
-            data.table.aggregate [Group_By "Index", Group_By "Flag", Median "Value"]
+            data.table.aggregate ["Index", "Flag"] [Aggregate_Column.Median "Value"]
 
         group_builder.specify "Mode_2_level_groups" <|
-            data.table.aggregate [Group_By "Index", Group_By "Flag", Mode "Index"]
+            data.table.aggregate ["Index", "Flag"] [Aggregate_Column.Mode "Index"]
 
 
 main = collect_benches . run_main

test/Benchmarks/src/Table/Cross_Tab.enso

@@ -1,7 +1,6 @@
 from Standard.Base import all
 
-from Standard.Table import Table
-from Standard.Table.Data.Aggregate_Column.Aggregate_Column import Count, Sum
+from Standard.Table import Table, Aggregate_Column
 
 from Standard.Test import Bench, Faker
 
@@ -42,7 +41,7 @@ collect_benches = Bench.build builder->
         data = Data.create num_rows
 
         builder.group ("CrossTab_" + num_rows.to_text) options group_builder->
-            specify group_by name_column values=[Count] =
+            specify group_by name_column values=[Aggregate_Column.Count] =
                 name = (group_by.join '_') + "_" + name_column + "_" + (values.map .to_text . join "_")
                 group_builder.specify (normalize_name name) <|
                     data.table.cross_tab group_by name_column values
@@ -53,7 +52,7 @@ collect_benches = Bench.build builder->
             specify ["type"] "size"
             specify ["store"] "size"
             specify ["size"] "store"
-            specify ["size"] "store" values=[Count, Sum "price"]
+            specify ["size"] "store" values=[Aggregate_Column.Count, Aggregate_Column.Sum "price"]
 
 
 normalize_name : Text -> Text

test/Exploratory_Benchmarks/src/Table/Column_Aggregate.enso

@@ -14,7 +14,7 @@ type Boxed_Total_Aggregate
     Instance text_column
 
     current_aggregate_implementation self =
-        self.text_column.to_table.aggregate [Aggregate_Column.Longest 0] . at 0 . at 0
+        self.text_column.to_table.aggregate [] [Aggregate_Column.Longest 0] . at 0 . at 0
 
     java_loop self =
         SimpleStorageAggregateHelpers.longestText self.text_column.java_column.getStorage
@@ -46,7 +46,7 @@ type Primitive_Total_Aggregate
     Instance int_column
 
     current_aggregate_implementation self =
-        self.int_column.to_table.aggregate [Aggregate_Column.Sum 0] . at 0 . at 0
+        self.int_column.to_table.aggregate [] [Aggregate_Column.Sum 0] . at 0 . at 0
 
     java_loop self =
         long_storage = self.int_column.java_column.getStorage

test/Table_Tests/src/Common_Table_Operations/Add_Row_Number_Spec.enso

@@ -4,8 +4,7 @@ import Standard.Base.Errors.Illegal_Argument.Illegal_Argument
 import Standard.Database.Extensions.Upload_Database_Table
 import Standard.Database.Extensions.Upload_In_Memory_Table
 
-from Standard.Table import Sort_Column
-from Standard.Table.Data.Aggregate_Column.Aggregate_Column import Group_By, Sum
+from Standard.Table import Sort_Column, Aggregate_Column
 from Standard.Table.Errors import Missing_Input_Columns, Duplicate_Output_Column_Names, Floating_Point_Equality
 
 from Standard.Test import all
@@ -118,7 +117,7 @@ add_specs suite_builder setup =
 
         group_builder.specify "Should work correctly after aggregation" <|
             t0 = table_builder [["X", ["a", "b", "a", "c"]], ["Y", [1, 2, 4, 8]]]
-            t1 = t0.aggregate [Group_By "X", Sum "Y"]
+            t1 = t0.aggregate ["X"] [Aggregate_Column.Sum "Y"]
 
             t2 = t1.order_by "X" . add_row_number
             t2.at "X" . to_vector . should_equal ['a', 'b', 'c']

test/Table_Tests/src/Common_Table_Operations/Column_Name_Edge_Cases_Spec.enso

@@ -89,7 +89,7 @@ add_specs suite_builder setup =
 
         group_builder.specify "case insensitive name collisions - aggregate" <|
             t1 = table_builder [["X", [2, 1, 3, 2]]]
-            t2 = t1.aggregate [Aggregate_Column.Maximum "X" "A", Aggregate_Column.Minimum "X" "a"]
+            t2 = t1.aggregate columns=[Aggregate_Column.Maximum "X" "A", Aggregate_Column.Minimum "X" "a"]
 
             case is_case_sensitive of
                 True ->

test/Table_Tests/src/Common_Table_Operations/Cross_Tab_Spec.enso

@@ -1,7 +1,7 @@
 from Standard.Base import all
 import Standard.Base.Errors.Illegal_Argument.Illegal_Argument
 
-from Standard.Table.Data.Aggregate_Column.Aggregate_Column import Average, Count, Group_By, Sum, Concatenate
+from Standard.Table import Aggregate_Column
 import Standard.Table.Data.Expression.Expression_Error
 from Standard.Table.Errors import all
 
