Quickest inline d3.js in Jupyter

Everyone has their own way to use d3.js in Jupyter. Here is the shortest and most concise I've been able to put together.

Step 1

Download d3.js and put it into the directory ~/.jupyter/custom

Step 2

Create a file ~/.jupyter/custom/custom.js and put the following into that file (note there is no ".js" in the quoted filepath):
require.config({paths:{d3:"/custom/d3.v5.min"}})

Step 3

In a Jupyter cell:

from IPython.core.display import display, Javascript
display(Javascript('''require(['d3'], function(d3) {
var svg = d3.select(element.get(0)).append('svg').attr('width',600).attr('height',200)
svg.append('circle').attr('cx',30).attr('cy',30).attr('r',20)
})'''))

Installation Quickstart: TensorFlow, Anaconda, Jupyter

What better way to start getting into TensorFlow than with a notebook technology like Jupyter, the successor to IPython Notebook? There are two little hurdles to achieve this:

1. Choice of OS. Trying to use Windows with TensorFlow is as painful as trying to use Windows with Spark. But even within Linux, it turns out you need a recent version. CentOS 7 works a lot better than CentOS 6 because it has a more recent glibc.
2. A step is missing from the TensorFlow installation page. From StackOverflow:
   conda install notebook ipykernel

Here then are the complete set of steps to achieve Hello World in Tensorflow on Jupyter via Anaconda:

1. Use CentOS 7.2 (aka 1511), for example using VirtualBox if under Windows. This step may be unnecessary if you use OSX, but I just haven't tried it.
2. Download and install Anaconda for Python 3.5.
3. From the TensorFlow installation instructions:
   conda create -n tensorflow python=3.5
   source activate tensorflow
   conda install -c conda-forge tensorflow
4. From StackOverflow:
   conda install notebook ipykernel
5. Launch Jupyter:
   jupyter notebook
6. Create a notebook and type in Hello World:
   import tensorflow as tf
   hello = tf.constant('Hello, TensorFlow!')
   sess = tf.Session()
   print(sess.run(hello))