FreePublished on GitHub

data-science-python

Use the DataSciencePython tutorial/example collection through modern self-contained helpers for Python data-science resources, statsmodels logistic regression, scikit-learn Kaggle-style tabular classifiers, and Twitter JSONL extraction.

The English summary is being prepared. Showing the original description.

VectorSpaceLab/AREX-Skill

Works withX (Twitter)

See how to install

Files included (32)

SKILL.md3.5 KB
references/environment.md2.0 KB
references/repo-provenance.md2.1 KB
references/repo-routing-metadata.json522 B
references/troubleshooting.md2.7 KB
scripts/check_data_science_python_env.py2.8 KB
sub-skills/kaggle-linear-models/references/api-reference.md3.9 KB
sub-skills/kaggle-linear-models/references/data-formats.md3.5 KB
sub-skills/kaggle-linear-models/references/troubleshooting.md5.0 KB
sub-skills/kaggle-linear-models/references/workflows.md6.9 KB
sub-skills/kaggle-linear-models/scripts/categorical_logistic_submission.py5.4 KB
sub-skills/kaggle-linear-models/scripts/hashed_logistic_sgd.py7.8 KB
sub-skills/kaggle-linear-models/scripts/make_tiny_fixtures.py5.9 KB
sub-skills/kaggle-linear-models/scripts/sklearn_svm_submission.py3.5 KB
sub-skills/kaggle-linear-models/SKILL.md3.9 KB
sub-skills/statsmodels-logit-workflow/references/data-formats.md1.7 KB
sub-skills/statsmodels-logit-workflow/references/data/admissions_test.csv1.5 KB
sub-skills/statsmodels-logit-workflow/references/data/admissions_train.csv4.9 KB
sub-skills/statsmodels-logit-workflow/references/troubleshooting.md1.9 KB
sub-skills/statsmodels-logit-workflow/references/workflows.md1.9 KB
sub-skills/statsmodels-logit-workflow/scripts/statsmodels_admission_logit.py11.1 KB
sub-skills/statsmodels-logit-workflow/SKILL.md1.5 KB
sub-skills/tutorial-resource-map/references/python-basics.md2.5 KB
sub-skills/tutorial-resource-map/references/topic-index.md3.4 KB
sub-skills/tutorial-resource-map/references/troubleshooting.md1.7 KB
sub-skills/tutorial-resource-map/SKILL.md1.8 KB
sub-skills/twitter-json-workflow/references/data-formats.md1.7 KB
sub-skills/twitter-json-workflow/references/troubleshooting.md2.1 KB
sub-skills/twitter-json-workflow/references/workflows.md1.8 KB
sub-skills/twitter-json-workflow/scripts/extract_tweet_text.py6.1 KB
sub-skills/twitter-json-workflow/scripts/twitter_stream_template.py4.5 KB
sub-skills/twitter-json-workflow/SKILL.md2.6 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

DataSciencePython

Use this repo skill when the task names DataSciencePython or asks for a safe, modern way to use its historical Python data-science tutorial list and standalone examples.

This repository is not an installable Python package. It is a curated README plus legacy scripts. Use the generated sub-skills and bundled helper scripts instead of running the original Python 2-era files directly.

Start here

Read references/repo-provenance.md when checking staleness against a checkout.
Read references/environment.md before running helper scripts.
Run scripts/check_data_science_python_env.py when dependency availability is uncertain.
Route to the smallest matching sub-skill below.

Route map

User intent	Load this sub-skill	Why
Navigate the README's Python/data science/pandas/sklearn/ML/NLP resource categories or modernize the tiny Python basics snippets.	`sub-skills/tutorial-resource-map/SKILL.md`	Distills the tutorial index and Python 2-era snippets without relying on external links being live.
Fit the admissions logistic-regression example with pandas and statsmodels, including dummy variables, an intercept, predictions, and optional plots.	`sub-skills/statsmodels-logit-workflow/SKILL.md`	Owns the copied admissions CSV fixtures and modernized `statsmodels_admission_logit.py` helper.
Run Kaggle-style dense SVM, hashed SGD logistic regression, or one-hot categorical LogisticRegression examples.	`sub-skills/kaggle-linear-models/SKILL.md`	Modernizes the legacy scikit-learn/Criteo/Amazon examples and supplies tiny fixture generation.
Extract text from stored Twitter/X JSON-lines data or plan an optional safe live-streaming attempt.	`sub-skills/twitter-json-workflow/SKILL.md`	Replaces local R/Windows/Tweepy examples with offline extraction and credential-safe streaming guidance.

