Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
First read
quantopian/pandas shows signs of reuse beyond stars, yet recent activity is softer. Read the repository as a potentially durable dependency, but verify maintenance rhythm before treating it as a default choice.
3 public stars in the current GitStar snapshot.
Needs a narrower context read
Last commit Sep 26, 2019.
Stale activity
pypi gives the strongest production-style signal.
7.6M/week
One or more key signals are partial, so GitStar keeps the interpretation conservative.
Partial snapshot
Snapshot facts
Compare lens
firecrawl/firecrawl and pandas-dev/pandas are the closest comparison targets GitStar found. A side-by-side comparison usually tells you more than a single raw rank.
Signal trail
Read the recent motion first. This block is for deciding whether the repository still looks alive, compounding, or flattening before you trust stars alone.
Package reality
GitStar found pypi:pandas. Package traffic can help separate visible repositories from dependencies that are quietly used in real workflows.
Validation note
GitStar can summarize public signals for quantopian/pandas, but the GitHub repository is still the primary place to confirm release cadence, issue activity, and maintainer intent.
GitStar uses the strongest linked package signal below when it reads Hype vs Reality for this repository.
GitStar surfaces public popularity and package signals. These rankings are not endorsements, security reviews, or investment advice.
Why this rank
This repository stands out because it combines package adoption.
Reconstructed from current stars and cached daily/weekly/monthly deltas.
Package adoption looks stronger than headline visibility alone suggests.
The repo may matter more in real dependency graphs than its current star narrative implies, so compare it against louder peers before dismissing it.
Shares the libraries category footprint with quantopian/pandas, so the comparison is closer to a same-problem decision than a same-language coincidence.
Shares the libraries category footprint with quantopian/pandas, so the comparison is closer to a same-problem decision than a same-language coincidence.
Shares the libraries category footprint with quantopian/pandas, so the comparison is closer to a same-problem decision than a same-language coincidence.
Shares the libraries category footprint with quantopian/pandas, so the comparison is closer to a same-problem decision than a same-language coincidence.
GitStar picked firecrawl + pandas as the closest next comparison from the related repository set.
[](https://gitstar.space/repo/quantopian/pandas)<a href="https://gitstar.space/repo/quantopian/pandas"><img src="https://gitstar.space/api/badge/quantopian/pandas" alt="GitStar"></a>Supercharge your AI agents with data from the web and beyond. Building the library for superintelligence. 🔥
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
A unified trading API with more than 100 crypto exchanges and prediction markets in JavaScript / TypeScript / Python / C# / PHP / Go / Java / Rust
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
A command line tool and library for transferring data with URL syntax, supporting DICT, FILE, FTP, FTPS, GOPHER, GOPHERS, HTTP, HTTPS, IMAP, IMAPS, LDAP, LDAPS, MQTT, MQTTS, POP3, POP3S, RTSP, SCP, SFTP, SMB, SMBS, SMTP, SMTPS, TELNET, TFTP, WS and WSS. libcurl offers a myriad of powerful features
📚 C/C++ 技术面试基础知识总结,包括语言、程序库、数据结构、算法、系统、网络、链接装载库等知识及面试经验、招聘、内推等信息。This repository is a summary of the basic knowledge of recruiting job seekers and beginners in the direction of C/C++ technology, including language, program library, data structure, algorithm, system, network, link loading library, interview experience, recruitment, recommendation, etc.
This page provides a quick overview of quantopian/pandas based on GitStar's cached data. The signal chart reconstructs approximate checkpoints from current stars plus cached daily, weekly, and monthly star deltas, so it is best read as directional context rather than as a precise historical audit log.
Want to show your project's ranking? Copy the badge embed code above and add it to your README.