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from bokeh.io import show
from bokeh.layouts import column, row
from bokeh.models import ColorPicker
from bokeh.plotting import Figure
plot = Figure(x_range=(0, 1), y_range=(0, 1), plot_width=350, plot_height=350)
line = plot.line(x=(0,1), y=(0,1), color="red", line_width=4)
picker = ColorPicker(title="Line Color", color="red")
picker.js_link('color', line.glyph, 'line_color')
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Analytical Web Apps for Python, R, Julia, and Jupyter. No JavaScript Required.
A neural network that transforms a design mock-up into a static website.
/kind feature
Persona: Infrastructure Engineer
Control Plane Walkthrough:
List of Data Science Cheatsheets to rule the world
Custom Jupyter Notebook Themes
Create HTML profiling reports from pandas DataFrame objects
Set up deep learning environment in a single command line.
could you add one of the spellchecker plugins?
A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.
how to use gui in the AidLearning?how to custom the gui?
How to use Watcher / WatcherClient over tcp/ip network?
Watcher seems to ZMQ server, and WatcherClient is ZMQ Client, but there is no API/Interface to config server IP address.
Do I need to implement a class that inherits from WatcherClient?
Plotting library for IPython/Jupyter notebooks
The Go kernel for Jupyter notebooks and nteract.
This extension is now maintained in the Microsoft fork.
A curated list of awesome Jupyter projects, libraries and resources
Resource scheduling and cluster management for AI
Tools for diffing and merging of Jupyter notebooks.
Create delightful python projects using Jupyter Notebooks
nbconvert as a web service: Render Jupyter Notebooks as static web pages
The example book created by jupyter-book create creates files with permissions 775. None of these files are really executable, and therefore the correct permissions should be 664 (or probably 644)
To Reproduce
jupyter-book create test; ls -al test
Add a description, image, and links to the jupyter topic page so that developers can more easily learn about it.
To associate your repository with the jupyter topic, visit your repo's landing page and select "manage topics."
To guide users towards doing things right, could we suggest they use the magics instead of the shell invocations? Possibly with a short explanation why. Was also mentioned in ipython/ipython#11524 (comment).