data-analysis

Compute descriptive statistics for a CSV dataset by loading the file and calculating mean, median, mode, standard deviation, min, max, and percentiles. The tool validates the schema and outputs a clear Markdown report containing all numeric column metrics.

Hypothesis testing and correlation analysis are supported for database exports. The tool identifies correlations and trends across variables, optionally runs basic hypothesis tests, and flags data quality issues or anomalies within the structured dataset.

Detecting anomalies in time-series data is handled by applying descriptive statistics and pattern identification to the loaded dataset. The tool flags data quality issues and outputs evidence-backed findings suitable for stakeholder reporting.

TSV files and categorical data are fully supported for analysis. The tool validates the presence and schema of the loaded dataset, computes statistics across numeric, categorical, and time-series data, and supports grouping or segmentation.

Generate an insights report from raw structured data by loading the dataset and computing descriptive statistics, correlations, and patterns. The tool automatically produces a concise, evidence-backed Markdown report suitable for stakeholders.

Basic hypothesis tests are limited to standard statistical validation on structured datasets like CSVs and TSVs. The tool focuses on descriptive statistics, correlations, and pattern identification rather than advanced predictive modeling or machine learning algorithms.