Concatenate Tables

Stack tables into one

how decides what concat() does when the inputs do not line up.

AI agent session

❯make a new table that takes the sales_east and sales_west tables and stacks their rows into one table

⏺

Needs a transformer. Getting its guide.

Called tabsdata 2 times (ctrl+o to expand)

⏺

Generating — concat() appends rows, and the default how="vertical" is right here because both inputs carry the same three columns with the same types.

Called tabsdata 3 times (ctrl+o to expand)

⏺

The transformer, registered in subscriptions:

@transformer(
  input_tables=["sales_east", "sales_west"],
  output_tables=["sales_all"],
)
def combine_sales(east: TableFrameSpec, west: TableFrameSpec) -> TableFrameSpec:
  return concat([east, west])

⏺

Execution committed, 0 failures.

⏺

subscriptions/sales_all is live — 2 rows from sales_east then 2 from sales_west, in that order, columns unchanged:

┌────────┬───────┬────────┐
│ region │ month │ amount │
├────────┼───────┼────────┤
│ east   │ jan   │ 10     │
├────────┼───────┼────────┤
│ east   │ feb   │ 20     │
├────────┼───────┼────────┤
│ west   │ jan   │ 30     │
├────────┼───────┼────────┤
│ west   │ feb   │ 40     │
└────────┴───────┴────────┘

Transformed tables

sales_east

region	month	amount
east	jan	10
east	feb	20

2 rows

sales_west

region	month	amount
west	jan	30
west	feb	40

2 rows

sales_all

region	month	amount
east	jan	10
east	feb	20
west	jan	30
west	feb	40

4 rows

AI agent session

❯make a new table that takes the sales_east and sales_west tables and stacks their rows into one table, casting a column that is typed differently in each

⏺

Needs a transformer. Getting its guide.

Called tabsdata 2 times (ctrl+o to expand)

⏺

Generating — the columns match and the types do not, so how="vertical_relaxed" casts amount to a common supertype instead of refusing.

Called tabsdata 3 times (ctrl+o to expand)

⏺

The transformer, registered in subscriptions:

@transformer(
  input_tables=["sales_east", "sales_west"],
  output_tables=["sales_all"],
)
def combine_sales(east: TableFrameSpec, west: TableFrameSpec) -> TableFrameSpec:
  return concat([east, west], how="vertical_relaxed")

⏺

Execution committed, 0 failures.

⏺

subscriptions/sales_all is live — amount came out Float64, so the Int64 value from sales_east was cast:

┌────────┬────────┐
│ region │ amount │
├────────┼────────┤
│ east   │ 10.0   │
├────────┼────────┤
│ west   │ 30.5   │
└────────┴────────┘

Transformed tables

sales_east

regionString	amountInt64
east	10

1 row

sales_west

regionString	amountFloat64
west	30.5

1 row

sales_all

regionString	amountFloat64
east	10.0
west	30.5

2 rows

AI agent session

❯make a new table that takes the sales_east and sales_west tables and stacks their rows into one table, unioning the columns only one of them has

⏺

Needs a transformer. Getting its guide.

Called tabsdata 2 times (ctrl+o to expand)

⏺

Generating — the columns differ, which how="vertical" rejects. how="diagonal" takes the union of the columns and fills the gaps with null.

Called tabsdata 3 times (ctrl+o to expand)

⏺

The transformer, registered in subscriptions:

@transformer(
  input_tables=["sales_east", "sales_west"],
  output_tables=["sales_all"],
)
def combine_sales(east: TableFrameSpec, west: TableFrameSpec) -> TableFrameSpec:
  return concat([east, west], how="diagonal")

⏺

Execution committed, 0 failures.

⏺

subscriptions/sales_all is live — 4 columns, the union of both inputs. The east row has no discount and the west row has no amount:

┌────────┬───────┬────────┬──────────┐
│ region │ month │ amount │ discount │
├────────┼───────┼────────┼──────────┤
│ east   │ jan   │ 10     │ null     │
├────────┼───────┼────────┼──────────┤
│ west   │ jan   │ null   │ 5        │
└────────┴───────┴────────┴──────────┘

Transformed tables

sales_east

region	month	amount
east	jan	10

1 row

sales_west

region	month	discount
west	jan	5

1 row

sales_all

region	month	amount	discount
east	jan	10	null
west	jan	null	5

2 rows

AI agent session

❯make a new table that takes the sales_east and sales_west tables and stacks their rows into one table, reconciling both the columns and the types

⏺

Needs a transformer. Getting its guide.

Called tabsdata 2 times (ctrl+o to expand)

⏺

Generating — the inputs differ in both their columns and their types, so this needs how="diagonal_relaxed", which unions the columns and casts to a supertype in one pass.

Called tabsdata 3 times (ctrl+o to expand)

⏺

The transformer, registered in subscriptions:

@transformer(
  input_tables=["sales_east", "sales_west"],
  output_tables=["sales_all"],
)
def combine_sales(east: TableFrameSpec, west: TableFrameSpec) -> TableFrameSpec:
  return concat([east, west], how="diagonal_relaxed")

⏺

Execution committed, 0 failures.

⏺

subscriptions/sales_all is live — the union of both column sets, each column keeping the type it needs:

┌────────┬────────┬──────────┐
│ region │ amount │ discount │
├────────┼────────┼──────────┤
│ east   │ 10     │ null     │
├────────┼────────┼──────────┤
│ west   │ null   │ 5.5      │
└────────┴────────┴──────────┘

Transformed tables

sales_east

regionString	amountInt64
east	10

1 row

sales_west

regionString	discountFloat64
west	5.5

1 row

sales_all

regionString	amountInt64	discountFloat64
east	10	null
west	null	5.5

2 rows

note

None entries in the list are skipped. A list that is None, empty, or empty once the None entries are dropped makes concat() return None, which leaves the output table on its current version instead of committing a new one.