# Custom Validation with specially()
Pointblank Validation
2026-07-13|17:45:42 Polars
STEP COLUMNS VALUES TBL EVAL UNITS PASS FAIL W E C EXT
#4CA64C66 1
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All values in column 'a' should be within 2 std devs of mean

 EXPR ✓ 2000 1947
0.97		 53
0.03		 -- -- -- --
#4CA64C 2
specially()

All values in column 'c' should be within 3 std devs of mean

 EXPR ✓ 2000 2000
1.00		 0
0.00		 -- -- -- --
2026-07-13 17:45:42 UTC< 1 s2026-07-13 17:45:42 UTC
``` python import pointblank as pb import polars as pl def within_std_deviations(df, column, n_std=2): """Check if all values are within n standard deviations of the mean""" mean_val = df[column].mean() std_val = df[column].std() lower_bound = mean_val - (n_std * std_val) upper_bound = mean_val + (n_std * std_val) # Add a boolean column and return the modified DataFrame return df.with_columns( pl.col(column).is_between(lower_bound, upper_bound, closed="both").alias("validation_result") ) validation = ( pb.Validate( data=pb.load_dataset(dataset="game_revenue", tbl_type="polars") ) .specially( expr=lambda df: within_std_deviations(df, column="session_duration", n_std=2), brief="All values in column 'a' should be within 2 std devs of mean" ) .specially( expr=lambda df: within_std_deviations(df, column="session_duration", n_std=3), brief="All values in column 'c' should be within 3 std devs of mean" ) .interrogate() ) validation ``` Preview of Input Table
PolarsRows2,000Columns11
player_id String
session_id String
session_start Datetime
time Datetime
item_type String
item_name String
item_revenue Float64
session_duration Float64
start_day Date
acquisition String
country String
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