LIDA vs missingno
A data-driven comparison of two Python exploratory data analysis & profiling tools: popularity, development activity, licensing and installation. Updated .
Key differences
- missingno has 1.3× as many GitHub stars as LIDA (4.2K vs 3.3K).
- missingno is downloaded 271× as often on PyPI (67.8K vs 250 per week).
- Both are released under the MIT license.
- LIDA is written primarily in Jupyter Notebook, missingno in Python.
- missingno is the older project: its repository was created in 2016, LIDA's in 2023.
- LIDA has had no commits since Mar 3, 2024.
- missingno has had no commits since Feb 26, 2023.
By the numbers
- LIDA
- missingno
Show data as a table
| Metric | LIDA | missingno |
|---|---|---|
| GitHub stars | 3,288 | 4,212 |
| PyPI downloads / week | 250 | 67,765 |
| Commits, last 12 months | 0 | 0 |
| Contributors | 14 | 16 |
| Forks | 381 | 519 |
Development activity
Commits per month to each default branch, last 12 complete months.
- LIDA
- missingno
Show data as a table
| Month | LIDA | missingno |
|---|---|---|
| Nov 2025 | 0 | 0 |
| Dec 2025 | 0 | 0 |
| Jan 2026 | 0 | 0 |
| Feb 2026 | 0 | 0 |
| Mar 2026 | 0 | 0 |
| Apr 2026 | 0 | 0 |
| May 2026 | 0 | 0 |
| Jun 2026 | 0 | 0 |
| Jul 2026 | 0 | 0 |
| Aug 2026 | 0 | 0 |
| Sep 2026 | 0 | 0 |
| Oct 2026 | 0 | 0 |
Side by side
| Attribute | LIDA | missingno |
|---|---|---|
| Description | Generates visualizations and infographics from data with large language models, from Microsoft. | Provides flexible toolset of data-visualization utilities that allows quick visual summary of the completeness of your dataset, based on matplotlib. |
| Category | Python exploratory data analysis & profiling tools | Python exploratory data analysis & profiling tools |
| License | MIT | MIT |
| Language | Jupyter Notebook | Python |
| Status | Inactive | Inactive |
| Latest release | – | 0.5.2 () |
| Last commit | ||
| Repository created | ||
| Open issues | 79 | 13 |
| Install | pip install lida | pip install missingno |
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.