Is Pandas Safe?
Pandas — Nerq Trust Score 90.0/100 (A+ grade). Based on analysis of 2 trust dimensions, it is considered safe to use. Last updated: 2026-03-30.
Yes, Pandas is safe to use. Pandas is a Python package with a Nerq Trust Score of 90.0/100 (A+), based on 3 independent data dimensions. It is recommended for production use. Security: 90/100. Popularity: 100/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-30. Machine-readable data (JSON).
Is Pandas safe?
YES — Pandas has a Nerq Trust Score of 90.0/100 (A+). It meets Nerq's trust threshold with strong signals across security, maintenance, and community adoption. Recommended for production use — review the full report below for specific considerations.
What is Pandas's trust score?
Pandas has a Nerq Trust Score of 90.0/100, earning a A+ grade. This score is based on 2 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Pandas?
Pandas's strongest signal is popularity at 100/100. No known vulnerabilities have been detected. It meets the Nerq Verified threshold of 70+.
What is Pandas and who maintains it?
| Author | Unknown |
| Category | pypi |
| Source | N/A |
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Safety Guide: Pandas
What is Pandas?
Pandas is a Python package — Powerful data structures for data analysis, time series, and statistics.
How to Verify Safety
Run pip audit or safety check. Review on PyPI for download stats.
You can also check the trust score via API: GET /v1/preflight?target=pandas
Key Safety Concerns for Python packages
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Trust Assessment
Pandas has a Nerq Trust Score of 81/100 (A-) and meets Nerq trust threshold. This score is based on automated analysis of security, maintenance, community, and quality signals.
Key Takeaways
- Pandas has a Trust Score of 81/100 (A-).
- Recommended for use — passes trust threshold.
- Always verify independently using the Nerq API.
Detailed Score Analysis
| Dimension | Score |
|---|---|
| Security | 90/100 |
| Privacy | 80/100 |
| Reliability | 90/100 |
| Transparency | 85/100 |
| Maintenance | 60/100 |
Based on 5 dimensions. Data from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard.
What data does Pandas collect?
Pandas is a Python package maintained by Unknown. It receives approximately 137,448,598 weekly downloads. Licensed under BSD 3-Clause License Copyright (c) 2008-2011, AQR Capital Management, LLC, Lambda.
As a development package, Pandas does not directly collect end-user personal data. However, applications built with it may collect data depending on implementation. Privacy score: 80/100.
Review the package's dependencies for potential supply chain risks. Run your package manager's audit command regularly.
Full analysis: Pandas Privacy Report · Privacy review
Is Pandas secure?
Security score: 90/100. Pandas has 0 known vulnerabilities (CVEs) in the National Vulnerability Database. This is a clean record.
Licensed under BSD 3-Clause License Copyright (c) 2008-2011, AQR Capital Management, LLC, Lambda, allowing code inspection. Open-source packages allow independent security review of the source code.
Run your package manager's audit command (`npm audit`, `pip audit`, `cargo audit`) to check for known vulnerabilities in your dependency tree.
Full analysis: Pandas Security Report
How we calculated this score
Pandas's trust score of 90.0/100 (A+) is computed from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 5 independent dimensions: security (90/100), privacy (80/100), reliability (90/100), transparency (85/100), maintenance (60/100). Each dimension is weighted equally to produce the composite trust score.
Nerq analyzes over 7.5 million entities across 26 registries using the same methodology, enabling direct cross-entity comparison. Scores are updated continuously as new data becomes available.
This page was last reviewed on March 30, 2026. Data version: 1.0.
Full methodology documentation · Machine-readable data (JSON API)
Frequently Asked Questions
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Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.