numeric_distribution_check

To validate numeric field distributions in a CSV file, run the skill in numeric mode to compare statistical measures like mean, standard deviation, median, and percentiles against your specified constraints. This ensures your structured data meets quality criteria.

Checking categorical frequency anomalies involves analyzing category frequencies in structured data to detect unreasonable category counts or single category dominance. This skill automates that validation process for files like CSV, TSV, and Excel.

Yes, you can validate data distributions in Excel and SPSS files because the skill uses pandas for data manipulation. It supports structured data formats including CSV, TSV, Excel, and SPSS to verify statistical and categorical criteria.

Yes, you need to specify constraints to run statistical checks because the skill compares your data's actual statistical measures and category frequencies against those predefined parameters to identify anomalies during data preprocessing.

Categorical frequency validation flags single category dominance because it indicates an imbalanced distribution, which violates quality control constraints. The skill detects this anomaly by analyzing category frequencies within your structured data files.