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Python Jupyter

General Information

scientific article published on 01 January 2019

Project Jupyter | Home

https://jupyter.org/

2020-07-29 · Jupyter supports over 40 programming languages, including Python, R, Julia, and Scala. Share notebooks Notebooks can be shared with others using email, Dropbox, GitHub and the Jupyter Notebook Viewer .Project Jupyter | Try Jupyter. The Jupyter Notebook is a web-based interactive …If installing using pip install --user, you must add the user-level bin directory to your …Project Jupyter is a non-profit, open-source project, born out of the IPython Project in …Jupyter meets the Earth: EarthCube Community Meeting Summary of the …Project Jupyter | Widgets. The Jupyter Notebook is a web-based interactive …Like all Project Jupyter efforts, JupyterHub is an open-source and community-driven …Project Jupyter | Documentation. The Jupyter Notebook is a web-based interactive …

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Jupyter Notebook: An Introduction – Real Python

https://realpython.com/jupyter-notebook-introduction/

The Jupyter Notebook is an open source web application that you can use to create and share documents that contain live code, equations, visualizations, and text. Jupyter Notebook is maintained by the people at Project Jupyter. Jupyter Notebooks are a spin-off project from the IPython project, which used to have an IPython Notebook project itself.

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Install Python and Jupyter Notebook to Windows …

https://medium.com/@kswalawage/install[...]book-to-windows-10-64-bit-66db782e1d02

2019-12-14 · This blog post is a step-by-step tutorial to install Python and Jupyter Notebook to Windows 10 (64 bit). Python 3.3 or greater, or Python…

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Project Jupyter - Wikipedia

https://en.wikipedia.org/wiki/Project_Jupyter

Project Jupyter is a nonprofit organization created to "develop open-source software, open-standards, and services for interactive computing across dozens of programming languages". Spun-off from IPython in 2014 by Fernando Pérez, Project Jupyter supports execution environments in several dozen languages. Project Jupyter's name is a reference to the three core programming languages supported by Jupyter, which are Julia, Python and R, and also a homage to Galileo's notebooks recording the discovery of the mo…

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Working with Jupyter code cells in the Python …

https://code.visualstudio.com/docs/python/jupyter-support-py

Working with the Python Interactive window. Jupyter (formerly IPython Notebook) is an open-source project that lets you easily combine Markdown text and executable Python source code on one canvas called a notebook.Visual Studio Code supports working with Jupyter Notebooks natively, as well as through Python code files.This topic covers the support offered through Python code files and ...

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Working with Jupyter Notebooks in Visual Studio …

https://code.visualstudio.com/docs/python/jupyter-support

Working with Jupyter Notebooks in Visual Studio Code. Jupyter (formerly IPython Notebook) is an open-source project that lets you easily combine Markdown text and executable Python source code on one canvas called a notebook.Visual Studio Code supports working with Jupyter Notebooks natively, as well as through Python code files.This topic covers the native support available for Jupyter ...

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Getting Started With Jupyter Notebook for Python | by ...

https://medium.com/codingthesmartway-c[...]pyter-notebook-for-python-4e7082bd5d46

Installing Jupyter Notebook by installing the Anaconda distribution Especially if you're new to Python and would like to set up your development environment from scratch using the Anaconda ...

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(Tutorial) Jupyter Notebook: The Definitive Guide - DataCamp

https://www.datacamp.com/community/tutorials/tutorial-jupyter-notebook

A basic overview of the Jupyter Notebook App and its components,; The history of Jupyter Project to show how it's connected to IPython,; An overview of the three most popular ways to run your notebooks: with the help of a Python distribution, with pip or in a Docker container,; A practical introduction to the components that were covered in the first section, complete with examples of Pandas ...

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python - How to change working directory in Jupyter ...

https://stackoverflow.com/questions/35[...]-working-directory-in-jupyter-notebook

It's simple, every time you open Jupyter Notebook and you are in your current work directory, open the Terminal in the near top right corner position where create new Python file in. The terminal in Jupyter will appear in the new tab. Type command cd and enter, and then type Jupyter Notebook in that terminal, a new ...

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How to Use Jupyter Notebook in 2020: A Beginner's Tutorial

https://www.dataquest.io/blog/jupyter-notebook-tutorial/

Jupyter's Notebooks and dashboard are web apps, and Jupyter starts up a local Python server to serve these apps to your web browser, making it essentially platform-independent and opening the door to easier sharing on the web. (If you don't understand this yet, don't worry — the important point is just that although Jupyter Notebooks opens ...

