AwesomeDataviz

Exploratory data analysis tools

Profile, explore and find patterns in a dataset quickly. 9 tools, ranked by GitHub stars and updated .

Tools for the first look at a dataset: automatic profiling reports, drag-and-drop exploration interfaces and automated insight discovery, for when you do not yet know which chart you need.

By GitHub stars, the most popular data exploration tools here are Apache Superset (75K stars), PyGWalker (16K stars), and ydata-profiling (13.7K stars). 9 of 9 had commits in the last 90 days.
1 Apache Superset

Data exploration and visualization platform with a no-code chart builder, SQL IDE and dashboards.

 Dashboards & BI 75K 5,646 Apache-2.0
2 PyGWalker

Turns dataframes into a drag-and-drop visual analysis UI in Jupyter, based on Graphic Walker.

 Python 16K 154 Apache-2.0
3 ydata-profiling

Generates statistical analytic reports with visualization for quick data analysis (formerly pandas-profiling).

 Python 13.7K 8 MIT
4 SandDance

Visual data exploration and presentation with animated unit visualizations, from Microsoft Research.

 Apps & tools 7.1K 67 MIT
5 Panel

Data exploration and web app framework for Python that works with many plotting libraries.

 Python 5.8K 392 BSD-3-Clause
6 Observable Plot

A JavaScript library for exploratory data visualization.

 JS charting 5.4K 38 ISC
7 RATH

Automatic Exploratory Data Analysis & Data Visualization tool which is powered by an AI-assisted Augmented Analytics engine.

 Apps & tools 4.7K 29 AGPL-3.0
8 Graphic Walker

An embeddable React component that functions as an open source alternative to Tableau, which allows data scientists to analyze data and visualize patterns with simple drag-and-drop operations.

 React 3.3K 51 Apache-2.0
9 Squey

Visualization software for exploring and understanding large amounts of tabular data (using parallel coordinates, timeseries and scatter plots).

 Apps & tools 23 – MIT

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Frequently asked questions

What is the most popular data exploration tool?

By GitHub stars, Apache Superset is the most popular, with 75K stars, followed by PyGWalker (16K) and ydata-profiling (13.7K).

Which data exploration tools are actively maintained?

9 of the 9 tools listed had commits in the last 12 months, including Apache Superset, PyGWalker, ydata-profiling, SandDance, and Panel. Each tool page shows monthly commit activity.

Are these data exploration tools free and open source?

9 of the 9 tools listed use an OSI-approved open-source license. The most common license here is Apache-2.0.

Missing a tool? Add it with a one-line pull request to the README.