danemacaulay

import string
from numpy import array

from nltk.corpus import stopwords as sw
from nltk.corpus import wordnet as wn
from nltk import wordpunct_tokenize
from nltk import WordNetLemmatizer
from nltk import sent_tokenize
from nltk import pos_tag

danemacaulay

from sklearn.feature_extraction.text import CountVectorizer

import numpy as np
import pandas as pd
import scipy as sp
posts = pd.read_csv('posts.csv')

# Create vectorizer for function to use
vectorizer = CountVectorizer(binary=False)
y = posts["score"].values.astype(np.float32)

danemacaulay

'use stric';

var fs = require('fs');
var less = require('less');
var path = require('path');
var async = require('async');
var _ = require('lodash');

function readLessFilesIntoString(lessFiles, callback) {
    var initialText = '';

danemacaulay

'use strict';

function attributeIterator(node, extractorFunction) {
    var selector = '';
    var attributes = node.attributes;
    for (var i = 0; i < attributes.length; i++) {
        var attr = attributes[i];
        var attrSelector = extractorFunction(attr);
        if (attrSelector) {
            selector += attrSelector;

danemacaulay

'use strict';

function attributeIterator(node, extractorFunction) {
    var selector = '';
    var attributes = node.attributes;
    for (var i = 0; i < attributes.length; i++) {
        var attr = attributes[i];
        var attrSelector = extractorFunction(attr);
        if (attrSelector) {
            selector += attrSelector;

danemacaulay

'use strict';

var _ = require('lodash');

function stripPx(val) {
    return val.replace('px', '');
}

function addPx(val) {
    return val + 'px';

danemacaulay

(function() {
    'use strict';
    function addGlobalStyle(css) {
        var head, style;
        head = document.getElementsByTagName('head')[0];
        if (!head) { return; }
        style = document.createElement('style');
        style.type = 'text/css';
        style.innerHTML = css;
        head.appendChild(style);

danemacaulay

This simple bar chart is constructed from a TSV file storing the frequency of letters in the English language. The chart employs conventional margins and a number of D3 features:

• d3.tsv - load and parse data
• d3.format - format percentages
• d3.scale.ordinal - x-position encoding
• d3.scale.linear - y-position encoding
• d3.max - compute domains
• d3.svg.axis - display axes

danemacaulay

// define a new chart type: a circle chart
d3.chart("CircleChart", {

  initialize: function() {
    // create a layer of circles that will go into
    // a new group element on the base of the chart
    this.layer("circles", this.base.append("g"), {

      // select the elements we wish to bind to and
      // bind the data to them.

danemacaulay

@failure-color: @chart-1;
@delinquency-color: @chart-2;
@paydex-color: @chart-3;

@industry-color: @chart-4;
@industry-lower-color: #45a6aa;
@industry-median-color: #99cc01;
@industry-upper-color: #ff8800;