Row reordering

The sort and cluster verbs change the order of rows. The individual rows are unchanged.

sort

Sort rows according to the given column names. The data frame is sorted by the first column name using subsequent columns to break any ties.

from tabeline import DataFrame

df = DataFrame(
    patient_id=[2, 1, 2, 1, 2, 1],
    t=[0.0, 0.0, 6.0, 6.0, 24.0, 24.0],
    measurement=[6.0, 5.5, 4.2, 4.0, 3.1, 3.0],
)

df.sort("patient_id", "t")
# ┌────────────┬──────┬─────────────┐
# │ patient_id ┆ t    ┆ measurement │
# │ ---        ┆ ---  ┆ ---         │
# │ i64        ┆ f64  ┆ f64         │
# ╞════════════╪══════╪═════════════╡
# │ 1          ┆ 0.0  ┆ 5.5         │
# ├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤
# │ 1          ┆ 6.0  ┆ 4.0         │
# ├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤
# │ 1          ┆ 24.0 ┆ 3.0         │
# ├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤
# │ 2          ┆ 0.0  ┆ 6.0         │
# ├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤
# │ 2          ┆ 6.0  ┆ 4.2         │
# ├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤
# │ 2          ┆ 24.0 ┆ 3.1         │
# └────────────┴──────┴─────────────┘

cluster

Bring together all the rows with the same value under the given columns. A side effect of sort is that all rows with the same key value under some given columns are brought together. If you want this clustering, without the sorting, cluster will bring all the rows with a given key together, but retain the order of first instance of that key.

from tabeline import DataFrame

df = DataFrame(
    patient_id=[2, 1, 2, 1, 2, 1],
    t=[0.0, 0.0, 6.0, 6.0, 24.0, 24.0],
    measurement=[6.0, 5.5, 4.2, 4.0, 3.1, 3.0],
)

df.cluster("patient_id")
shape: (6, 3)
# ┌────────────┬──────┬─────────────┐
# │ patient_id ┆ t    ┆ measurement │
# │ ---        ┆ ---  ┆ ---         │
# │ i64        ┆ f64  ┆ f64         │
# ╞════════════╪══════╪═════════════╡
# │ 2          ┆ 0.0  ┆ 6.0         │
# ├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤
# │ 2          ┆ 6.0  ┆ 4.2         │
# ├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤
# │ 2          ┆ 24.0 ┆ 3.1         │
# ├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤
# │ 1          ┆ 0.0  ┆ 5.5         │
# ├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤
# │ 1          ┆ 6.0  ┆ 4.0         │
# ├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤
# │ 1          ┆ 24.0 ┆ 3.0         │
# └────────────┴──────┴─────────────┘