Apply Validation Rules to Multiple Columns

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

Pointblank Validation
2025-01-31|16:28:29
Polars
STEP COLUMNS VALUES TBL EVAL UNITS PASS FAIL W S N EXT
#4CA64C 1
col_vals_gte
col_vals_ge() 		a 0 ✓ 13 13
1.00		 0
0.00		 — — — —
#4CA64C66 2
col_vals_gte
col_vals_ge() 		c 0 ✓ 13 11
0.85		 2
0.15		 — — —
#4CA64C 3
col_vals_gte
col_vals_ge() 		d 0 ✓ 13 13
1.00		 0
0.00		 — — — —
#4CA64C 4
col_exists
col_exists() 		date_time — ✓ 1 1
1.00		 0
0.00		 — — — —
#4CA64C 5
col_exists
col_exists() 		date — ✓ 1 1
1.00		 0
0.00		 — — — —
2025-01-31 16:28:29 UTC< 1 s2025-01-31 16:28:29 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