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   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Homework 5: Networks and Congress\n",
      "\n",
      "*Due Friday, November 15, 11:59pm*\n",
      "\n",
      "<img src=\"http://img.washingtonpost.com/rf/image_1024w/2010-2019/WashingtonPost/2011/08/05/National-Politics/Images/uscap.JPG\">\n",
      "\n",
      "<br>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline\n",
      "\n",
      "import json\n",
      "\n",
      "import numpy as np\n",
      "import networkx as nx\n",
      "import requests\n",
      "from pattern import web\n",
      "import matplotlib.pyplot as plt\n",
      "\n",
      "# set some nicer defaults for matplotlib\n",
      "from matplotlib import rcParams\n",
      "\n",
      "#these colors come from colorbrewer2.org. Each is an RGB triplet\n",
      "dark2_colors = [(0.10588235294117647, 0.6196078431372549, 0.4666666666666667),\n",
      "                (0.8509803921568627, 0.37254901960784315, 0.00784313725490196),\n",
      "                (0.4588235294117647, 0.4392156862745098, 0.7019607843137254),\n",
      "                (0.9058823529411765, 0.1607843137254902, 0.5411764705882353),\n",
      "                (0.4, 0.6509803921568628, 0.11764705882352941),\n",
      "                (0.9019607843137255, 0.6705882352941176, 0.00784313725490196),\n",
      "                (0.6509803921568628, 0.4627450980392157, 0.11372549019607843),\n",
      "                (0.4, 0.4, 0.4)]\n",
      "\n",
      "rcParams['figure.figsize'] = (10, 6)\n",
      "rcParams['figure.dpi'] = 150\n",
      "rcParams['axes.color_cycle'] = dark2_colors\n",
      "rcParams['lines.linewidth'] = 2\n",
      "rcParams['axes.grid'] = False\n",
      "rcParams['axes.facecolor'] = 'white'\n",
      "rcParams['font.size'] = 14\n",
      "rcParams['patch.edgecolor'] = 'none'\n",
      "\n",
      "def remove_border(axes=None, top=False, right=False, left=True, bottom=True):\n",
      "    \"\"\"\n",
      "    Minimize chartjunk by stripping out unnecessary plot borders and axis ticks\n",
      "    \n",
      "    The top/right/left/bottom keywords toggle whether the corresponding plot border is drawn\n",
      "    \"\"\"\n",
      "    ax = axes or plt.gca()\n",
      "    ax.spines['top'].set_visible(top)\n",
      "    ax.spines['right'].set_visible(right)\n",
      "    ax.spines['left'].set_visible(left)\n",
      "    ax.spines['bottom'].set_visible(bottom)\n",
      "    \n",
      "    #turn off all ticks\n",
      "    ax.yaxis.set_ticks_position('none')\n",
      "    ax.xaxis.set_ticks_position('none')\n",
      "    \n",
      "    #now re-enable visibles\n",
      "    if top:\n",
      "        ax.xaxis.tick_top()\n",
      "    if bottom:\n",
      "        ax.xaxis.tick_bottom()\n",
      "    if left:\n",
      "        ax.yaxis.tick_left()\n",
      "    if right:\n",
      "        ax.yaxis.tick_right()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The website [govtrack.us](http://www.govetrack.us) collects data on activities in the Senate and House of Representatives. It's a great source of information for making data-driven assessments about Congress."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Problem 1.\n",
      "\n",
      "The directories at http://www.govtrack.us/data/congress/113/votes/2013 contain JSON information about every vote cast for the current (113th)  Congress. Subdirectories beginning with \"S\" correspond to Senate votes, while subdirectories beginning with \"H\" correspond to House votes.\n",
      "\n",
      "Write two functions: one that downloads and parses a single Senate vote page given the vote number, and another that repeatedly calls this function to build a full collection of Senate votes from the 113th Congress."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\"\"\"\n",
      "Function\n",
      "--------\n",
      "get_senate_vote\n",
      "\n",
      "Scrapes a single JSON page for a particular Senate vote, given by the vote number\n",
      "\n",
      "Parameters\n",
      "----------\n",
      "vote : int\n",
      "   The vote number to fetch\n",
      "   \n",
      "Returns\n",
      "-------\n",
