Key differences

  • PyGWalker has 4.9× as many GitHub stars as LIDA (16K vs 3.3K).
  • PyGWalker had more development activity over the last 12 months: 154 commits vs 0.
  • PyGWalker is downloaded 208× as often on PyPI (51.9K vs 250 per week).
  • LIDA is licensed under MIT; PyGWalker under Apache-2.0.
  • LIDA is written primarily in Jupyter Notebook, PyGWalker in Python.
  • LIDA has had no commits since Mar 3, 2024.

By the numbers

  • LIDA
  • PyGWalker
GitHub stars
3.3K 16K
PyPI downloads / week
250 51.9K
Commits, last 12 months
0 154
Contributors
14 26
Forks
381 893
Show data as a table
LIDA vs PyGWalker by the numbers
MetricLIDAPyGWalker
GitHub stars3,28816,001
PyPI downloads / week25051,921
Commits, last 12 months0154
Contributors1426
Forks381893

Development activity

Commits per month to each default branch, last 12 complete months.

  • LIDA
  • PyGWalker
050100150 Nov 2025 Dec Jan 2026 Feb Mar Apr May Jun Jul Aug Sep Oct
050100150 Nov 2025 Feb 2026 May Aug
Show data as a table
LIDA vs PyGWalker: commits per month
MonthLIDAPyGWalker
Nov 202503
Dec 202507
Jan 202600
Feb 202601
Mar 202604
Apr 202601
May 202600
Jun 20260134
Jul 202603
Aug 202600
Sep 202601
Oct 202600

Side by side

AttributeLIDAPyGWalker
DescriptionGenerates visualizations and infographics from data with large language models, from Microsoft.Turns dataframes into a drag-and-drop visual analysis UI in Jupyter, based on Graphic Walker.
CategoryPython exploratory data analysis & profiling toolsPython exploratory data analysis & profiling tools
LicenseMITApache-2.0
LanguageJupyter NotebookPython
StatusInactiveActive
Latest release–0.5.0.1 ()
Last commit
Repository created
Open issues7964
Install
pip install lida
pip install pygwalker

Which should you choose?

Popularity and activity are only part of the story. Consider which ecosystem you work in, the chart types and interactions you need, how much data you render, and whether the license fits your project. Both tool pages list alternatives if neither is quite right.

  • LIDA

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

    3.3K starsJupyter NotebookMIT

  • PyGWalker

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

    16K starsPythonApache-2.0

More comparisons