spark-py-notebooks - Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks

•    Jupyter

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This is a collection of IPython notebook/Jupyter notebooks intended to train the reader on different Apache Spark concepts, from basic to advanced, by using the Python language. If Python is not your language, and it is R, you may want to have a look at our R on Apache Spark (SparkR) notebooks instead. Additionally, if your are interested in being introduced to some basic Data Science Engineering, you might find these series of tutorials interesting. There we explain different concepts and applications using Python and R.

spark pyspark data-analysis mllib ipython-notebook notebook ipython data-science machine-learning big-data bigdata

emacs-ipython-notebook - IPython notebook client in Emacs

•    Emacs

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It is stable enough for my day to day work, but I can't guarantee the safety for your notebook data. So please make sure you have backup. Emacs IPython Notebook (EIN) provides a IPython Notebook client and integrated REPL (like SLIME) in Emacs. While EIN makes notebook editing very powerful by allowing you to use any Emacs features, it also expose IPython features such as code evaluation, object inspection and code completion to the Emacs side. These features can be accessed anywhere in Emacs and improve Python code editing and reading in Emacs.

nteract - 📘 The interactive computing suite for you! ✨

•    Javascript

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nteract is first and foremost a dynamic tool to give you flexibility when writing code, exploring data, and authoring text to share insights about the data. Edit code, write prose, and visualize.

notebook nteract data-science repl ipython jupyter jupyter-notebook desktop-application react react-components zeromq monorepo electron data

jupyter-dark-theme - Dark theme for Jupyter Notebook (iPython 4) UI

•    CSS

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This is a completely dark theme for the Jupyter Notebook interface. Jupyter includes iPython 4 as its default kernel (which, confusingly, supports both Python 2.x and 3.x). Since the iPython 3 to 4 transition, it has gained better support for other interpreters like R and Ruby. It is possible to upgrade iPython 2 or 3 to Jupyter + iPython 4. Source code coloring is based on the Twilight theme for Textmate. Print preview output for notebooks retains a white background with printable foreground colors.

ipyvolume - 3d plotting for Python in the Jupyter notebook based on IPython widgets using WebGL

•    Jupyter

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3d plotting for Python in the Jupyter notebook based on IPython widgets using WebGL.

ipython-widget jupyter jupyter-notebook visualisation volume-rendering virtual-reality plotting dataviz scientific-visualization webgl threejs rendering-3d-volumes quiver

data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines

•    Python

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IPython Notebook(s) demonstrating deep learning functionality.IPython Notebook(s) demonstrating scikit-learn functionality.

machine-learning deep-learning data-science big-data aws tensorflow theano caffe scikit-learn kaggle spark mapreduce hadoop matplotlib pandas numpy scipy keras

vscodeJupyter - Jupyter for Visual Studio Code

•    TypeScript

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For further information and details continue through to the documentation.

jupyter jupyter-notebook osx ipython ipython-notebook vscode data-science

urban-data-science - Course materials, Jupyter notebooks, tutorials, guides, and demos for a Python-based urban data science course

•    Jupyter

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This repo is my workspace for developing a cycle of course materials, IPython notebooks, and tutorials towards an academic urban data science course based on Python. Between Fall 2013 and Fall 2016, I was the grad student instructor (3 years) and co-lead instructor (1 year) for CP255, Urban Informatics and Visualization, at UC Berkeley. This course was developed by Paul Waddell and is ongoing at Berkeley with the fantastic contributions of @Arezoo-bz. If you're interested in these topics at all, you owe it to yourself to check out the latest iterations of Paul's excellent pedagogy in his CP255 repo. A couple years ago, I wrote this blog post describing our efforts for the course.

ptpython - A better Python REPL

•    Python

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Ptpython is an advanced Python REPL. It should work on all Python versions from 2.6 up to 3.5 and work cross platform (Linux, BSD, OS X and Windows).

interpreter python-interpreter repl terminal curses

ipython-in-depth - IPython in-depth Tutorial, first presented at PyCon 2012

•    Jupyter

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In its current form, this tutorial is meant to be executed with Jupyter notebook 5.0, using IPython 6.0 or newer on Python 3, the latest IPython version compatible with Python 2 is IPython 5.x that may not have the exact same behavior and all the features presented in this tutorial. Or download current master and unzip it.

