Apply Validation Rules to Multiple Columns

Create multiple validation steps by using a list of column names with columns=.

Pointblank Validation
2025-01-20|18:18:13 Polars
		STEP	COLUMNS	VALUES	TBL	EVAL	UNITS	PASS	FAIL	W	S	N	EXT
#4CA64C	1	col_vals_ge()	a	0		✓	13	13 1.00	0 0.00	—	—	—	—
#4CA64C66	2	col_vals_ge()	c	0		✓	13	11 0.85	0 0.00	—	—	—	—
#4CA64C	3	col_vals_ge()	d	0		✓	13	13 1.00	0 0.00	—	—	—	—
#4CA64C	4	col_exists()	date_time	—		✓	1	1 1.00	0 0.00	—	—	—	—
#4CA64C	5	col_exists()	date	—		✓	1	1 1.00	0 0.00	—	—	—	—
2025-01-20 18:18:13 UTC< 1 s2025-01-20 18:18:13 UTC

import pointblank as pb

validation = (
    pb.Validate(
        data=pb.load_dataset(dataset="small_table", tbl_type="polars")
    )
    .col_vals_ge(columns=["a", "c", "d"], value=0)   # check values in 'a', 'c', and 'd'
    .col_exists(columns=["date_time", "date"])       # check for the existence of two columns
    .interrogate()
)

validation

Preview of Input Table

PolarsRows13Columns8
	date_time Datetime	date Date	a Int64	b String	c Int64	d Float64	e Boolean	f String
1	2016-01-04 11:00:00	2016-01-04	2	1-bcd-345	3	3423.29	True	high
2	2016-01-04 00:32:00	2016-01-04	3	5-egh-163	8	9999.99	True	low
3	2016-01-05 13:32:00	2016-01-05	6	8-kdg-938	3	2343.23	True	high
4	2016-01-06 17:23:00	2016-01-06	2	5-jdo-903	None	3892.4	False	mid
5	2016-01-09 12:36:00	2016-01-09	8	3-ldm-038	7	283.94	True	low
6	2016-01-11 06:15:00	2016-01-11	4	2-dhe-923	4	3291.03	True	mid
7	2016-01-15 18:46:00	2016-01-15	7	1-knw-093	3	843.34	True	high
8	2016-01-17 11:27:00	2016-01-17	4	5-boe-639	2	1035.64	False	low
9	2016-01-20 04:30:00	2016-01-20	3	5-bce-642	9	837.93	False	high
10	2016-01-20 04:30:00	2016-01-20	3	5-bce-642	9	837.93	False	high
11	2016-01-26 20:07:00	2016-01-26	4	2-dmx-010	7	833.98	True	low
12	2016-01-28 02:51:00	2016-01-28	2	7-dmx-010	8	108.34	False	low
13	2016-01-30 11:23:00	2016-01-30	1	3-dka-303	None	2230.09	True	high