AwesomeDataviz

Python exploratory data analysis & profiling tools

Visual reports and explorers for a whole dataset at once. 6 tools, ranked by GitHub stars and updated .

Tools for a first look at a dataset. ydata-profiling and Sweetviz generate HTML reports with distributions, correlations and missing values, missingno focuses on missing data, and D-Tale and PyGWalker open dataframes in interactive, point-and-click explorers.

By GitHub stars, the most popular Python data exploration tools here are PyGWalker (16K stars), ydata-profiling (13.7K stars), and D-Tale (5.2K stars). 2 of 6 had commits in the last 90 days.
1 PyGWalker

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

 16K 154 Apache-2.0
2 ydata-profiling

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

 13.7K 14 MIT
3 D-Tale

Web-based visual explorer for pandas DataFrames with charts, summaries and correlations.

 5.2K 33 LGPL-2.1
4 missingno Inactive

Provides flexible toolset of data-visualization utilities that allows quick visual summary of the completeness of your dataset, based on matplotlib.

 4.2K 0 MIT
5 LIDA Inactive

Generates visualizations and infographics from data with large language models, from Microsoft.

 3.3K 0 MIT
6 Sweetviz

Generates self-contained HTML reports that visualize and compare datasets for exploratory analysis.

 3.1K 12 MIT

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Frequently asked questions

What is the most popular Python data exploration tool?

By GitHub stars, PyGWalker is the most popular, with 16K stars, followed by ydata-profiling (13.7K) and D-Tale (5.2K).

Which Python data exploration tools are actively maintained?

4 of the 6 tools listed had commits in the last 12 months, including PyGWalker, ydata-profiling, D-Tale, and Sweetviz. Each tool page shows monthly commit activity.

Are these Python data exploration tools free and open source?

6 of the 6 tools listed use an OSI-approved open-source license. The most common license here is MIT.

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