Put custom.css in .jupyter/custom/ (if you are running recent version of Jupyter).
Note: Tested only on Chrome. Let me know if something is not working.
| import json | |
| import re | |
| import urllib2 | |
| path_to_save = '' # create a directory and write the name of directory here | |
| data_file = urllib2.urlopen('https://github.com/NREL/EnergyPlus/raw/develop/weather/master.geojson') | |
| data = json.load(data_file) | |
| # or you can download master.geojson and run the below code instead of downloading from the net | |
| # with open('master.geojson') as data_file: | |
| # data = json.load(data_file) |
The following debugging information was generated by Atom Beautify on Sat Jun 11 2016 12:58:56 GMT+0200 (W. Europe Daylight Time).
| # download the file @ https://www.dropbox.com/s/urqmc4jgt66hbef/notMNIST.pickle?dl=0 | |
| pickle_file = 'notMNIST.pickle' | |
| from time import strftime | |
| from math import sqrt | |
| from __future__ import print_function | |
| import numpy as np | |
| import tensorflow as tf | |
| from six.moves import cPickle as pickle |
| { | |
| "directed": false, | |
| "graph": [], | |
| "nodes": [{ | |
| "id": "Christian Wolff (philosopher)" | |
| }, { | |
| "id": "Martin Heidegger" | |
| }, { | |
| "id": "Lucretius" | |
| }, { |
| from networkx.readwrite import json_graph | |
| import json | |
| # Return data in adjacency format that is suitable for | |
| # JSON serialization and use in Javascript documents. | |
| # more @https://goo.gl/QoRlbL | |
| data = json_graph.adjacency_data(G) | |
| with codecs.open('matrix.json', 'w', encoding='utf-8') as f: | |
| json.dump(data, f) |