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How to install Jupyter Notebook in Windows? - GeeksforGeeks

https://www.geeksforgeeks.org/how-to-install-jupyter-notebook-in-windows/

Jupyter Notebook can be installed by using either of the two ways described below: Using Anaconda: Install Python and Jupyter using the Anaconda Distribution, which includes Python, the Jupyter Notebook, and other commonly used packages for scientific computing and data science.

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Jupyter - Docker Hub

https://hub.docker.com/u/jupyter/#!

Jupyter Notebook Python, Scala, R, Spark, Mesos Stack from https://github.com/jupyter/docker-stacks. Container. 100K+ Downloads. 169 Stars

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Anaconda | Individual Edition

https://www.anaconda.com/products/individual

Anaconda Individual Edition is the world's most popular Python distribution platform with over 20 million users worldwide. You can trust in our long-term commitment to supporting the Anaconda open-source ecosystem, the platform of choice for Python data science.

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How To Set Up Jupyter Notebook with Python 3 on Ubuntu 18 ...

https://www.digitalocean.com/community[...]notebook-with-python-3-on-ubuntu-18-04

By the end of this guide, you will be able to run Python 3 code using Jupyter Notebook running on a remote server. Prerequisites. In order to complete this guide, you should have a fresh Ubuntu 18.04 server instance with a basic firewall and a non-root user with sudo privileges configured.

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Jupyter Notebook を使ってみよう - Python でデータサイエンス

https://pythondatascience.plavox.info/[...]A3%E3%81%A6%E3%81%BF%E3%82%88%E3%81%86

Jupyter Notebook の基本的な使い方. Jupyter Notebook を起動後、ノートブックを作成したいフォルダ階層で、「New」ボタン ⇒「Python3」を選択し、ノートブックを作成します。 以下のように、セルと呼ばれるスペースに Python のコードを入力し実行することができます。

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Exploring an Alternative to Jupyter Notebooks for Python ...

https://pbpython.com/notebook-alternative.html

Despite how much I like using python in Jupyter notebooks, I do wish for the editor capabilities you can find in VS Code. I also would like my files to work better when versioning them with git. Recently, I have started using a solution that supports the interactivity of the Jupyter notebook and the developer friendliness of plain .py text files.

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IPython - Magic Commands - Tutorialspoint

https://www.tutorialspoint.com/jupyter/ipython_magic_commands.htm

While using Jupyter notebook, %matplotlib inline directive displays plot output in the browser only. %notebook. This function converts current IPython history into an IPython notebook file with ipynb extension. The input cells in previous example are saved as sine.ipynb ... Time execution of a Python statement or expression uses the timeit ...

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Books with Jupyter

https://jupyterbook.org/intro.html

Jupyter Book is a wrapper around a collection of tools in the Python ecosystem that make it easier to publish computational documents. Here are a few key pieces: It uses the MyST markdown language in markdown and notebook documents. This allows users to write rich, publication-quality markup in their documents. ...

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jupyterlab · PyPI

https://pypi.org/project/jupyterlab/

JupyterLab is the next-generation user interface for Project Jupyter offering all the familiar building blocks of the classic Jupyter Notebook (notebook, terminal, text editor, file browser, rich outputs, etc.) in a flexible and powerful user interface. JupyterLab will eventually replace the classic Jupyter Notebook.

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GitHub - vpython/vpython-jupyter: 3D visualization made easy

https://github.com/vpython/vpython-jupyter

VPython. This package enables one to run VPython in a browser, using the GlowScript VPython API, documented in the Help at https://www.glowscript.org.If the code is in a cell in a Jupyter notebook, the 3D scene appears in the Jupyter notebook.

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Develop with Q# Jupyter Notebooks - Microsoft Quantum ...

https://docs.microsoft.com/en-us/quantum/quickstarts/install-jupyter

Install the IQ# Jupyter kernel. IQ# (pronounced i-q-sharp) is an extension primarily used by Jupyter and Python to the .NET Core SDK that provides the core functionality for compiling and simulating Q# operations.

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LaTeX - Mathematical Python

https://www.math.ubc.ca/~pwalls/math-python/jupyter/latex/

Jupyter Jupyter Jupyter Notebook Markdown LaTeX LaTeX Table of contents. Mathematics Inline and Display Common Symbols Matrices and Brackets Examples Derivative Continuity MacLaurin Series Jacobian Matrix Exercises Python Python Numbers Variables Sequences Functions Logic

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Using Virtual Environments in Jupyter Notebook and Python ...

https://janakiev.com/blog/jupyter-virtual-envs/

Jupyter Notebook makes sure that the IPython kernel is available, but you have to manually add a kernel with a different version of Python or a virtual environment. First, you need to activate your virtual environment.