      "vote : dict\n",
      "   The JSON-decoded dictionary for that vote\n",
      "   \n",
      "Examples\n",
      "--------\n",
      ">>> get_senate_vote(11)['bill']\n",
      "{u'congress': 113,\n",
      " u'number': 325,\n",
      " u'title': u'A bill to ensure the complete and timely payment of the obligations of the United States Government until May 19, 2013, and for other purposes.',\n",
      " u'type': u'hr'}\n",
      "\"\"\"\n",
      "#your code here\n",
      "\n",
      "def get_senate_vote(vote):\n",
      "    base_url = 'http://www.govtrack.us/data/congress/113/votes/2013/s%i/data.json'\n",
      "    url = base_url % vote\n",
      "    r = requests.get(url)\n",
      "    return r.json()\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\"\"\"\n",
      "Function\n",
      "--------\n",
      "get_all_votes\n",
      "\n",
      "Scrapes all the Senate votes from http://www.govtrack.us/data/congress/113/votes/2013,\n",
      "and returns a list of dicts\n",
      "\n",
      "Parameters\n",
      "-----------\n",
      "None\n",
      "\n",
      "Returns\n",
      "--------\n",
      "votes : list of dicts\n",
      "    List of JSON-parsed dicts for each senate vote\n",
      "\"\"\"\n",
      "#Your code here\n",
      "\n",
      "\n",
      "def get_all_votes():\n",
      "    page = requests.get('https://www.govtrack.us/data/congress/113/votes/2013/').text\n",
      "    dom = web.Element(page)\n",
      "    votes = [a.attr['href'] for a in dom.by_tag('a')if a.attr['href'].startswith('s')]\n",
      "    return [get_senate_vote(i) for i in range(1, len(votes) + 1)]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "vote_data = get_all_votes()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Problem 2\n",
      "\n",
      "Now, turn these data into a NetworkX graph, according to the spec below. For details on using NetworkX, consult the lab materials for November 1, as well as the [NetworkX documentation](http://networkx.github.io/)."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\"\"\"\n",
      "Function\n",
      "--------\n",
      "vote_graph\n",
      "\n",
      "Parameters\n",
      "----------\n",
      "data : list of dicts\n",
      "    The vote database returned from get_vote_data\n",
      "\n",
      "Returns\n",
      "-------\n",
      "graph : NetworkX Graph object, with the following properties\n",
      "    1. Each node in the graph is labeled using the `display_name` of a Senator (e.g., 'Lee (R-UT)')\n",
      "    2. Each node has a `color` attribute set to 'r' for Republicans, \n",
      "       'b' for Democrats, and 'k' for Independent/other parties.\n",
      "    3. The edges between two nodes are weighted by the number of \n",
      "       times two senators have cast the same Yea or Nay vote\n",
      "    4. Each edge also has a `difference` attribute, which is set to `1 / weight`.\n",
      "\n",
      "Examples\n",
      "--------\n",
      ">>> graph = vote_graph(vote_data)\n",
      ">>> graph.node['Lee (R-UT)']\n",
      "{'color': 'r'}  # attributes for this senator\n",
      ">>> len(graph['Lee (R-UT)']) # connections to other senators\n",
      "101\n",
      ">>> graph['Lee (R-UT)']['Baldwin (D-WI)']  # edge relationship between Lee and Baldwin\n",
      "{'difference': 0.02, 'weight': 50}\n",
      "\"\"\"\n",
      "#Your code here\n",
      "import pandas as pd\n",
      "\n",
      "def node_color(s):\n",
      "    if '(R' in s:\n",
      "        return 'r'\n",
      "    if '(D' in s:\n",
      "        return 'b'\n",
      "    return 'k'\n",
      "\n",
      "data = vote_data  \n",
      "\n",
      "def vote_graph(data):\n",
      "    senators = set()\n",
      "    for row in data:\n",
      "        for vote_type in row['votes']:\n",
      "            for vote in row['votes'][vote_type]:\n",
      "                senators.add(vote['display_name'])\n",
      "    \n",
      "    weights = pd.DataFrame(np.zeros((len(senators), len(senators))), index=senators, columns=senators)\n",
      "    \n",
      "    for row in data:\n",
      "        for vote_type in ['Yea', 'Nay']:\n",
      "            # All names inside `row['votes'][vote_type]` voted the same\n",