jupyterhub - Multi-user server for Jupyter notebooks

•    Python

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With JupyterHub you can create a multi-user Hub which spawns, manages, and proxies multiple instances of the single-user Jupyter notebook server. Project Jupyter created JupyterHub to support many users. The Hub can offer notebook servers to a class of students, a corporate data science workgroup, a scientific research project, or a high performance computing group.

jupyter-notebook jupyterhub multi-user ipython

bokeh-notebooks - Interactive Web Plotting with Bokeh in IPython notebook

•    Jupyter

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Bokeh is a Python interactive visualization library for large datasets that natively uses the latest web technologies. Its goal is to provide elegant, concise construction of novel graphics in the style of Protovis/D3, while delivering high-performance interactivity over large data to thin clients. These Jupyter notebooks provide useful Bokeh examples and a tutorial to get started. You can visualize the rendered Jupyter notebooks on NBViewer or download the repository and execute jupyter notebook from your terminal.

emacs-ipython-notebook - Jupyter and IPython 2.x/3.x notebook client in Emacs

•    Emacs

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EIN works with IPython 2.x, 3.x, and Jupyter! Note that remote and password protected logins are working with IPython 3.x, but have not been tested with Jupyter. The code for testing EIN is horribly broken, but I regularly hand check the code running against IPython's suite of sample notebooks. It's a worse-is-better solution to problem requiring a time-consuming solution.

emacs-lisp jupyter-notebook

dive-into-machine-learning - Dive into Machine Learning with Python Jupyter notebook and scikit-learn!

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I learned Python by hacking first, and getting serious later. I wanted to do this with Machine Learning. If this is your style, join me in getting a bit ahead of yourself. I suggest you get your feet wet ASAP. You'll boost your confidence.

machine-learning data-science scikit-learn ipython-notebook deep-learning jupyter-notebook courses learning learning-by-doing diy

nbstripout - strip output from Jupyter and IPython notebooks

•    Python

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Opens a notebook, strips its output, and writes the outputless version to the original file. Useful mainly as a git filter or pre-commit hook for users who don't want to track output in VCS.

jupyter jupyter-notebook ipython ipython-notebook git filter hooks

hydrogen - :atom: Run code interactively, inspect data, and plot

•    Javascript

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Hydrogen is an interactive coding environment that supports Python, R, JavaScript and other Jupyter kernels. Checkout our Documentation and Medium blog post to see what you can do with Hydrogen.

data-science jupyter ipython repl hydrogen atom jupyter-kernels nteract execute run julia torch ijulia irkernel itorch plot image

bpython - A fancy curses interface to the Python interactive interpreter

•    Python

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bpython is a lightweight Python interpreter that adds several features common to IDEs. These features include syntax highlighting, expected parameter list, auto-indentation, and autocompletion. bpython does not aim to be a complete IDE - the focus is on implementing a few ideas in a practical, useful, and lightweight manner.

interpreter python-interpreter curses terminal

Data-Science-45min-Intros - Ipython notebook presentations for getting starting with basic programming, statistics and machine learning techniques

•    Jupyter

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Every week*, our data science team @Gnip (aka @TwitterBoulder) gets together for about 50 minutes to learn something. While these started as opportunities to collectively "raise the tide" on common stumbling blocks in data munging and analysis tasks, they have since grown to machine learning, statistics, and general programming topics. Anything that will help us do our jobs better is fair game.

jupyter-scala - Lightweight Scala kernel for Jupyter / IPython 3

•    Scala

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Jupyter Scala is a Scala kernel for Jupyter. It aims at being a versatile and easily extensible alternative to other Scala kernels or notebook UIs, building on both Jupyter and Ammonite. The current version is available for Scala 2.11. Support for Scala 2.10 could be added back, and 2.12 should be supported soon (via ammonium / Ammonite).

jupyter jupyter-notebook repl jupyter-kernels

knowledge-repo - A next-generation curated knowledge sharing platform for data scientists and other technical professions

•    Python

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The Knowledge Repository project is focused on facilitating the sharing of knowledge between data scientists and other technical roles using data formats and tools that make sense in these professions. It provides various data stores (and utilities to manage them) for "knowledge posts", with a particular focus on notebooks (R Markdown and Jupyter / IPython Notebook) to better promote reproducible research.Check out this Medium Post for the inspiration for the project.

data data-science knowledge data-analysis