EdaValidator

Calculates and displays EDA statistics for numeric columns. Uses Rich for formatted console output.

Basic Usage

from epftoolbox2.data.validators import EdaValidator

validator = EdaValidator()
result = validator.validate(df)

Console Output

┏━━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┓
┃ Column      ┃ Min      ┃ Max      ┃ Mean     ┃ Std      ┃
┡━━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━┩
│ load_actual │ 8500.12  │ 25000.45 │ 15234.67 │ 3456.78  │
│ price       │ -5.23    │ 450.00   │ 85.45    │ 45.23    │
└─────────────┴──────────┴──────────┴──────────┴──────────┘

Statistics Included

Statistic	Description
Min	Minimum value
Max	Maximum value
Mean	Average value
Std	Standard deviation
Q25	25th percentile
Q50	Median (50th percentile)
Q75	75th percentile
Nulls	Count of null values

Accessing Statistics Programmatically

result = validator.validate(df)

# Get stats as DataFrame
stats_df = result.stats
print(stats_df)

When to Use

Initial data exploration
Checking for outliers
Verifying data ranges are reasonable