Timothy Dobbins tmthyjames

## index.html
<!DOCTYPE html>
<html>
<head>

<script type="text/javascript" src="http://d3js.org/d3.v2.js"></script>
<script type="text/javascript" src="./sankey.js"></script>

<title>Sankey Diagram</title>
<style>

## README.md

      
              3 files
            
          
              6 forks
            
          
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                tmcw
                / README.md
            
            
              Created
              October 31, 2012 15:00
            
              
                GIS with Python, Shapely, and Fiona Example 1 - CSV Files
              
          
    This is companion code to this guide.

  
## gitcreate.sh
#!/bin/bash

# https://gist.github.com/robwierzbowski/5430952/
# Create and push to a new github repo from the command line.
# Grabs sensible defaults from the containing folder and `.gitconfig`.
# Refinements welcome.

# Gather constant vars
CURRENTDIR=${PWD##*/}
GITHUBUSER=$(git config github.user)

## wavio.py
# wavio.py
# Author: Warren Weckesser
# License: BSD 3-Clause (http://opensource.org/licenses/BSD-3-Clause)

import wave
import numpy as np


def _wav2array(nchannels, sampwidth, data):
    """data must be the string containing the bytes from the wav file."""

## README.md

      
              5 files
            
          
              5 forks
            
          
              9 comments
            
          
              28 stars
            
          
                mdml
                / README.md
            
            
              Last active
              March 30, 2023 16:30
            
              
                Dendrograms: Convert from Scipy to D3
              
          
    A dendrogram is a common way to represent hierarchical data. For Python users, Scipy has a hierarchical clustering module that performs hierarchical clustering and outputs the results as dendrogram plots via matplotlib. When it's time to make a prettier, more customized, or web-version of the dendogram, however, it can be tricky to use Scipy's dendrogram to create a suitable visualization. My preferred method of visualizing data -- especially on the web -- is D3. This example includes a script to convert a Scipy dendrogram into JSON format used by D3's cluster method.
In the example, I cluster six genes by their expression values from two experiments. You can easily replace that data with your own, larger data set, to harness the power of both Scipy and D3 for analyzing hierarchical data. The D3 code I used to generate this example is straigh

  
## geojsonio_embed.ipynb

      
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                jwass
                / geojsonio_embed.ipynb
            
            
              Created
              August 18, 2014 18:02
            
              
                Embed geojson.io in a Jupyter / IPython notebook using geojsonio.py
              
          
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## defaultDict.js

/* Kinda like Python's defaultdict, but for JS*/
function defDict(type) {
    var dict = {};
    return {
        get: function (key) {
        if (!dict[key]) {
            dict[key] = type.constructor();
        }
        return dict[key];

## geopandas_lightning_talk.ipynb

      
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                jorisvandenbossche
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              Created
              August 29, 2015 13:02
            
          
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## config.py
consumer_key = 'your-consumer-key'
consumer_secret = 'your-consumer-secret'
access_token = 'your-access-token'
access_secret = 'your-access-secret'

## ec2_info_retriever.py
from collections import defaultdict

import boto3

"""
A tool for retrieving basic information from the running EC2 instances.
"""

# Connect to EC2
ec2 = boto3.resource('ec2')
	<!DOCTYPE html>
	<html>
	<head>

	<script type="text/javascript" src="http://d3js.org/d3.v2.js"></script>
	<script type="text/javascript" src="./sankey.js"></script>

	<title>Sankey Diagram</title>
	<style>
	#!/bin/bash

	# https://gist.github.com/robwierzbowski/5430952/
	# Create and push to a new github repo from the command line.
	# Grabs sensible defaults from the containing folder and `.gitconfig`.
	# Refinements welcome.

	# Gather constant vars
	CURRENTDIR=${PWD##*/}
	GITHUBUSER=$(git config github.user)
	# wavio.py
	# Author: Warren Weckesser
	# License: BSD 3-Clause (http://opensource.org/licenses/BSD-3-Clause)

	import wave
	import numpy as np


	def _wav2array(nchannels, sampwidth, data):
	"""data must be the string containing the bytes from the wav file."""

	/* Kinda like Python's defaultdict, but for JS*/
	function defDict(type) {
	var dict = {};
	return {
	get: function (key) {
	if (!dict[key]) {
	dict[key] = type.constructor();
	}
	return dict[key];
	consumer_key = 'your-consumer-key'
	consumer_secret = 'your-consumer-secret'
	access_token = 'your-access-token'
	access_secret = 'your-access-secret'
	from collections import defaultdict

	import boto3

	"""
	A tool for retrieving basic information from the running EC2 instances.
	"""

	# Connect to EC2
	ec2 = boto3.resource('ec2')