REPOGEO REPORT · LITE

youssefHosni/Efficient-Python-for-Data-Scientists-Book

Default branch main · commit 2507c7f7 · scanned 6/15/2026, 12:27:43 AM

GitHub: 579 stars · 136 forks

AI VISIBILITY SCORE

15 /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

0 / 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 youssefHosni/Efficient-Python-for-Data-Scientists-Book, 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

Reposition the README's opening to clarify it's a book/guide for optimization

Why:

CURRENT

## Efficient Python for Data Scientists Book ##
Learn how to write efficient Python code as a data scientist. You can buy from here

COPY-PASTE FIX

## Efficient Python for Data Scientists: The Official Book Repository ##
This repository provides the code examples and resources for the book 'Efficient Python for Data Scientists', a comprehensive guide to writing high-performance Python code for data science tasks. Learn practical techniques to optimize your data processing, algorithms, and overall Python scripts.

highlicense#2

Add a LICENSE file to the repository

Why:

COPY-PASTE FIX

Create a LICENSE file (e.g., MIT or Apache-2.0) in the repository root to specify usage terms for the code examples.

mediumtopics#3

Refine repository topics to emphasize 'optimization' and 'book'

Why:

CURRENT

data-science, numpy, pandas, python

COPY-PASTE FIX

data-science, python-optimization, performance-tuning, efficient-coding, data-science-book, python-for-data-scientists

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 youssefHosni/Efficient-Python-for-Data-Scientists-Book

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

NumPy

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

NumPy · recommended 1×
Pandas · recommended 1×
Numba · recommended 1×
Cython · recommended 1×
Dask · recommended 1×

CATEGORY QUERY
How to optimize Python code for faster data processing in data science projects?
you: not recommended
AI recommended (in order):
1. NumPy
2. Pandas
3. Numba
4. Cython
5. Dask
6. Polars
7. PyPy
AI recommended 7 alternatives but never named youssefHosni/Efficient-Python-for-Data-Scientists-Book. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are best practices for writing performant Python scripts for large datasets?
you: not recommended
AI recommended (in order):
1. Pandas (pandas-dev/pandas)
2. NumPy (numpy/numpy)
3. Dask (dask/dask)
4. Polars (pola-rs/polars)
5. PySpark (apache/spark)
6. Vaex (vaexio/vaex)
7. Modin (modin-project/modin)
AI recommended 7 alternatives but never named youssefHosni/Efficient-Python-for-Data-Scientists-Book. 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 youssefHosni/Efficient-Python-for-Data-Scientists-Book?
pass
AI did not name youssefHosni/Efficient-Python-for-Data-Scientists-Book — 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?
If a team adopts youssefHosni/Efficient-Python-for-Data-Scientists-Book in production, what risks or prerequisites should they evaluate first?
pass
AI did not name youssefHosni/Efficient-Python-for-Data-Scientists-Book — 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?
In one sentence, what problem does the repo youssefHosni/Efficient-Python-for-Data-Scientists-Book solve, and who is the primary audience?
pass
AI did not name youssefHosni/Efficient-Python-for-Data-Scientists-Book — 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?

Embed your GEO score

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MARKDOWN (README)

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Brand-free category queries5 vs 2 in Lite
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