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How to Install Python & Jupyter in Anaconda | 365 Data Science

https://365datascience.com/how-to-install-python/

How to Install Python and Jupyter in Anaconda? There are different ways to install Python and Jupyter on your computer. But especially for new users, it is highly recommended to opt for Anaconda. It will install, not only Python but also the Jupyter Notebook App and many scientific computing and data science packages. Let's open www.anaconda.com.

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Jupyter Tutorial - Tutorialspoint

https://www.tutorialspoint.com/jupyter/index.htm

Jupyter notebook is a defacto standard interactive environment for data scientists today. This tutorial is useful for everyone who wants to learn and practice data science libraries of Python/R etc. Prerequisites. This is not a tutorial to teach Python programming. It describes use of powerful interactive environment to use Python.

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Installing Python and Jupyter - Research Computing ...

https://sites.northwestern.edu/researc[...]sources/installing-python-and-jupyter/

Python workshops use the current version of Python (currently 3.7 or 3.8). We recommend the Anaconda distribution of Python 3. Anaconda includes Python, Jupyter Notebook, Jupyter Lab, and most of the Python packages used in our workshops. Our Python Fundamentals workshop uses Jupyter Lab, which comes with the Anaconda distribution.

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GPU Accelerated Computing with Python | NVIDIA Developer

https://developer.nvidia.com/how-to-cuda-python

SETUP CUDA PYTHON To run CUDA Python, you will need the CUDA Toolkit installed on a system with CUDA capable GPUs. Use this guide for easy steps to install CUDA. If you do not have a CUDA-capable GPU, you can access one of the thousands of GPUs available from cloud service providers including Amazon AWS, Microsoft Azure and IBM SoftLayer.The NVIDIA-maintained CUDA Amazon Machine Image (AMI) on ...

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Crash course in Jupyter and Python — STA663-2019 1.0 ...

http://people.duke.edu/~ccc14/sta-663-[...]/S01_Jupyter_and_Python_Annotated.html

PEP 8 — the Style Guide for Python Code Many code editors can be used with linters to check if your code conforms to PEP 8 style guidelines. E.g. see jupyter-autopep8

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Computational Proteomics with Jupyter and Python

https://www.zora.uzh.ch/id/eprint/1711[...]col_ComputationalProteomicsWithJup.pdf

Proteomics based on mass spectrometry produces complex data in large quantities. The need for flexible computational pipelines, in the context of big data, in proteomics and other areas of science, has prompted the development of computational platforms and libraries that facilitate data analysis and data processing. In this respect, Python appears to be one of the winners among programming languages in terms of popularity and development. This chapter shows how to perform basic tasks using Python and dedicated libraries in a Jupyter framework: from basic search result summarizations to the creation of MS1 chromatograms.

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Python and Jupyter Notebook for Medical Image Analysis - OpenMRBenelux 2020

http://dx.doi.org/10.5281/zenodo.3611368

Dataset for the workshop "Python and Jupyter Notebook for Medical Image Analysis" at OpenMRBenelux - January 22, 2020 - Nijmegen (The Netherlands)

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FANCY: Fast Estimation of Privacy Risk in Functional Genomics Data.

https://www.ncbi.nlm.nih.gov/pubmed/32726397

DOI: 10.1093/bioinformatics/btaa661 Abstract: Functional genomics data is becoming clinically actionable, raising privacy concerns. However, quantifying privacy leakage via genotyping is difficult due to the heterogeneous nature of sequencing techniques. Thus, we present FANCY, a tool that rapidly e...

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Interactive Classrooms with Jupyter and Python

http://dx.doi.org/10.5951/mathteacher.111.4.0304

We describe how to set up and share the Jupyter notebooks as a way to introduce the Python computer language in the mathematics classroom. Additionally, we discuss how to use the Binder application together with GitHub® as a way to share the notebooks with students over the Internet. We conclude with some suggestions for how teachers might use these notebooks in class.

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Supporting Jupyter Python notebook for "A new class of efficient randomized benchmarking protocols"

http://dx.doi.org/10.5281/zenodo.2549368

Python notebook containing the code used to generate the data for figure 2 in the appendix of "A new class of efficient randomized benchmarking protocols" (arXiv:1806.02048).

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Python Jupyter Notebook to Perform Automatic Microscopic Image Analysis by Moving Window Local Fourier Transform and Machine Learning

http://dx.doi.org/10.17632/25X46XJYR5.1

Python Jupyter Notebook together with exemplary images to perform automatic microscopic image analysis using moving window local Fourier Transform and Machine Learning data decomposition using Non-Negative Matrix Factorization (NMF). The number of decomposition components is obtained from prior PCA Scree Plot analysis.

