RRepoGEO

REPOGEO REPORT · LITE

PandaAI-Tech/panda_factor

Default branch main · commit c714e189 · scanned 5/12/2026, 11:13:03 PM

GitHub: 2,651 stars · 417 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface PandaAI-Tech/panda_factor, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    PandaFactor is a high-performance quantitative factor library for financial data analysis, technical indicator calculation, and factor construction, supporting both Python and formula-based factor definition.
  • highreadme#2
    Reposition README's H1 and opening paragraph

    Why:

    CURRENT
    # PandaFactor - PandaAI量化因子库

## PandaAI首届因子大赛已启动，你的Alpha值得被看见
“没有一个alpha，一开始就是alpha”

“开始量化，最好是十年前，其次是现在”

“如果没有天赋，那就一直重复”

“看似不起眼的数学，会在将来的某一天，突然让你看到坚持的意义”

“一切都很好，我听到自己，向上的声音”

“市场会惩罚，模糊的愿望，奖励清晰的请求”

“你正在寻找的因子，此刻也在寻找你”

点击报名
## 概述

PandaFactor 提供了一系列高性能的量化算子，用于金融数据分析、技术指标计算和因子构建，并且提供了一系列的可视化图表.
    COPY-PASTE FIX
    # PandaFactor - 高性能量化因子库，用于金融数据分析与因子构建

PandaFactor 提供了一系列高性能的量化算子，用于金融数据分析、技术指标计算和因子构建，并且提供了一系列的可视化图表。它支持Python和公式两种方式编写因子，旨在帮助量化分析师和数据科学家高效地进行因子研究和策略开发。

## PandaAI首届因子大赛已启动，你的Alpha值得被看见
“没有一个alpha，一开始就是alpha”

“开始量化，最好是十年前，其次是现在”

“如果没有天赋，那就一直重复”

“看似不起眼的数学，会在将来的某一天，突然让你看到坚持的意义”

“一切都很好，我听到自己，向上的声音”

“市场会惩罚，模糊的愿望，奖励清晰的请求”

“你正在寻找的因子，此刻也在寻找你”

点击报名

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface PandaAI-Tech/panda_factor
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NumPy
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. NumPy · recommended 2×
  2. TA-Lib · recommended 2×
  3. pandas · recommended 1×
  4. scikit-learn · recommended 1×
  5. statsmodels · recommended 1×
  • CATEGORY QUERY
    What are effective Python libraries for constructing custom quantitative financial factors?
    you: not recommended
    AI recommended (in order):
    1. pandas
    2. NumPy
    3. TA-Lib
    4. scikit-learn
    5. statsmodels
    6. Alphalens
    7. Pyfolio

    AI recommended 7 alternatives but never named PandaAI-Tech/panda_factor. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a Python framework for high-performance financial data processing and indicator calculation.
    you: not recommended
    AI recommended (in order):
    1. Pandas
    2. Numba
    3. NumPy
    4. TA-Lib
    5. vectorbt
    6. Dask
    7. PyTorch
    8. TensorFlow
    9. Polars

    AI recommended 9 alternatives but never named PandaAI-Tech/panda_factor. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of PandaAI-Tech/panda_factor?
    pass
    AI named PandaAI-Tech/panda_factor explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts PandaAI-Tech/panda_factor in production, what risks or prerequisites should they evaluate first?
    pass
    AI named PandaAI-Tech/panda_factor explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo PandaAI-Tech/panda_factor solve, and who is the primary audience?
    pass
    AI named PandaAI-Tech/panda_factor explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite