Kanaries

PyGWalker is a Python library that converts any pandas or polars DataFrame into a fully interactive Tableau-style visual analytics interface with a single line of code inside a Jupyter Notebook.

Users can drag and drop column names onto chart axes, apply filters, switch chart types, and annotate or clean data all without leaving their notebook environment.

It also supports natural language queries, allowing analysts to describe the chart they want in plain English and letting the AI generate it automatically.

RATH (now evolved into Kanaries' AI Workspace) is the automated exploratory data analysis engine that powers one-click insight discovery.

It uses an augmented analytics pipeline to scan datasets, identify statistically significant patterns, surface related insights based on the user's current focus, and highlight potential causal relationships dramatically accelerating the time from raw data to meaningful conclusions.

On the data infrastructure side, Kanaries integrates natively with high-performance query engines including DuckDB for local large-scale data processing, as well as external cloud warehouses like Snowflake and ClickHouse for enterprise-scale analytics.

The Data Painter feature enables visual data cleaning, letting users select and remove outliers, clusters, or anomalous patterns directly on a chart rather than writing filter logic.