The number of test units (aligned rows).
Comparison.n: int
A comparison aligns the rows of the two tables and gives each aligned row one status (see the Test Units and Row Statuses section of compare()). n is the total, so it’s always the sum of the values in status_counts and of n_passed and n_failed. It’s the denominator to use for any fraction of rows that pass or fail.
n isn’t the row count of either table. A row that’s in both tables counts once, rows in only one table count once each, and a duplicated key counts as many units as the larger of its two occurrence counts. The row counts of the two tables are available as n_source_rows and n_target_rows.
These two tables of weather station readings have four rows each, but only three stations in common.
import pointblank as pb
import polars as pl
readings_v1 = pl.DataFrame(
{"station": ["S1", "S2", "S3", "S4"], "temp": [12.1, 14.0, 9.8, 11.2]}
)
readings_v2 = pl.DataFrame(
{"station": ["S1", "S2", "S3", "S5"], "temp": [12.1, 14.3, 9.8, 8.0]}
)
comparison = pb.compare(readings_v1, readings_v2, keys="station")
comparison.n, comparison.n_source_rows, comparison.n_target_rows(5, 4, 4)There are five test units: the three shared stations, S4 (only in the source), and S5 (only in the target). Dividing by n gives the fraction of rows that failed:
Three of the five units failed: S2 changed, S4 is missing, and S5 is extra.