jupyter
jupyter
You cannot share Jupter Notebook's ipynb files with everyone. However, if you convert it to PDF, sharing becomes easier. Here's how to do it.
JupyterLab 4.3.0 and Notebook 7.3.0 have been released! These new minor releases include many enhancements and bug fixes.
The digital age demands for automation and efficiency in the domain of software and applications. Automating repetitive coding tasks and reducing debugging time frees up programmers' time for more strategic work. This can be especially beneficial for businesses and organizations that rely heavily on software development. The recently released AI-powered Python notebook Thread addresses the challenge of improving coding efficiency, reducing errors, and enhancing the overall coding experience for both beginners and experienced programmers. Traditional coding environments often require significant investment in writing boilerplate code, debugging, and understanding complex syntax, which can be daunting for beginners and time-consuming for experts.
JupyterLab 4.1 and Notebook 7.1 are now available! These releases include several new features, bug fixes, and enhancements for extension…
Unlock the full potential of Jupyter Notebook with expert tips and techniques, including time-saving shortcuts, powerful magic functions, and advanced features, to boost your productivity.
We are pleased to announce a major update to JupyterLab Desktop which adds many new features with main focus on the user experience…
Explore data with Python & SQL, work together with your team, and share insights that lead to action — all in one place with Deepnote.
I have to conclusion how to setup MongoDB (NoSQL) with Jupyter Notebook by summary step like...
Project Jupyter provides a broad collection of open-source tools for interactive computing that has become ubiquitous in data science and…
Write, test, document, and distribute software packages and technical articles — all in one place, your notebook.
Create delightful software with Jupyter Notebooks
Explore the Jupyter Notebook beyond its traditional use. Discover 8 alternative ways to utilize this versatile tool, making it even more powerful for coding, experimentation, and collaboration.
I love Jupyter notebooks and the power they provide.They can be used to present findings as well as share code in the most effective manner which was not easy with the previous IDEs.Yet there is something still amiss.There are a few functionalities I aspire in my text editor which don’t come by default in Jupyter.But fret not. Just like everything in Python, Jupyter too has third-party extensions. This post is about some of the most useful extensions I found.
IPython is a powerful Python REPL that gives you tab completion, better tracebacks, multiline editing, and several useful features on top…
If you're doing data science in Python, notebooks are a powerful tool. This free Jupyter Notebooks tutorial has will help you get the best out of Jupyter.
Jupyter notebooks are mostly known for their web-based user interface, such as JupyterLab or the Classic Notebook. They offer a great user…
Introducing a new Jupyter kernel for Robot Framework
Hi, conda activate base jupyter notebook Gives me this message: Traceback (most recent call last): File "/home/ics_vr/anaconda3/bin/jupyter-notebook", line 7, in from noteb...
Official gem repository: Ruby kernel for Jupyter/IPython Notebook - SciRuby/iruby
Jupyter Notebook is an open-source web application that lets you create and share interactive code, visualizations, and more. This tool can be used with seve…
This article introduces the easy to use blogging platform fastpages. fastpages relies on Github pages for hosting, and Github Actions to automate the creation of your blog, and contains extra features for Jupyter Notebooks.
By Pier Paolo Ippolito Introduction Jupyter Notebook is nowadays probably the most used environment for solving Machine Learning/Data Science tasks in Python. Jupyter Notebook is a client-server application used for running notebook documents in the...
The Xeus project has been incorporated as a Jupyter subproject.
Collection of notebooks about quantitative finance, with interactive python code. - cantaro86/Financial-Models-Numerical-Methods
Here's how to install PySpark on your computer and get started working with large data sets using Python and PySpark in a Jupyter Notebook.
Jupyter Notebook is a powerful tool for data analysis. Here are 28 tips, tricks and shortcuts to turn you into a Jupyter notebooks power user!
Creating complex layouts of widgets (button, sliders, maps, graphs etc.) can be cumbersome. New layout templates make this task a breeze.
Today, we are pleased to announce the 1.0 release of JupyterHub. We’ve come a long way since our first release in March, 2015. There are…
Being in the data science domain for quite some years, I have seen good Jupyter notebooks but also a lot of ugly. Notebooks can have the perfect balance between text, code and visualisations but how often do your notebooks rather get messy and incomprehensible after a while? Follow some simple best practices to work more efficiently with your notebooks.
Edited: Update on 2018-11-23 Added: Table of Content, %debug magic, nbdime for notebook diffing
Scientists, educators and engineers not only use programming languages to build software systems, but also in interactive workflows, using…
Introduction of a new feature-rich golang Jupyter kernel
Check out these 5 Jupyter notebook extensions to help increase your productivity.
Custom Jupyter Notebook Themes.
Interactive Widgets for the Jupyter Notebook.
Looking to bring more features into your Jupyter Notebooks? Lean about the powerful features that can be added to enhance business intelligence.