linogaliana/python-datascientist
linogaliana/python-datascientist has 187 GitHub stars and 59 forks. Star changes are not measured yet. Last checked 2026-11-14 08:36 UTC. Last push 2026-11-07.
측정된 스타 증가
- in 24h
- 기록 수집 중
- in 7 days
- 기록 수집 중
- in 15 days
- 기록 수집 중
- in 1 month
- 기록 수집 중
서로 겹치는 기간의 순증가량이며 일별 합계가 아닙니다. 측정값이 없으면 비워 둡니다. 스타는 관심도를 나타내며 품질을 보장하지 않습니다.
소개
Dépôt associé au cours Python pour data scientists (ENSAE 2e année)
머신러닝README.md
OriginalData Science with Python

Lino Galiana • Data scientist, Insee (French national statistical institute)
Course given in two top French engineering schools (ENSAE and ENSAI) and available for self-paced learning.
[!NOTE]
This is the English 🇬🇧🇺🇸 version of theREADME. To see the French 🇫🇷 version, click here:
About
This repository hosts the source files for my Python for Data Science, a hands-on course designed to take students from first contact with
Python to practical data science workflows.
It is taught in two French engineering schools in 2n year (Master 1):
- ENSAE since 2021
- ENSAI from 2026
The material combines explanations, examples, and exercises, with an emphasis on reproducible and real-world datasets.
All chapters (notes, examples, and exercises available as Jupyter notebooks) are available at https://pythonds.linogaliana.fr/.
📌 License and attribution
This course is released under the Creative Commons CC BY-NC-SA license .
If you use this course material, please cite:
Galiana, Lino. 2025. Python pour la data science. https://doi.org/10.5281/zenodo.8229676
@book{galiana2025,
author = {Galiana, Lino},
title = {Python pour la data science},
date = {2025},
url = {https://pythonds.linogaliana.fr/},
doi = {10.5281/zenodo.8229676},
langid = {fr}
}
🎨 Gallery
A few examples of figures produced during the course (click to open the course website):
📖 Course content
This course is suitable for both beginners and advanced learners.
The syllabus below is fully clickable and collapsible.
1. Getting started: why Python for data science?
🔗 https://pythonds.linogaliana.fr/en/content/getting-started/
- Getting a functional Python environment for data science
- How to deal with a data set
- Python basics
2. Data wrangling
🔗 https://pythonds.linogaliana.fr/en/content/manipulation/
- Numpy, the foundation of data science
- Introduction to Pandas
- Data wrangling with Pandas
- Spatial data with GeoPandas
- Webscraping with Python
- Retrieving data with APIs
- Mastering regular expressions
- Importing data from Parquet and S3
3. Data visualisation and communication
🔗 https://pythonds.linogaliana.fr/en/content/visualisation/
- Building graphics with Python
- Introduction to cartography
4. Modeling
🔗 https://pythonds.linogaliana.fr/en/content/modelisation/
- Why preprocessing matters
- Evaluating model quality
- Introduction to classification
- Introduction to regression
- Feature selection
- Clustering
5. Natural Language Processing (NLP)
🔗 https://pythonds.linogaliana.fr/en/content/nlp/
- Cleaning and structuring texts
- Bag-of-words approach
- Text embeddings
🔗 Resources
The course content relies heavily on open data, including French datasets (from data.gouv and Insee) and American datasets.
Complementary course with Romain Avouac (@avouacr):
https://ensae-reproductibilite.github.io/website/
🚀 Accessing the course online
[!TIP]
Run examples instantly on SSP Cloud or Google Colab. Here is an example forPandaschapter:
🤝 Contributing
I welcome contributions!
[!NOTE]
See the guide for contributors:
관련 프로젝트 살펴보기
tensorflow/tensorflow
모두를 위한 오픈소스 머신러닝 프레임워크
201,593 스타huggingface/transformers
🤗 Transformers: 텍스트, 비전, 오디오, 멀티모달 분야의 최첨단 머신러닝 모델을 위한 모델 정의 프레임워크로, 추론과 학습을 모두 지원합니다.
168,962 스타AUTOMATIC1111/stable-diffusion-webui
Stable Diffusion 웹 UI
165,312 스타Comfy-Org/ComfyUI
그래프와 노드로 구성된 인터페이스를 갖춘, 가장 강력하고 모듈성이 뛰어난 확산 모델 GUI, API, 백엔드입니다. 세계에서 가장 빠른 로컬 추론 엔진입니다.
146,755 스타