@@ -53,7 +53,7 @@ add_specs suite_builder setup =
             t1.at "z" . to_vector . should_equal [2]
 
         group_builder.specify "should allow a different aggregate" <|
-            t1 = data.table.cross_tab [] "Key" values=[Sum "Value"]
+            t1 = data.table.cross_tab [] "Key" values=[Aggregate_Column.Sum "Value"]
             t1.column_names . should_equal ["x", "y", "z"]
             t1.row_count . should_equal 1
             t1.at "x" . to_vector . should_equal [10]
@@ -61,7 +61,7 @@ add_specs suite_builder setup =
             t1.at "z" . to_vector . should_equal [17]
 
         group_builder.specify "should allow a custom expression for the aggregate" <|
-            t1 = data.table.cross_tab [] "Key" values=[Sum "[Value]*[Value]"]
+            t1 = data.table.cross_tab [] "Key" values=[Aggregate_Column.Sum "[Value]*[Value]"]
             t1.column_names . should_equal ["x", "y", "z"]
             t1.row_count . should_equal 1
             t1.at "x" . to_vector . should_equal [30]
@@ -94,7 +94,7 @@ add_specs suite_builder setup =
             t1.at "z" . to_vector . should_equal [1, 1]
 
         group_builder.specify "should allow a grouping by Aggregate_Column" <|
-            t1 = data.table2.cross_tab [Group_By "Group"] "Key"
+            t1 = data.table2.cross_tab [Aggregate_Column.Group_By "Group"] "Key"
             t1.column_names . should_equal ["Group", "x", "y", "z"]
             t1.row_count . should_equal 2
             t1.at "Group" . to_vector . should_equal ["A", "B"]
@@ -102,11 +102,11 @@ add_specs suite_builder setup =
             t1.at "y" . to_vector . should_equal [2, 1]
             t1.at "z" . to_vector . should_equal [1, 1]
 
-            data.table2.cross_tab [Sum "Group"] "Key" . should_fail_with Illegal_Argument
+            data.table2.cross_tab [Aggregate_Column.Sum "Group"] "Key" . should_fail_with Illegal_Argument
 
         group_builder.specify "should allow a grouping by Aggregate_Colum, with some empty bins" <|
             table3 = table_builder [["Group", ["B","A","B","A","A"]], ["Key", ["x", "y", "y", "y", "z"]], ["Value", [4, 5, 6, 7, 8]]]
-            t1 = table3.cross_tab [Group_By "Group"] "Key"
+            t1 = table3.cross_tab [Aggregate_Column.Group_By "Group"] "Key"
             t1.column_names . should_equal ["Group", "x", "y", "z"]
             t1.row_count . should_equal 2
             t1.at "Group" . to_vector . should_equal ["A", "B"]
@@ -127,7 +127,7 @@ add_specs suite_builder setup =
             t2.column_names . should_equal ["Group", "x", "y", "z"]
 
         group_builder.specify "should allow multiple values aggregates" <|
-            t1 = data.table.cross_tab [] "Key" values=[Count, Sum "Value"]
+            t1 = data.table.cross_tab [] "Key" values=[Aggregate_Column.Count, Aggregate_Column.Sum "Value"]
             t1.column_names . should_equal ["x Count", "x Sum", "y Count", "y Sum", "z Count", "z Sum"]
             t1.row_count . should_equal 1
             t1.at "x Count" . to_vector . should_equal [4]
@@ -156,31 +156,31 @@ add_specs suite_builder setup =
             err2.catch.criteria . should_equal [42]
 
         group_builder.specify "should fail if aggregate values contain missing columns" <|
-            err1 = data.table.cross_tab [] "Key" values=[Count, Sum "Nonexistent Value", Sum "Value", Sum "OTHER"]
+            err1 = data.table.cross_tab [] "Key" values=[Aggregate_Column.Count, Aggregate_Column.Sum "Nonexistent Value", Aggregate_Column.Sum "Value", Aggregate_Column.Sum "OTHER"]
             err1.should_fail_with Invalid_Aggregate_Column
             err1.catch.name . should_equal "Nonexistent Value"
 
-            err2 = data.table.cross_tab [] "Key" values=[Count, Sum "Nonexistent Value", Sum "Value", Sum 42]
+            err2 = data.table.cross_tab [] "Key" values=[Aggregate_Column.Count, Aggregate_Column.Sum "Nonexistent Value", Aggregate_Column.Sum "Value", Aggregate_Column.Sum 42]
             err2.should_fail_with Missing_Input_Columns
             err2.catch.criteria . should_equal [42]
 
         group_builder.specify "should fail if aggregate values contain invalid expressions" <|
-            err1 = data.table.cross_tab [] "Key" values=[Sum "[MISSING]*10"]
+            err1 = data.table.cross_tab [] "Key" values=[Aggregate_Column.Sum "[MISSING]*10"]
             err1.should_fail_with Invalid_Aggregate_Column
             err1.catch.name . should_equal "[MISSING]*10"
             err1.catch.expression_error . should_equal (No_Such_Column.Error "MISSING")
 
-            err2 = data.table.cross_tab [] "Key" values=[Sum "[[["]
+            err2 = data.table.cross_tab [] "Key" values=[Aggregate_Column.Sum "[[["]
             err2.should_fail_with Invalid_Aggregate_Column
             err2.catch.name . should_equal "[[["
             err2.catch.expression_error . should_be_a Expression_Error.Syntax_Error
 
         group_builder.specify "should not allow Group_By for values" <|
-            err1 = data.table.cross_tab [] "Key" values=[Count, Group_By "Value"] on_problems=Problem_Behavior.Ignore
+            err1 = data.table.cross_tab [] "Key" values=[Aggregate_Column.Count, Aggregate_Column.Group_By "Value"] on_problems=Problem_Behavior.Ignore
             err1.should_fail_with Illegal_Argument
 
         group_builder.specify "should gracefully handle duplicate aggregate names" <|
-            action = data.table.cross_tab [] "Key" values=[Count new_name="Agg1", Sum "Value" new_name="Agg1"] on_problems=_
+            action = data.table.cross_tab [] "Key" values=[Aggregate_Column.Count new_name="Agg1", Aggregate_Column.Sum "Value" new_name="Agg1"] on_problems=_
             tester table =
                 table.column_names . should_equal ["x Agg1", "x Agg1 1", "y Agg1", "y Agg1 1", "z Agg1", "z Agg1 1"]
             problems = [Duplicate_Output_Column_Names.Error ["x Agg1", "y Agg1", "z Agg1"]]
@@ -235,11 +235,11 @@ add_specs suite_builder setup =
             t = table_builder [["Key", ["a", "a", "b", "b"]], ["ints", [1, 2, 3, 4]], ["texts", ["a", "b", "c", "d"]]]
 