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Jupyter (IPython) y Nature | 6.1 - Curso Python científico

http://vertice.cpd.ua.es/137587

Jupyter (IPython) y Nature- Curso online de Python científico (2ª ed)

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an interactive and comprehensive working environment for high energy physics software with python and jupyter notebooks

http://stacks.iop.org/1742-6596/898/i=7/a=072020/pdf

Today's analyses for high-energy physics (HEP) experiments involve processing a large amount of data with highly specialized algorithms. The contemporary workflow from recorded data to final results is based on the execution of small scripts – often written in Python or ROOT macros which call complex compiled algorithms in the background – to perform fitting procedures and generate plots. During recent years interactive programming environments, such as Jupyter, became popular. Jupyter allows to develop Python-based applications, so-called notebooks, which bundle code, documentation and results, e.g. plots. Advantages over classical script-based approaches is the feature to recompute only parts of the analysis code, which allows for fast and iterative development, and a web-based user frontend, which can be hosted centrally and only requires a browser on the user side. In our novel approach, Python and Jupyter are tightly integrated into the Belle II Analysis Software Framework (basf2), currently being developed for the Belle II experiment in Japan. This allows to develop code in Jupyter notebooks for every aspect of the event simulation, reconstruction and analysis chain. These interactive notebooks can be hosted as a centralized web service via jupyterhub with docker and used by all scientists of the Belle II Collaboration. Because of its generality and encapsulation, the setup can easily be scaled to large installations.

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Visual debugger for Jupyter Notebooks: Myth or Reality?

http://dx.doi.org/10.5446/44869

Many Python developers like Jupyter Notebooks for their flexibility: they are very useful for interactive prototyping, scientific experiments, visualizations and many other tasks. There are different development tools which make working with Jupyter Notebooks easier and smoother, but all of them lack very important feature: visual debugger. Since Jupyter Kernel is a usual Python process, it looks reasonably to use one of existing Python debuggers with it. But is it really possible? In this talk we’ll try to understand how Python debugger should be changed to work with Jupyter cells and how these changes are already implemented in the PyCharm IDE. After that we’ll look into the whole Jupyter architecture and try to understand which bottlenecks in it prevent creation of universal Jupyter debugger at the moment. This talk requires a basic knowledge of Jupyter Notebooks and understanding of Python functions and objects. It will be interesting for people who want to learn internals of the tools they use every day. Also it might be an inspiration for people who want to implement a visual debugger in their favourite IDE.

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Introducción a Jupyter (IPython 3.0) y novedades | 6.2 - Curso Python científico

http://vertice.cpd.ua.es/137830

Introducción a Jupyter (IPython 3.0) desde el navegador web y novedades interesantes

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simple generator of jupyter notebook interactive documents from marked up python programming code

http://dx.doi.org/10.36994/2707-4110-2019-1-22-31

Jupyter Notebook is widely used for interactive computing in various fields of science and technology. As a rule, Jupyter Notebook documents are created directly in the browser, but it is possible to generate them by software, for example, from Python code that contains Python string literals with Markdown code. Generation from Python code allows you to save documents in an easy-to-edit text format. In addition, in some cases, this Python code can be executed by a standard Python interpreter without having a Jupyter Notebook installed. This provides format flexibility. Currently, there are several tools for converting Python code to a Jupyter Notebook (.ipynb) document. Their disadvantage is either support for old formats or an inconvenient way to mark up cells in a Jupyter Notebook document. The principles of function are described and the Python program is developed for generating interactive Jupyter Notebook documents (.ipynb v4) from the simple marked Python code. The program has the ability to further convert .ipynb to HTML and docx formats. The program can be used to facilitate the creation and editing of documents based on Jupyter Notebook. In comparison with analogues, the program has a simple and clear algorithm based on regular expressions, which allows its simple modification for other tasks. An additional advantage is the simple way of marking Python code on cells, which consists in placing Markdown text blocks in multiline Python literals in quotes and separating code blocks by using ## symbols. An example of creating Python code is provided, which contains a Markdown block with such features as formatting with various fonts, hyperlinks, pictures, program code blocks, LaTeX formulas and tables; a block of code for building interactive graphics using Python libraries Matplotlib and ipywidgets; a block of code that outputs unformatted text and interpretation results of HTML, Markdown, SVG code by the display function from the IPython.display module. An example of converting this code to Jupyter Notebook (including interactive), Markdown, HTML and docx formats is shown.

