Access Table Values

Rayforce-Py provides a handy interface to access Table columns and values.

Access a Specific Column

The at_column() method returns all values from a specific column as a Vector.

>>> table = Table.from_dict({
    "id": Vector(items=["001", "002", "003"], ray_type=Symbol),
    "name": Vector(items=["alice", "bob", "charlie"], ray_type=Symbol),
    "age": Vector(items=[29, 34, 41], ray_type=I64),
})

>>> name_col = table.at_column("name")
>>> name_col
Vector([Symbol('alice'), Symbol('bob'), Symbol('charlie')])

>>> age_col = table.at_column("age")
>>> age_col
Vector([I64(29), I64(34), I64(41)])

Access a Specific Row

The at_row() method returns all column values for a specific row as a Dict. The row index is zero-based.

>>> table = Table.from_dict({
    "id": Vector(items=["001", "002", "003"], ray_type=Symbol),
    "name": Vector(items=["alice", "bob", "charlie"], ray_type=Symbol),
    "age": Vector(items=[29, 34, 41], ray_type=I64),
})

>>> row_0 = table.at_row(0)
>>> row_0
Dict({'id': '001', 'name': 'alice', 'age': 29})

>>> row_0.to_python()
{'id': '001', 'name': 'alice', 'age': 29}

>>> row_2 = table.at_row(2)
>>> row_2.to_python()
{'id': '003', 'name': 'charlie', 'age': 41}

Slice a Table

The slice() method returns a new table containing a subset of rows from the original table.

When called with a single argument, it takes the first n rows:

>>> table = Table.from_dict({
    "id": Vector(items=["001", "002", "003", "004"], ray_type=Symbol),
    "name": Vector(items=["alice", "bob", "charlie", "dana"], ray_type=Symbol),
    "age": Vector(items=[29, 34, 41, 38], ray_type=I64),
})

>>> first_two = table.slice(2)
>>> print(first_two)
┌────────┬────────┬────────────────────┐
│   id   │  name  │        age         │
│ SYMBOL │ SYMBOL │        I64         │
├────────┼────────┼────────────────────┤
│ 001    │ alice  │ 29                 │
│ 002    │ bob    │ 34                 │
├────────┴────────┴────────────────────┤
│ 2 rows (2 shown) 3 columns (3 shown) │
└──────────────────────────────────────┘

When called with two arguments, it takes tail rows starting from start_idx:

>>> middle_rows = table.slice(1, 2)
>>> print(middle_rows)
┌────────┬─────────┬───────────────────┐
│   id   │  name   │        age        │
│ SYMBOL │ SYMBOL  │        I64        │
├────────┼─────────┼───────────────────┤
│ 002    │ bob     │ 34                │
│ 003    │ charlie │ 41                │
├────────┴─────────┴───────────────────┤
│ 2 rows (2 shown) 3 columns (3 shown) │
└──────────────────────────────────────┘

When called negative number of rows, it takes tail rows:

>>> last_rows = table.slice(-2)
>>> print(last_rows)
┌────────┬─────────┬───────────────────┐
│   id   │  name   │        age        │
│ SYMBOL │ SYMBOL  │        I64        │
├────────┼─────────┼───────────────────┤
│ 003    │ charlie │ 41                │
│ 004    │ dana    │ 38                │
├────────┴─────────┴───────────────────┤
│ 2 rows (2 shown) 3 columns (3 shown) │
└──────────────────────────────────────┘

Get Column Names and Values

>>> table: Table
>>> table.columns()
Vector([Symbol('symbol'), Symbol('time'), Symbol('bid'), Symbol('ask')])

>>> table.values()
List([
    Vector([Symbol('AAPL'), Symbol('AAPL'), Symbol('AAPL'), Symbol('GOOG'), Symbol('GOOG'), Symbol('GOOG')]),
    Vector([Time(datetime.time(9, 0, 0, 95000)), Time(datetime.time(9, 0, 0, 105000)), Time(datetime.time(9, 0, 0, 295000)), Time(datetime.time(9, 0, 0, 145000)), Time(datetime.time(9, 0, 0, 155000)), Time(datetime.time(9, 0, 0, 345000))]),
    Vector([F64(100.0), F64(101.0), F64(102.0), F64(200.0), F64(201.0), F64(202.0)]),
    Vector([F64(110.0), F64(111.0), F64(112.0), F64(210.0), F64(211.0), F64(212.0)])
])

>>> [column for column in [records[0] for records in table.values()]]
[Symbol('AAPL'), Time(datetime.time(9, 0, 0, 95000)), F64(100.0), F64(110.0)]