             [Problem_Behavior.Report_Error, Problem_Behavior.Report_Warning, Problem_Behavior.Ignore].each pb-> Test.with_clue "Problem_Behavior="+pb.to_text+" " <|
-                t1 = t.cross_tab [] "Key" values=[Average "texts"] on_problems=pb
+                t1 = t.cross_tab [] "Key" values=[Aggregate_Column.Average "texts"] on_problems=pb
                 t1.should_fail_with Invalid_Value_Type
-                t2 = t.cross_tab [] "Key" values=[Sum "texts"] on_problems=pb
+                t2 = t.cross_tab [] "Key" values=[Aggregate_Column.Sum "texts"] on_problems=pb
                 t2.should_fail_with Invalid_Value_Type
-                t3 = t.cross_tab [] "Key" values=[Concatenate "ints"] on_problems=pb
+                t3 = t.cross_tab [] "Key" values=[Aggregate_Column.Concatenate "ints"] on_problems=pb
                 t3.should_fail_with Invalid_Value_Type
 
         group_builder.specify "should return predictable types" <|
@@ -250,7 +250,7 @@ add_specs suite_builder setup =
             t1.at "a" . value_type . is_integer . should_be_true
             t1.at "b" . value_type . is_integer . should_be_true
 
-            t2 = table.cross_tab [] "Int" values=[Average "Float", Concatenate "Text"] . sort_columns
+            t2 = table.cross_tab [] "Int" values=[Aggregate_Column.Average "Float", Aggregate_Column.Concatenate "Text"] . sort_columns
             t2.column_names . should_equal ["1 Average Float", "1 Concatenate Text", "2 Average Float", "2 Concatenate Text"]
             t2.at "1 Average Float" . value_type . is_floating_point . should_be_true
             t2.at "1 Concatenate Text" . value_type . is_text . should_be_true
@@ -263,7 +263,7 @@ add_specs suite_builder setup =
             r1.should_fail_with Invalid_Column_Names
             r1.catch.to_display_text . should_contain "cannot contain the NUL character"
 
-            r2 = data.table2.cross_tab [] "Key" values=[Average "Value" new_name='x\0']
+            r2 = data.table2.cross_tab [] "Key" values=[Aggregate_Column.Average "Value" new_name='x\0']
             r2.print
             r2.should_fail_with Invalid_Column_Names
             r2.catch.to_display_text . should_contain "cannot contain the NUL character"

test/Table_Tests/src/Common_Table_Operations/Integration_Tests.enso

@@ -2,7 +2,6 @@ from Standard.Base import all
 
 # We hide the table constructor as instead we are supposed to use `table_builder` which is backend-agnostic.
 from Standard.Table import all hiding Table
-from Standard.Table.Data.Aggregate_Column.Aggregate_Column import Group_By, Count, Sum
 
 from Standard.Test import all
 
@@ -54,7 +53,7 @@ add_specs suite_builder setup =
             t1 = table_builder [["Count", [1, 2, 3]], ["Class", ["X", "Y", "Z"]]] 
             t2 = table_builder [["Letter", ["A", "B", "A", "A", "C", "A", "C", "D", "D", "B", "B"]]]
 
-            t3 = t2.aggregate [Group_By "Letter", Count]
+            t3 = t2.aggregate ["Letter"] [Aggregate_Column.Count]
             t4 = t3.join t1 on="Count" join_kind=Join_Kind.Left_Outer |> materialize |> _.order_by "Letter"
             t4.columns.map .name . should_equal ["Letter", "Count", "Right Count", "Class"]
             rows = t4.rows . map .to_vector
@@ -66,7 +65,7 @@ add_specs suite_builder setup =
         group_builder.specify "aggregates and distinct" <|
             t2 = table_builder [["Letter", ["A", "B", "A", "A", "C", "C"]], ["Points", [2, 5, 2, 1, 10, 3]]]
 
-            t3 = t2.aggregate [Group_By "Letter", Sum "Points"]
+            t3 = t2.aggregate ["Letter"] [Aggregate_Column.Sum "Points"]
             t4 = t3.distinct "Sum Points" |> materialize |> _.order_by "Sum Points"
             t4.columns.map .name . should_equal ["Letter", "Sum Points"]
             t4.row_count . should_equal 2
@@ -81,7 +80,7 @@ add_specs suite_builder setup =
         group_builder.specify "aggregates and filtering" <|
             t2 = table_builder [["Letter", ["A", "B", "A", "A", "C", "C", "B"]], ["Points", [2, 5, 2, 1, 10, 3, 0]]]
 
-            t3 = t2.aggregate [Group_By "Letter", Sum "Points"]
+            t3 = t2.aggregate ["Letter"] [Aggregate_Column.Sum "Points"]
             t4 = t3.filter "Sum Points" (Filter_Condition.Equal 5)  |> materialize |> _.order_by "Letter"
             t4.columns.map .name . should_equal ["Letter", "Sum Points"]
             rows = t4.rows . map .to_vector
@@ -90,7 +89,7 @@ add_specs suite_builder setup =
 
         group_builder.specify "aggregates and ordering" <|
             t1 = table_builder [["Letter", ["C", "A", "B", "A", "A", "C", "C", "B"]], ["Points", [0, -100, 5, 2, 1, 10, 3, 0]]]
-            t2 = t1.aggregate [Group_By "Letter", Sum "Points"]
+            t2 = t1.aggregate ["Letter"] [Aggregate_Column.Sum "Points"]
             t3 = t2.order_by "Sum Points" |> materialize
             t3.columns.map .name . should_equal ["Letter", "Sum Points"]
             t3.at "Letter" . to_vector . should_equal ["A", "B", "C"]
@@ -194,7 +193,7 @@ add_specs suite_builder setup =
                     vt1.should_be_a (Value_Type.Char ...)
                     vt1.variable_length.should_be_true
 