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Mi primer widget interactivo de IPython 3.0 - Jupyter: matplotib y NumPy | 6.4 - Curso Python científico

http://vertice.cpd.ua.es/137606

Ejemplo simple de widget interactivo de IPython 3.0 / Jupyter: Gráficas interactivas con matplotib y NumPy

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Tutorial de Widgets interactivos de IPython 3.0 - Jupyter: Sliders, botones y checkboxes | 6.5 - Curso Python científico

http://vertice.cpd.ua.es/137605

Widgets interactivos de IPython 3.0 / Jupyter: Deslizadores (sliders), botones y casillas de verificación (checkboxes)

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Drops Of Jupyter Notebooks: How To Keep Notes In The Information Age

https://hackaday.com/2019/02/22/drops-[...]-to-keep-notes-in-the-information-age/

For those times that you want something quick but want something more than a spreadsheet, you should check out Jupyter Notebooks. The system is most commonly associated with Python, but it isn’t ...

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Setting up a Jupyter Notebook

https://www.rit.edu/researchcomputing/[...]ructions/Setting-up-a-Jupyter-Notebook

The following instructions will explain how to setup a jupyter notebook securely within your terminal. The Jupyter Notebook relies on Python, so you must load in a version of Python that works with ...

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Kite brings its AI-powered code completions to Jupyter notebooks

https://venturebeat.com/2020/08/04/kit[...]code-completions-to-jupyter-notebooks/

Data scientists can now get code completions powered by Kite’s deep learning, which is trained on over 25 million open-source Python files, as they type in Jupyter notebooks. Using AI to help ...

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7 data science certifications to boost your resume and salary

https://www.msn.com/en-us/finance/care[...]ost-your-resume-and-salary/ar-BB18tTno

Students in this course will take a series of hands-on labs in the IBM cloud that provide experience with Jupyter/JupyterLab ... Data science methodology Python for data science and AI ...

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ArcGIS Notebooks – Using GIS and Python Notebooks for Workflow Automation

https://www.directionsmag.com/webinar/10062

In this session you will learn: A quick overview of ArcGIS Notebooks – Esri’s integrated Jupyter experience – now available across the platform (ArcGIS Pro, ArcGIS Online and ArcGIS Enterprise). How ...

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Explore How to Use ArcGIS and Jupyter for Geospatial Data Science

https://www.directionsmag.com/webinar/9311

Walk through an end-to-end data science workflow from data engineering, visualization and exploration, spatial analysis, and end with high impact ways to deliver results using ArcGIS tools and Jupyter ...

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SD Times Open-Source Project of the Week: Jupyter Book

https://sdtimes.com/open-source/sd-tim[...]urce-project-of-the-week-jupyter-book/

Jupyter Book is an open-source tool for building publication-quality books, websites and documents with computational content. It enables users to write content in markdown files or Jupyter ...

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Creating an executable paper is a journey through Open Science

https://www.nature.com/articles/s42005-020-00403-4

Executable papers take transparency and openness in research communication one step further. In this comment, an early career researcher reports her experience of creating an executable paper as a ...

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Python Programming Beginner - Lecture 8 Jupyter (iPython) Notebooks - Complete Python Bootcamp 2016

Python Programming Beginner - Lecture 8 Jupyter (iPython) Notebooks - Complete Python Bootcamp 2016

Python Programming Beginner - Complete Python Bootcamp 2016 Lecture 8 Jupyter (iPython) Notebooks ___________________________________________ Follow our channel to view more free courses and python lectures: http://www.dailymotion.com/udemycoursesfree All lecture in Complete Python Bootcamp course will be updated constantly! You can request what course you want to learn and we will update it as soon as possible Thank you very much and follow us!

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FUN-MOOC : Python 3 : des fondamentaux aux concepts avancés du langage (session 2)

FUN-MOOC : Python 3 : des fondamentaux aux concepts avancés du langage (session 2)

Dans ce cours, vous apprendrez à bien programmer en Python. On vous mènera des premiers pas dans le langage à l'étude des concepts les plus évolués au travers de nombreuses vidéos courtes, d'exercices et de mini-projets. Pour en savoir plus :https://www.fun-mooc.fr/courses/course-v1:UCA+107001+session02/about

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Set in Python | Python Sets

Set in Python | Python Sets

Mainly this Channel is developed for Students, such as BTech/BE, Diploma Engineering (Polytechnic), also BSc, BCA, MCA, NIELIT( 'O' Level, 'A' Level), ICSE Board, CBSE Board etc. This Video Tutorial will be very helpful to our Students (Computer Science & Information Technology).

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With Attributes

  • Author: Lars Malmström
  • Publication date: 1 January 2019