RRepoGEO

REPOGEO REPORT · LITE

r0f1/datascience

Default branch master · commit a85b56a3 · scanned 5/9/2026, 2:33:10 PM

GitHub: 4,621 stars · 711 forks

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 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 r0f1/datascience, 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

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

OVERALL DIRECTION
  • highreadme#1
    Clarify repo's identity as a resource list, not a project or library

    Why:

    CURRENT
    > A curated list of awesome resources for practicing data science using Python, including not only libraries, but also links to tutorials, code snippets, blog posts and talks.
    COPY-PASTE FIX
    > A curated list of awesome resources for practicing data science using Python, including not only libraries, but also links to tutorials, code snippets, blog posts and talks. This repository serves as a comprehensive guide and reference, not a software project or personal code collection.
  • mediumhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://github.com/r0f1/datascience
  • lowtopics#3
    Add 'learning-resources' topic to reinforce repo type

    Why:

    CURRENT
    artificial-intelligence, awesome, awesome-list, bayes, data-analysis, data-mining, data-science, data-visualization, datascience, deep-learning, deeplearning, machine-learning, python, statistics
    COPY-PASTE FIX
    artificial-intelligence, awesome, awesome-list, bayes, data-analysis, data-mining, data-science, data-visualization, datascience, deep-learning, deeplearning, machine-learning, python, statistics, learning-resources

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 r0f1/datascience
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
pandas-dev/pandas
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. pandas-dev/pandas · recommended 1×
  2. numpy/numpy · recommended 1×
  3. matplotlib/matplotlib · recommended 1×
  4. mwaskom/seaborn · recommended 1×
  5. scikit-learn/scikit-learn · recommended 1×
  • CATEGORY QUERY
    What are the best Python libraries and learning resources for starting with data science?
    you: not recommended
    AI recommended (in order):
    1. Pandas (pandas-dev/pandas)
    2. NumPy (numpy/numpy)
    3. Matplotlib (matplotlib/matplotlib)
    4. Seaborn (mwaskom/seaborn)
    5. Scikit-learn (scikit-learn/scikit-learn)
    6. Jupyter Notebook (jupyter/notebook)
    7. JupyterLab (jupyterlab/jupyterlab)
    8. Plotly (plotly/plotly.py)
    9. Bokeh (bokeh/bokeh)
    10. Python for Data Analysis
    11. Kaggle Learn
    12. DataCamp
    13. Coursera
    14. Applied Data Science with Python Specialization
    15. freeCodeCamp.org (freeCodeCamp/freeCodeCamp)
    16. Data Analysis with Python course
    17. Towards Data Science
    18. Medium
    19. Stack Overflow

    AI recommended 19 alternatives but never named r0f1/datascience. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a comprehensive guide to Python tools for data analysis, visualization, and machine learning.
    you: not recommended
    AI recommended (in order):
    1. Pandas
    2. NumPy
    3. SciPy
    4. Polars
    5. Dask
    6. Matplotlib
    7. Seaborn
    8. Plotly
    9. Altair
    10. Bokeh
    11. scikit-learn
    12. TensorFlow
    13. PyTorch
    14. Keras
    15. XGBoost
    16. LightGBM
    17. CatBoost

    AI recommended 17 alternatives but never named r0f1/datascience. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    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 r0f1/datascience?
    pass
    AI named r0f1/datascience explicitly

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

  • If a team adopts r0f1/datascience in production, what risks or prerequisites should they evaluate first?
    pass
    AI named r0f1/datascience 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 r0f1/datascience solve, and who is the primary audience?
    pass
    AI did not name r0f1/datascience — likely talking about a different project

    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
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