-                t4 = t3.aggregate [Aggregate_Column.Shortest "X", Aggregate_Column.Group_By "Y"]
+                t4 = t3.aggregate ["Y"] [Aggregate_Column.Shortest "X"]
                 vt2 = t4.at "Shortest X" . value_type
                 Test.with_clue "t4[X].value_type="+vt2.to_display_text+": " <|
                     vt2.should_be_a (Value_Type.Char ...)
@@ -219,7 +218,7 @@ add_specs suite_builder setup =
                     c.value_type.variable_length.should_be_true
 
                 t2 = t1.set c "C"
-                t3 = t2.aggregate [Aggregate_Column.Shortest "C"]
+                t3 = t2.aggregate columns=[Aggregate_Column.Shortest "C"]
                 t3.at "Shortest C" . to_vector . should_equal ["b"]
                 vt = t3.at "Shortest C" . value_type
                 Test.with_clue "t3[C].value_type="+vt.to_display_text+": " <|

test/Table_Tests/src/Common_Table_Operations/Missing_Values_Spec.enso

@@ -1,7 +1,6 @@
 from Standard.Base import all
 
 from Standard.Table import Value_Type, Column_Ref, Previous_Value, Blank_Selector
-from Standard.Table.Data.Aggregate_Column.Aggregate_Column import Count_Distinct
 from Standard.Table.Errors import all
 
 from Standard.Database.Errors import Unsupported_Database_Operation

test/Table_Tests/src/Common_Table_Operations/Take_Drop_Spec.enso

@@ -4,7 +4,7 @@ import Standard.Base.Errors.Common.Index_Out_Of_Bounds
 import Standard.Base.Errors.Common.Type_Error
 import Standard.Base.Errors.Illegal_Argument.Illegal_Argument
 
-from Standard.Table.Data.Aggregate_Column.Aggregate_Column import Group_By, Sum
+from Standard.Table import Aggregate_Column
 from Standard.Table.Errors import all
 
 from Standard.Test import all
@@ -254,7 +254,7 @@ add_specs suite_builder setup =
 
         group_builder.specify "Should work correctly after aggregation" <|
             t0 = table_builder [["X", ["a", "b", "a", "c"]], ["Y", [1, 2, 4, 8]]]
-            t1 = t0.aggregate [Group_By "X", Sum "Y"]
+            t1 = t0.aggregate ["X"] [Aggregate_Column.Sum "Y"]
 
             t2 = t1.order_by "X" . take 2
             t2.at "X" . to_vector . should_equal ['a', 'b']

test/Table_Tests/src/Database/Codegen_Spec.enso

@@ -1,8 +1,7 @@
 from Standard.Base import all
 import Standard.Base.Errors.Illegal_State.Illegal_State
 
-from Standard.Table import Sort_Column, Value_Type, Blank_Selector
-from Standard.Table.Data.Aggregate_Column.Aggregate_Column import all hiding First, Last
+from Standard.Table import Sort_Column, Value_Type, Blank_Selector, Aggregate_Column
 from Standard.Table.Errors import No_Input_Columns_Selected, Missing_Input_Columns, No_Such_Column
 
 from Standard.Database import all
@@ -158,12 +157,12 @@ add_specs suite_builder =
             data.teardown
 
         group_builder.specify "should allow to count rows" <|
-            code = data.t1.aggregate [Group_By "A" "A grp", Count "counter"] . to_sql . prepare
-            code . should_equal ['SELECT "T1"."A grp" AS "A grp", "T1"."counter" AS "counter" FROM (SELECT "T1"."A" AS "A grp", COUNT(*) AS "counter" FROM "T1" AS "T1" GROUP BY "T1"."A") AS "T1"', []]
+            code = data.t1.aggregate ["A"] [Aggregate_Column.Count "counter"] . to_sql . prepare
+            code . should_equal ['SELECT "T1"."A" AS "A", "T1"."counter" AS "counter" FROM (SELECT "T1"."A" AS "A", COUNT(*) AS "counter" FROM "T1" AS "T1" GROUP BY "T1"."A") AS "T1"', []]
 
         group_builder.specify "should allow to group by multiple fields" <|
-            code = data.t1.aggregate [Sum "A" "sum_a", Group_By "C", Group_By "B" "B grp"] . to_sql . prepare
-            code . should_equal ['SELECT "T1"."sum_a" AS "sum_a", "T1"."C" AS "C", "T1"."B grp" AS "B grp" FROM (SELECT SUM("T1"."A") AS "sum_a", "T1"."C" AS "C", "T1"."B" AS "B grp" FROM "T1" AS "T1" GROUP BY "T1"."C", "T1"."B") AS "T1"', []]
+            code = data.t1.aggregate ["C", "B"] [Aggregate_Column.Sum "A" "sum_a"] . to_sql . prepare
+            code . should_equal ['SELECT "T1"."C" AS "C", "T1"."B" AS "B", "T1"."sum_a" AS "sum_a" FROM (SELECT "T1"."C" AS "C", "T1"."B" AS "B", SUM("T1"."A") AS "sum_a" FROM "T1" AS "T1" GROUP BY "T1"."C", "T1"."B") AS "T1"', []]
 
 main =
     suite = Test.build suite_builder->

test/Table_Tests/src/Database/Common/Common_Spec.enso

@@ -2,8 +2,7 @@ from Standard.Base import all
 import Standard.Base.Errors.Common.Index_Out_Of_Bounds
 import Standard.Base.Errors.Illegal_Argument.Illegal_Argument
 
-from Standard.Table import Table, Sort_Column
-from Standard.Table.Data.Aggregate_Column.Aggregate_Column import all hiding First, Last
+from Standard.Table import Table, Sort_Column, Aggregate_Column
 from Standard.Table.Errors import all
 
 from Standard.Database import all
@@ -424,15 +423,15 @@ add_specs (suite_builder : Suite_Builder) (prefix : Text) (create_connection_fn
         group_builder.specify "should allow counting group sizes and elements" <|
             ## Names set to lower case to avoid issue with Redshift where columns are
                returned in lower case.
-            aggregates = [Count "count", Count_Not_Nothing "price" "count not nothing price", Count_Nothing "price" "count nothing price"]
+            aggregates = [Aggregate_Column.Count "count", Aggregate_Column.Count_Not_Nothing "price" "count not nothing price", Aggregate_Column.Count_Nothing "price" "count nothing price"]
 
-            t1 = determinize_by "name" (data.t9.aggregate ([Group_By "name"] + aggregates) . read)
+            t1 = determinize_by "name" (data.t9.aggregate ["name"] aggregates . read)
             t1.at  "name" . to_vector . should_equal ["bar", "baz", "foo", "quux", "zzzz"]
             t1.at  "count" . to_vector . should_equal [2, 1, 5, 1, 7]
             t1.at  "count not nothing price" . to_vector . should_equal [2, 1, 3, 0, 5]
             t1.at  "count nothing price" . to_vector . should_equal [0, 0, 2, 1, 2]
 
-            t2 = data.t9.aggregate aggregates . read
+            t2 = data.t9.aggregate [] aggregates . read
             t2.at  "count" . to_vector . should_equal [16]
             t2.at  "count not nothing price" . to_vector . should_equal [11]
             t2.at  "count nothing price" . to_vector . should_equal [5]
@@ -440,16 +439,16 @@ add_specs (suite_builder : Suite_Builder) (prefix : Text) (create_connection_fn
         group_builder.specify "should allow simple arithmetic aggregations" <|
             ## Names set to lower case to avoid issue with Redshift where columns are
                returned in lower case.
-            aggregates = [Sum "price" "sum price", Sum "quantity" "sum quantity", Average "price" "avg price"]
+            aggregates = [Aggregate_Column.Sum "price" "sum price", Aggregate_Column.Sum "quantity" "sum quantity", Aggregate_Column.Average "price" "avg price"]
             ## TODO can check the datatypes
 
-            t1 = determinize_by "name" (data.t9.aggregate ([Group_By "name"] + aggregates) . read)
+            t1 = determinize_by "name" (data.t9.aggregate ["name"] aggregates . read)
             t1.at  "name" . to_vector . should_equal ["bar", "baz", "foo", "quux", "zzzz"]
             t1.at  "sum price" . to_vector . should_equal [100.5, 6.7, 1, Nothing, 2]
             t1.at  "sum quantity" . to_vector . should_equal [80, 40, 120, 70, 2]
             t1.at  "avg price" . to_vector . should_equal [50.25, 6.7, (1/3), Nothing, (2/5)]
 
-            t2 = data.t9.aggregate aggregates . read
+            t2 = data.t9.aggregate [] aggregates . read
             t2.at  "sum price" . to_vector . should_equal [110.2]
             t2.at  "sum quantity" . to_vector . should_equal [312]
             t2.at  "avg price" . to_vector . should_equal [(110.2 / 11)]

test/Table_Tests/src/Database/Common/Default_Ordering_Spec.enso

@@ -68,7 +68,7 @@ add_specs (suite_builder : Suite_Builder) (prefix : Text) (create_connection_fn
 
         group_builder.specify "will return Nothing for composite tables (join, aggregate)"
             data.db_table_with_key.join data.db_table_with_key . default_ordering . should_equal Nothing
-            data.db_table_with_key.aggregate [Aggregate_Column.Group_By "X"] . default_ordering . should_equal Nothing
+            data.db_table_with_key.aggregate ["X"] . default_ordering . should_equal Nothing
 
         group_builder.specify "will return the ordering determined by order_by" <|
             v1 = data.db_table_with_key.order_by ["Y", Sort_Column.Name "X" Sort_Direction.Descending] . default_ordering

test/Table_Tests/src/Database/Common/Names_Length_Limits_Spec.enso

@@ -188,7 +188,7 @@ add_specs suite_builder prefix create_connection_func =
             src = Table.new [[name_1, [1, 2, 3]], [name_2, [4, 5, 6]]]
             t1 = src.select_into_database_table data.connection (Name_Generator.random_name "long-column-names") temporary=True
             # We create 2 Maximum columns that if wrongly truncated will have the same name, introducing possible ambiguity to further queries.
-            t2 = t1.aggregate [Aggregate_Column.Group_By name_1, Aggregate_Column.Maximum name_2, Aggregate_Column.Maximum name_1]
+            t2 = t1.aggregate [name_1] [Aggregate_Column.Maximum name_2, Aggregate_Column.Maximum name_1]
 
             # The newly added column would by default have a name exceeding the limit, if there's one - and its 'dumbly' truncated name will clash with the already existing column.
             t3 = t1.set (t1.at name_1 * t1.at name_2)
@@ -372,7 +372,7 @@ add_specs suite_builder prefix create_connection_func =
                 src = Table.new [["X", [1, 2, 3]]]
                 db_table = src.select_into_database_table data.connection (Name_Generator.random_name "long-column-names") temporary=True
                 long_name = "a" * (max_column_name_length + 1)
-                r = db_table.aggregate [Aggregate_Column.Maximum "X" new_name=long_name]
+                r = db_table.aggregate columns=[Aggregate_Column.Maximum "X" new_name=long_name]
                 r.should_fail_with Name_Too_Long
                 r.catch.entity_kind . should_equal "column"
                 r.catch.name . should_equal long_name
@@ -382,7 +382,7 @@ add_specs suite_builder prefix create_connection_func =
                 name_b = "x" * (max_column_name_length - 1) + "B"
                 src = Table.new [[name_a, [1, 2, 3]], [name_b, [4, 5, 6]]]
                 db_table = src.select_into_database_table data.connection (Name_Generator.random_name "long-column-names") temporary=True
-                t2 = db_table.aggregate [Aggregate_Column.Maximum name_a, Aggregate_Column.Maximum name_b]
+                t2 = db_table.aggregate columns=[Aggregate_Column.Maximum name_a, Aggregate_Column.Maximum name_b]
                 w1 = Problems.expect_warning Truncated_Column_Names t2
 
