Creating new columns

The mutate and transmute verbs create new columns based on expressions of existing columns. The number of rows is unchanged.

mutate

Create new columns or redefine existing columns. This takes an arbitrary number of named arguments. The name of each argument is the name of a column. The value of the argument is an expression that provides a definition for that column. If the column name already exists, that column will be replaced by the evaluation of the new definition. If the column name does not already exist, the new column will be appended to the existing columns.

from tabeline import DataFrame

df = DataFrame(
    name=["wide", "tall", "square"],
    width=[5, 2, 3],
    height=[1, 4, 3],
)

df.mutate(area="width * height")
# ┌────────┬───────┬────────┬──────┐
# │ name   ┆ width ┆ height ┆ area │
# │ ---    ┆ ---   ┆ ---    ┆ ---  │
# │ str    ┆ i64   ┆ i64    ┆ i64  │
# ╞════════╪═══════╪════════╪══════╡
# │ wide   ┆ 5     ┆ 1      ┆ 5    │
# ├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┤
# │ tall   ┆ 2     ┆ 4      ┆ 8    │
# ├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┤
# │ square ┆ 3     ┆ 3      ┆ 9    │
# └────────┴───────┴────────┴──────┘

transmute

Just like mutate except the existing columns are not kept. This is identical to mutate followed by select on the newly defined columns.

from tabeline import DataFrame

df = DataFrame(
    name=["wide", "tall", "square"],
    width=[5, 2, 3],
    height=[1, 4, 3],
)

df.transmute(name="name", area="width * height")
# shape: (3, 2)
# ┌────────┬──────┐
# │ name   ┆ area │
# │ ---    ┆ ---  │
# │ str    ┆ i64  │
# ╞════════╪══════╡
# │ wide   ┆ 5    │
# ├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┤
# │ tall   ┆ 8    │
# ├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┤
# │ square ┆ 9    │
# └────────┴──────┘