Reference · Vectors

vec.column

vec.column(list | null, str | int) -> list

What it does

One column out of a list of rows. With a string key, each row is a map and the result is that field of every row, in order; with an int, each row is a list and the result is that item of every row. A row without the field or the position gives null there. It turns database rows into a list of numbers for stats and vec.

Examples

let orders = [{ name: "ann", total: 12.5 }, { name: "bob", total: 30 }]print(vec.column(orders, "total"))print(vec.column(orders, "name"))print(vec.column([[1, 2], [3, 4]], 1))

[12.5, 30]["ann", "bob"][2, 4]

Edge cases

• A missing field or a position past the row gives null in that place; filter the nulls out before arithmetic.
• A row of the wrong kind (a list under a string key, a map under an int, a plain value) gives null too, not an error.
• A negative position is null, not counted from the end.
• A string key reads maps only: an int key does not look up "0" in a map.
• The empty list, or null, gives the empty list.

let orders = [{ name: "ann", total: 12.5 }, { name: "bob", total: 30 }, { name: "cy" }]print(vec.column(orders, "total"), vec.column(orders, "missing"))print(vec.column([[1, 2], [3, 4], [5]], 1), vec.column([[1, 2]], -1))print(vec.column([{ a: 1 }, [1, 2], 7], "a"), vec.column([{ a: 1 }, [1, 2], 7], 0))print(vec.column([{ "0": "z" }], 0))print(vec.column([], "x"), vec.column(null, 0))

[12.5, 30, null] [null, null, null][2, 4, null] [null][1, null, null] [null, 1, null][null][] []

Errors

A key that is neither a string nor an int, or rows that are not a list, are runtime errors, not error values.

print(vec.column([{ a: 1 }], null))

line 1: `vec.column` expects a str or int key as argument 2, got null

print(vec.column("rows", "a"))

line 1: `vec.column` expects a list as argument 1, got str

Chaining

rows | vec.column("total") reads well in a pipeline, with the statistics after it:

let orders = [{ name: "ann", total: 12.5 }, { name: "bob", total: 30 }, { name: "cy" }]print(orders | vec.column("total") | filter((t) => t != null) | sum)print(orders | vec.column("name") | join(", "))

42.5ann, bob, cy

See also

vec.transpose, map, stats.describe, vec.matmul

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