                 w1.original_names . should_contain_the_same_elements_as ["Maximum "+name_a, "Maximum "+name_b]
@@ -397,7 +397,7 @@ add_specs suite_builder prefix create_connection_func =
                 src2 = Table.new (names.map_with_index i-> name-> [name, [100 + i, 200 + i]])
                 db_table2 = src2.select_into_database_table data.connection (Name_Generator.random_name "long-column-names") temporary=True
                 Problems.assume_no_problems db_table2
-                t3 = db_table2.aggregate (names.map name-> Aggregate_Column.Maximum name)
+                t3 = db_table2.aggregate columns=(names.map name-> Aggregate_Column.Maximum name)
                 w2 = Problems.expect_warning Truncated_Column_Names t3
                 w2.original_names . should_contain_the_same_elements_as (names.map name-> "Maximum " + name)
                 t3.column_names . should_contain_the_same_elements_as w2.truncated_names

test/Table_Tests/src/Database/Postgres_Spec.enso

@@ -4,8 +4,7 @@ import Standard.Base.Errors.Illegal_State.Illegal_State
 import Standard.Base.Runtime.Ref.Ref
 
 import Standard.Table.Data.Type.Value_Type.Bits
-from Standard.Table import Table, Value_Type
-from Standard.Table.Data.Aggregate_Column.Aggregate_Column import all hiding First, Last
+from Standard.Table import Table, Value_Type, Aggregate_Column
 from Standard.Table.Errors import Invalid_Column_Names, Inexact_Type_Coercion, Duplicate_Output_Column_Names
 
 import Standard.Database.Data.Column.Column
@@ -231,7 +230,7 @@ postgres_specific_spec suite_builder create_connection_fn db_name setup =
             i.at "Value Type" . to_vector . should_equal [default_text, Value_Type.Integer, Value_Type.Boolean, Value_Type.Float]
 
         group_builder.specify "should return Table information, also for aggregated results" <|
-            i = data.t.aggregate [Concatenate "strs", Sum "ints", Count_Distinct "bools"] . info
+            i = data.t.aggregate columns=[Aggregate_Column.Concatenate "strs", Aggregate_Column.Sum "ints", Aggregate_Column.Count_Distinct "bools"] . info
             i.at "Column" . to_vector . should_equal ["Concatenate strs", "Sum ints", "Count Distinct bools"]
             i.at "Items Count" . to_vector . should_equal [1, 1, 1]
             i.at "Value Type" . to_vector . should_equal [default_text, Value_Type.Decimal, Value_Type.Integer]
@@ -277,19 +276,19 @@ postgres_specific_spec suite_builder create_connection_fn db_name setup =
             data.teardown
 
         group_builder.specify "Concatenate, Shortest and Longest" <|
-            r = data.t.aggregate [Concatenate "txt", Shortest "txt", Longest "txt"]
+            r = data.t.aggregate columns=[Aggregate_Column.Concatenate "txt", Aggregate_Column.Shortest "txt", Aggregate_Column.Longest "txt"]
             r.columns.at 0 . value_type . should_equal default_text
             r.columns.at 1 . value_type . should_equal default_text
             r.columns.at 2 . value_type . should_equal default_text
 
         group_builder.specify "Counts" <|
-            r = data.t.aggregate [Count, Count_Empty "txt", Count_Not_Empty "txt", Count_Distinct "i1", Count_Not_Nothing "i2", Count_Nothing "i3"]
+            r = data.t.aggregate columns=[Aggregate_Column.Count, Aggregate_Column.Count_Empty "txt", Aggregate_Column.Count_Not_Empty "txt", Aggregate_Column.Count_Distinct "i1", Aggregate_Column.Count_Not_Nothing "i2", Aggregate_Column.Count_Nothing "i3"]
             r.column_count . should_equal 6
             r.columns.each column->
                 column.value_type . should_equal Value_Type.Integer
 
         group_builder.specify "Sum" <|
-            r = data.t.aggregate [Sum "i1", Sum "i2", Sum "i3", Sum "i4", Sum "r1", Sum "r2"]
+            r = data.t.aggregate columns=[Aggregate_Column.Sum "i1", Aggregate_Column.Sum "i2", Aggregate_Column.Sum "i3", Aggregate_Column.Sum "i4", Aggregate_Column.Sum "r1", Aggregate_Column.Sum "r2"]
             r.columns.at 0 . value_type . should_equal Value_Type.Integer
             r.columns.at 1 . value_type . should_equal Value_Type.Integer
             r.columns.at 2 . value_type . should_equal Value_Type.Decimal
@@ -298,7 +297,7 @@ postgres_specific_spec suite_builder create_connection_fn db_name setup =
             r.columns.at 5 . value_type . should_equal (Value_Type.Float Bits.Bits_64)
 
         group_builder.specify "Average" <|
-            r = data.t.aggregate [Average "i1", Average "i2", Average "i3", Average "i4", Average "r1", Average "r2"]
+            r = data.t.aggregate columns=[Aggregate_Column.Average "i1", Aggregate_Column.Average "i2", Aggregate_Column.Average "i3", Aggregate_Column.Average "i4", Aggregate_Column.Average "r1", Aggregate_Column.Average "r2"]
             r.columns.at 0 . value_type . should_equal Value_Type.Decimal
             r.columns.at 1 . value_type . should_equal Value_Type.Decimal
             r.columns.at 2 . value_type . should_equal Value_Type.Decimal

test/Table_Tests/src/Database/Types/Postgres_Type_Mapping_Spec.enso

@@ -111,7 +111,7 @@ add_specs suite_builder create_connection_fn =
             t.evaluate_expression 'is_nan([d])' . value_type . should_equal Value_Type.Boolean
             t.evaluate_expression 'is_nothing([a])' . value_type . should_equal Value_Type.Boolean
 
