Jim Vallandingham vlandham

## index.html
<html lang="en">
<head>
  <meta charset="utf-8">

  <title>2D Picking with canvas</title>
  <meta name="description" content="">
  <meta name="author" content="Yannick Assogba">
  <script src="//rawgit.com/mrdoob/stats.js/master/build/stats.min.js"></script>
  <script src="https://cdnjs.cloudflare.com/ajax/libs/dat-gui/0.5/dat.gui.js"></script>

## part1.md

      
              3 files
            
          
              22 forks
            
          
              12 comments
            
          
              117 stars
            
          
                vlandham
                / part1.md
            
            
              Last active
              March 21, 2024 12:57
            
              
                Feature Branches and Pull Requests : Walkthrough
              
          
    Here's a little walkthrough of how Yannick and I are using feature branches and pull requests to develop new features and adding them to the project. Below are the steps I take when working on a new feature. Hopefully this, along with watching the process on Github, will serve as a starting point to having everyone use a similar workflow.
Questions, comments, and suggestions for improvements welcome!
Start with the latest on master

When starting a new feature, I make sure to start with the latest and greatest codebase:
git checkout master


## iris.csv

          
            Sepal.Length
            Sepal.Width
            Petal.Length
            Petal.Width
            Species

            
              5.1
              3.5
              1.4
              0.2
              setosa

            
              4.9
              3
              1.4
              0.2
              setosa

            
              4.7
              3.2
              1.3
              0.2
              setosa

            
              4.6
              3.1
              1.5
              0.2
              setosa

            
              5
              3.6
              1.4
              0.2
              setosa

            
              5.4
              3.9
              1.7
              0.4
              setosa

            
              4.6
              3.4
              1.4
              0.3
              setosa

            
              5
              3.4
              1.5
              0.2
              setosa

            
              4.4
              2.9
              1.4
              0.2
              setosa

## introducting_learnjsdata.md

      
              1 file
            
          
              0 forks
            
          
              2 comments
            
          
              0 stars
            
          
                vlandham
                / introducting_learnjsdata.md
            
            
              Last active
              August 29, 2015 14:17
            
          
    Learn JS Data is a new guide introducing JavaScript as a language that can support data processing and manipulation.

The idea behind this project is to help those who may have some JavaScript experience, but have not really dealt much with data. Also, the guide can help those who have done data processing in other scripting languages, like python or R, and now have a need for similar data manipulation tools in JavaScript.
While there are many great tutorials and examples for doing data processing in other languages, there appeared to be a deficiency for data munging in JavaScript. We wanted to start to fill this gap in with LearnJSData.com!
It is meant to be a quick but somewhat comprehensive introduction to the topic that includes a small set of native tools and libraries to make data processing fun. Readers should be able to easily utilize these tools and techniques in wrangling their own data.

  
## outline.css
#sections {
  position: relative;
  display: inline-block;
  width: 250px;
  top: 0px;
  z-index: 90;
}

.step {
  margin-bottom: 200px;

## cities.csv

          
            city
            state
            population
            land area

            
              seattle
              WA
              652405
              83.9

            
              new york
              NY
              8405837
              302.6

            
              boston
              MA
              645966
              48.3

            
              kansas city
              MO
              467007
              315.0

## read_data.js
// # Reading in Data

// The first step in any data processing is getting the data!

// Here is how to parse in and prepare common input formats using D3.js

// ## Parsing CSV Files

// [D3 has a bunch](https://github.com/mbostock/d3/wiki/Requests) of filetypes it can support when loading data, and one of the most common is probably plain old CSV (comma separated values).

## -
// # Reading in Data

// The first step in any data processing is getting the data!

// Here is how to parse in and prepare common input formats using D3.js

// ## Parsing CSV Files

// [D3 has a bunch](https://github.com/mbostock/d3/wiki/Requests) of filetypes it can support when loading data, and one of the most common is probably plain old CSV (comma separated values).

## films_all.json
[
   {
      "name":"A Better Tomorrow",
      "id":"ABetterTomorrow"
   },
   {
      "name":"A Boy and His Dog",
      "id":"ABoyAndHisDog"
   },
   {

## chronicling_america-scraper.py
#Script for scraping Chronicling America
import requests
import re
import csv
from bs4 import BeautifulSoup, SoupStrainer
import os
from time import sleep
from datetime import date, datetime, timedelta

#search_terms is a string of words separated by spaces.
	<html lang="en">
	<head>
	<meta charset="utf-8">

	<title>2D Picking with canvas</title>
	<meta name="description" content="">
	<meta name="author" content="Yannick Assogba">
	<script src="//rawgit.com/mrdoob/stats.js/master/build/stats.min.js"></script>
	<script src="https://cdnjs.cloudflare.com/ajax/libs/dat-gui/0.5/dat.gui.js"></script>
Sepal.Length	Sepal.Width	Petal.Length	Petal.Width	Species
5.1	3.5	1.4	0.2	setosa
4.9	3	1.4	0.2	setosa
4.7	3.2	1.3	0.2	setosa
4.6	3.1	1.5	0.2	setosa
5	3.6	1.4	0.2	setosa
5.4	3.9	1.7	0.4	setosa
4.6	3.4	1.4	0.3	setosa
5	3.4	1.5	0.2	setosa
4.4	2.9	1.4	0.2	setosa
	#sections {
	position: relative;
	display: inline-block;
	width: 250px;
	top: 0px;
	z-index: 90;
	}

	.step {
	margin-bottom: 200px;
city	state	population	land area
seattle	WA	652405	83.9
new york	NY	8405837	302.6
boston	MA	645966	48.3
kansas city	MO	467007	315.0
	// # Reading in Data

	// The first step in any data processing is getting the data!

	// Here is how to parse in and prepare common input formats using D3.js

	// ## Parsing CSV Files

	// [D3 has a bunch](https://github.com/mbostock/d3/wiki/Requests) of filetypes it can support when loading data, and one of the most common is probably plain old CSV (comma separated values).
	[
	{
	"name":"A Better Tomorrow",
	"id":"ABetterTomorrow"
	},
	{
	"name":"A Boy and His Dog",
	"id":"ABoyAndHisDog"
	},
	{
	#Script for scraping Chronicling America
	import requests
	import re
	import csv
	from bs4 import BeautifulSoup, SoupStrainer
	import os
	from time import sleep
	from datetime import date, datetime, timedelta

	#search_terms is a string of words separated by spaces.