Dependency quick check

From this generated skill root:

python scripts/check_data_science_python_env.py

For optional plot output, add:

python scripts/check_data_science_python_env.py --check-plots

For the optional live-stream template, add:

python scripts/check_data_science_python_env.py --check-tweepy

Important operating constraints

Treat README links as topic signals, not guaranteed live URLs.
Do not instruct future agents to run original source scripts; the bundled helpers are the runtime surface.
Do not assume pip install -e . works; there is no package metadata in the source snapshot.
Keep live Twitter/X collection opt-in only. It requires user-provided credentials, Tweepy compatibility, network access, and explicit authorization to connect.
Use tiny bundled/generated fixtures for smoke tests when the original Kaggle/Amazon data files are missing.

Cross-cutting references

references/environment.md explains the public dependency set and compatibility notes.
references/troubleshooting.md covers missing package metadata, legacy APIs, missing competition data, stale links, and credentialed workflows.
references/repo-routing-metadata.json contains managed router metadata for a later import transaction.

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

More skills from this repository

3d-resnets-pytorch

Free

Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.

The English summary is being prepared. Showing the original description.

VectorSpaceLab/AREX-Skill338Updated Sep 3, 2026

3ddfa

Free

Guide 3DDFA Python inference, geometry rendering, training/evaluation, and optional C++ ONNX workflows for 3D dense face alignment.

The English summary is being prepared. Showing the original description.

VectorSpaceLab/AREX-Skill338Updated Sep 3, 2026

3ddfa-v2

Free

Routes 3DDFA_V2 face-alignment setup, still-image demos, video tracking, and ONNX benchmarking workflows.

The English summary is being prepared. Showing the original description.

VectorSpaceLab/AREX-Skill338Updated Sep 3, 2026

ab3dmot

Free

Operate AB3DMOT 3D multi-object tracking workflows for KITTI and nuScenes data, tracking, evaluation, and visualization.

The English summary is being prepared. Showing the original description.

VectorSpaceLab/AREX-Skill338Updated Sep 3, 2026

accelerate

Free

Use Hugging Face Accelerate for PyTorch training-loop migration, distributed launch/configuration, DeepSpeed/FSDP/TPU backend setup, big-model inference/offload, checkpointing, tracking, and troubleshooting.

The English summary is being prepared. Showing the original description.

VectorSpaceLab/AREX-Skill338Updated Sep 3, 2026

acme

Free

Route Acme reinforcement-learning framework tasks across core loops, replay/data, JAX agents, and TensorFlow/Sonnet agents.

The English summary is being prepared. Showing the original description.

VectorSpaceLab/AREX-Skill338Updated Sep 3, 2026

See all skills by VectorSpaceLab

Report a problem with this skill

Install

Install with a command

npx skills add https://github.com/VectorSpaceLab/AREX-Skill --skill data-science-python

Paste it into your terminal and run it (requires Node.js). You can choose which agents to install it for, such as Claude Code or Codex.

Ask your agent

Please install the following Agent Skill.
https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/data-science-python

First review SKILL.md and the bundled files and confirm there is nothing suspicious (such as sending data externally or reading credentials). Then place it in ~/.claude/skills/data-science-python/ for Claude Code, or ~/.agents/skills/data-science-python/ for Codex.

Send this text to Claude Code or Codex as is. It checks the contents before installing.

View source on GitHub

Repository: VectorSpaceLab/AREX-Skill
Stars: 338
Forks: 26
Category: Data & AI
License: Apache-2.0
Original language: English
Last updated: Sep 3, 2026

A skill is a set of instructions and scripts for an agent. cccskills does not guarantee that skills are safe. Review the contents before you install.