-            t2 = t.aggregate [Aggregate_Column.Group_By "b", Aggregate_Column.Sum "a", Aggregate_Column.Maximum "a", Aggregate_Column.Count_Not_Nothing "c", Aggregate_Column.Concatenate "b", Aggregate_Column.Count, (Aggregate_Column.First "c" order_by="a")]
+            t2 = t.aggregate ["b"] [Aggregate_Column.Sum "a", Aggregate_Column.Maximum "a", Aggregate_Column.Count_Not_Nothing "c", Aggregate_Column.Concatenate "b", Aggregate_Column.Count, (Aggregate_Column.First "c" order_by="a")]
             t2.at "b" . value_type . should_equal default_text
             t2.at "Sum a" . value_type . should_equal (Value_Type.Integer Bits.Bits_64)
             t2.at "Maximum a" . value_type . should_equal (Value_Type.Integer Bits.Bits_16)

test/Table_Tests/src/Database/Types/SQLite_Type_Mapping_Spec.enso

@@ -88,7 +88,7 @@ add_specs suite_builder =
             t.evaluate_expression 'is_empty([b])' . value_type . should_equal Value_Type.Boolean
             t.evaluate_expression 'is_nothing([a])' . value_type . should_equal Value_Type.Boolean
 
-            t2 = t.aggregate [Aggregate_Column.Group_By "b", Aggregate_Column.Sum "a", Aggregate_Column.Maximum "a", Aggregate_Column.Minimum "d", Aggregate_Column.Count_Not_Nothing "c", Aggregate_Column.Concatenate "b", Aggregate_Column.Count]
+            t2 = t.aggregate ["b"] [Aggregate_Column.Sum "a", Aggregate_Column.Maximum "a", Aggregate_Column.Minimum "d", Aggregate_Column.Count_Not_Nothing "c", Aggregate_Column.Concatenate "b", Aggregate_Column.Count]
             t2.at "b" . value_type . should_equal Value_Type.Char
             t2.at "Sum a" . value_type . should_equal Value_Type.Integer
             t2.at "Maximum a" . value_type . should_equal Value_Type.Integer

test/Table_Tests/src/Database/Upload_Spec.enso

@@ -489,7 +489,7 @@ add_specs suite_builder make_new_connection prefix persistent_connector=True =
             db_table_1 = t1.select_into_database_table data.connection (Name_Generator.random_name "source-table-1") temporary=True primary_key=Nothing
 
             db_table_2 = db_table_1.set "[Y] + 100 * [X]" "C1" . set '"constant_text"' "C2"
-            db_table_3 = db_table_1.aggregate [Aggregate_Column.Group_By "X", Aggregate_Column.Sum "[Y]*[Y]" "C3"] . set "[X] + 1" "X"
+            db_table_3 = db_table_1.aggregate ["X"] [Aggregate_Column.Sum "[Y]*[Y]" "C3"] . set "[X] + 1" "X"
 
             db_table_4 = db_table_2.join db_table_3 join_kind=Join_Kind.Left_Outer
             db_table_4.is_trivial_query . should_fail_with Table_Not_Found

test/Table_Tests/src/In_Memory/Table_Spec.enso

@@ -6,7 +6,6 @@ import Standard.Base.Errors.Common.Type_Error
 import Standard.Base.Errors.Illegal_Argument.Illegal_Argument
 
 from Standard.Table import Table, Column, Sort_Column, Aggregate_Column, Blank_Selector
-from Standard.Table.Data.Aggregate_Column.Aggregate_Column import all hiding First, Last
 import Standard.Table.Data.Type.Value_Type.Value_Type
 from Standard.Table.Errors import Invalid_Column_Names, Duplicate_Output_Column_Names, No_Input_Columns_Selected, Missing_Input_Columns, No_Such_Column, Floating_Point_Equality, Invalid_Value_Type, Row_Count_Mismatch
 
@@ -656,19 +655,19 @@ add_specs suite_builder =
             objects = ["objects", [My.Data 0 1, My.Data 0 1, My.Data 2 2, My.Data 2 2]]
             table = Table.new [dates, texts, mixed, ints, floats, objects]
 
-            t1 = table.aggregate [Group_By "dates", Shortest "texts", Aggregate_Column.First "texts", Aggregate_Column.First "objects", Aggregate_Column.First "ints", Aggregate_Column.Last "mixed"]
+            t1 = table.aggregate ["dates"] [Aggregate_Column.Shortest "texts", Aggregate_Column.First "texts", Aggregate_Column.First "objects", Aggregate_Column.First "ints", Aggregate_Column.Last "mixed"]
             t1.info.at "Column" . to_vector . should_equal ["dates", "Shortest texts", "First texts", "First objects", "First ints", "Last mixed"]
             t1.info.at "Value Type" . to_vector . should_equal [Value_Type.Date, Value_Type.Char, Value_Type.Char, Value_Type.Mixed, Value_Type.Integer, Value_Type.Mixed]
 
-            t2 = table.aggregate [Mode "dates", Count_Not_Nothing "objects", Count_Distinct "texts", Minimum "ints", Maximum "floats"]
+            t2 = table.aggregate [] [Aggregate_Column.Mode "dates", Aggregate_Column.Count_Not_Nothing "objects", Aggregate_Column.Count_Distinct "texts", Aggregate_Column.Minimum "ints", Aggregate_Column.Maximum "floats"]
             t2.info.at "Column" . to_vector . should_equal ["Mode dates", "Count Not Nothing objects", "Count Distinct texts", "Minimum ints", "Maximum floats"]
             t2.info.at "Value Type" . to_vector . should_equal [Value_Type.Date, Value_Type.Integer, Value_Type.Integer, Value_Type.Integer, Value_Type.Float]
 
