# Mutate the Table in a Validation Step
Pointblank Validation
2026-07-13|17:45:09 Polars
STEP COLUMNS VALUES TBL EVAL UNITS PASS FAIL W E C EXT
#4CA64C 1
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" /> col_vals_between()
a [3, 6] ✓ 1 1
1.00		 0
0.00		 -- -- -- --
#4CA64C 2
col_vals_eq()
b_len 9 ✓ 13 13
1.00		 0
0.00		 -- -- -- --
2026-07-13 17:45:09 UTC< 1 s2026-07-13 17:45:09 UTC
Notes

Step 1 (pre_applied) Precondition applied: table dimensions [13 rows, 8 columns] → [1 row, 1 column].

Step 2 (pre_applied) Precondition applied: table dimensions [13 rows, 8 columns] → [13 rows, 9 columns].

Step 2 (syn_target_col) Synthetic target column b_len created via preprocessing.
``` python import pointblank as pb import polars as pl import narwhals as nw # Define preprocessing functions def get_median_a(df): """Use a Polars expression to aggregate column `a`.""" return df.select(pl.median("a")) def add_b_length_column(df): """Use Narwhals to add a string length column `b_len`.""" return ( nw.from_native(df) .with_columns(b_len=nw.col("b").str.len_chars()) ) validation = ( pb.Validate( data=pb.load_dataset(dataset="small_table", tbl_type="polars") ) .col_vals_between( columns="a", left=3, right=6, pre=get_median_a ) .col_vals_eq( columns="b_len", value=9, pre=add_b_length_column ) .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