-            t3 = table.aggregate [Group_By "texts", Group_By "ints", Aggregate_Column.Last "floats"]
+            t3 = table.aggregate ["texts", "ints"] [Aggregate_Column.Last "floats"]
             t3.info.at "Column" . to_vector . should_equal ["texts", "ints", "Last floats"]
             t3.info.at "Value Type" . to_vector . should_equal [Value_Type.Char, Value_Type.Integer, Value_Type.Float]
 
-            t4 = table.aggregate [Group_By "mixed", Sum "ints", Sum "floats"]
+            t4 = table.aggregate ["mixed"] [Aggregate_Column.Sum "ints", Aggregate_Column.Sum "floats"]
             t4.info.at "Column" . to_vector . should_equal ["mixed", "Sum ints", "Sum floats"]
             t4.info.at "Value Type" . to_vector . should_equal [Value_Type.Mixed, Value_Type.Float, Value_Type.Float]
 
@@ -676,20 +675,20 @@ add_specs suite_builder =
             texts = ["texts", ['ściana', 'ściana', 'łąka', 's\u0301ciana', 'ła\u0328ka', 'sciana']]
             ints = ["ints", [1, 2, 4, 8, 16, 32]]
             table = Table.new [texts, ints]
-            r1 = table.aggregate [Group_By "texts", Sum "ints"] . order_by ([Sort_Column.Name "texts"])
+            r1 = table.aggregate ["texts"] [Aggregate_Column.Sum "ints"] . order_by ([Sort_Column.Name "texts"])
             r1.at "texts" . to_vector . should_equal ['sciana', 'ściana', 'łąka']
             r1.at "Sum ints" . to_vector . should_equal [32, 11, 20]
 
-            r2 = table.aggregate [Count_Distinct "texts"]
+            r2 = table.aggregate columns=[Aggregate_Column.Count_Distinct "texts"]
             r2.at "Count Distinct texts" . to_vector . should_equal [3]
 
         group_builder.specify "should be able to aggregate over enso Types" <|
             weekday_table  = Table.new [["days", [Day_Of_Week.Monday, Day_Of_Week.Monday, Day_Of_Week.Monday, Day_Of_Week.Tuesday, Day_Of_Week.Sunday]], ["group", [1,1,2,1,2]]]
 
-            r1 = weekday_table.aggregate [Group_By "days"] . order_by "days"
+            r1 = weekday_table.aggregate ["days"] . order_by "days"
             r1.at "days" . to_vector . should_equal [Day_Of_Week.Sunday, Day_Of_Week.Monday, Day_Of_Week.Tuesday]
 
-            r2 = weekday_table.aggregate [Group_By "group", Minimum "days" "min", Maximum "days" "max"] . order_by "group"
+            r2 = weekday_table.aggregate ["group"] [Aggregate_Column.Minimum "days" "min", Aggregate_Column.Maximum "days" "max"] . order_by "group"
             r2.at "group" . to_vector . should_equal [1, 2]
             r2.at "min" . to_vector . should_equal [Day_Of_Week.Monday, Day_Of_Week.Sunday]
             r2.at "max" . to_vector . should_equal [Day_Of_Week.Tuesday, Day_Of_Week.Monday]

test/Visualization_Tests/src/Table_Spec.enso

@@ -69,7 +69,7 @@ add_specs suite_builder =
             json = make_json header=["A"] data=[['a', 'a']] all_rows=3 ixes_header=[] ixes=[]
             vis . should_equal json
 
-            g = data.t.aggregate [Aggregate_Column.Group_By "A", Aggregate_Column.Group_By "B", Aggregate_Column.Average "C"] . at "Average C"
+            g = data.t.aggregate ["A", "B"] [Aggregate_Column.Average "C"] . at "Average C"
             vis2 = Visualization.prepare_visualization g 1
             json2 = make_json header=["Average C"] data=[[4.0]] all_rows=2 ixes_header=[] ixes=[]
             vis2 . should_equal json2

tools/performance/benchmark-analysis/src/Main.enso

@@ -36,7 +36,7 @@ main =
     operator25 = Table.from_rows operator27 [operator27]
     operator28 = operator25.first_row
     operator29 = operator28.at 'current_implementation'
-    operator30 = operator22.aggregate [(Aggregate_Column.Group_By 'Approach'), (Aggregate_Column.Average 'Time')]
+    operator30 = operator22.aggregate ['Approach'] [Aggregate_Column.Average 'Time']
     operator31 = operator30.filter 'Approach' (Filter_Condition.Equal operator29)
     operator32 = operator31.at 'Average Time' . at 0
     operator33 = operator30.set "[Average Time] / "+operator32.to_text "Percentage"

tools/performance/engine-benchmarks/Engine_Benchs/src/Main.enso

@@ -1,16 +1,12 @@
 from Standard.Base import all
-from Standard.Base.Data.Filter_Condition import Filter_Condition
-from Standard.Base.Data.Map import Map
-from Standard.Base.Data.Time.Date import Date
 from Standard.Table import all
 from Standard.Database import all
-from Standard.Table.Data.Aggregate_Column import Aggregate_Column
 import Standard.Visualization
 
 main =
     operator4 = [Aggregate_Column.Maximum "commit_timestamp"]
     operator11 = [Aggregate_Column.Minimum "commit_timestamp"]
-    operator13 = [Aggregate_Column.Group_By "label"]
+    operator13 = ["label"]
     number1 = 26
     text1 = "benchs.csv"
     operator5 = enso_project.data / text1
@@ -18,8 +14,8 @@ main =
     operator7 = operator6.row_count
     operator1 = operator6.column_names
     operator9 = operator6.at 'commit_timestamp'
-    operator3 = operator6.aggregate operator4
-    operator8 = operator6.aggregate operator11
+    operator3 = operator6.aggregate [] operator4
+    operator8 = operator6.aggregate [] operator11
     operator12 = operator6.aggregate operator13
     operator17 = operator12.at 'label'
     operator18 = operator17.to_vector