      "            votes = row['votes'][vote_type]\n",
      "            for i in range(len(votes)):\n",
      "                for j in range(i + 1, len(votes)):\n",
      "                    sen1 = votes[i]['display_name']\n",
      "                    sen2 = votes[j]['display_name']\n",
      "                    weights[sen1][sen2] += 1\n",
      "                    weights[sen2][sen1] += 1\n",
      "    \n",
      "    graph = nx.Graph()\n",
      "    for s in senators:\n",
      "        graph.add_node(s)\n",
      "        graph.node[s]['color'] = node_color(s)\n",
      "        \n",
      "    for sen1, row in weights.iterrows():\n",
      "        for sen2, weight in row.iteritems():\n",
      "            if weight != 0:\n",
      "                graph.add_edge(sen1, sen2, weight=weight, difference=1. / weight)\n",
      "\n",
      "    return graph"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 99
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "votes = vote_graph(vote_data)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 100
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### How (and how not) to visualize networks\n",
      "\n",
      "Network plots often *look* impressive, but creating sensible network plots is tricky. From Ben Fry, the author of the Processing program:\n",
      "<blockquote>\n",
      "Usually a graph layout isn\u2019t the best option for data sets larger than a few dozen nodes. You\u2019re most likely to wind up with enormous spider webs or balls of string, and the mess seen so far is more often the case than not. Graphs can be a powerful way to represent relationships between data, but they are also a very abstract concept, which means that they run the danger of meaning something only to the creator of the graph. Often, simply showing the structure of the data says very little about what it actually means, even though it\u2019s a perfectly accurate means of representing the data. Everything looks like a graph, but almost nothing should ever be drawn as one.\n",
      "</blockquote>\n",
      "\n",
      "Let's look at bad and better ways of visualizing the senate vote network.\n",
      "\n",
      "First, consider the \"default\" plot from networkx."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#this makes sure draw_spring results are the same at each call\n",
      "np.random.seed(1)  \n",
      "\n",
      "color = [votes.node[senator]['color'] for senator in votes.nodes()]\n",
      "\n",
      "#determine position of each node using a spring layout\n",
      "pos = nx.spring_layout(votes, iterations=200)\n",
      "\n",
      "#plot the edges\n",
      "nx.draw_networkx_edges(votes, pos, alpha = .05)\n",
      "\n",
      "#plot the nodes\n",
      "nx.draw_networkx_nodes(votes, pos, node_color=color)\n",
      "\n",
      "#draw the labels\n",
      "lbls = nx.draw_networkx_labels(votes, pos, alpha=5, font_size=8)\n",
      "\n",
      "#coordinate information is meaningless here, so let's remove it\n",
      "plt.xticks([])\n",
      "plt.yticks([])\n",
      "remove_border(left=False, bottom=False)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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ANpsmbwEvATcCrwCdgPeAr3EzFZhIlB7EA00S8A4wHsgE9gKbgDRg5wn8Hnv2\n7Mnu3bsJBAJkZGTwP//zPzz55JM88sgjWg8h0gAo8Ig0cHPnzqWwsBC/38/QoUP53//93/2bvxsT\nDB7f2ZsTwel02sGruhwOB0lJSUSjUcLhMOeffz4fffQR/fv3Z9SoUezcuZOJEyfStm3bE/TUIlLb\nNEFLpIGZM2cOp556qj3bprCwEIjfTPrggw/sVlBdDDvAUYcdiLetKlauvvrqK/7+97/z7bff0qlT\nJ6655hpeeOGFmn5UEalDFHhEGpDi4mLuv/9+nE4nV155JT6fr8pAvYaxMiEcDvP222/j8/lYvnw5\nXbt2ZeHChbX9WCJyAinwiCS4uXPn4vF42LFjBzNmzCA9PZ0lS5aQkZFBSkoKjRs3rvDqSK0958mU\nn5/Pv//9b7Kzs+0DzFXPLYlIYlHgEamn5s6dS4cOHSgsLGTgwIGsWrXqgF+///77AWjdujUtWrTg\nww8/ZObMmTgcDp588klKSkooLi6ujcevVWeccQYul4vGjRuz9zhnBIlI/aDAI1JPORwOrr32Wj7/\n/HMef/zxA86gfP311zz66KPs2bOHvLw8nE4nH374IZFIBOuuQsX/3pBYV8+3bt1Kq1atAHRLSyTB\nabqWSD1mhZU9e/awa9cu7r//fs4++2xuuOEG1q1bB8CVV16JYRjHdNg30VgzhBYsWEBKSgq7du1i\n4MCBfPPNN/Tt27e2H09ETiBdSxepp5566ikmTZpEamoq5eXlPPLII7z00kts2rTJHqQnleXl5fHT\nTz8RiURYtmwZhYWFfPvtt0yePFnX0kUSnFpaIvXUCy+8gNPppGfPnrhcLn73u9+xZ88ehR2gefPm\nwM9Tl51OJ02bNuWxxx6ja9eujBo1ik2bNpGVlUWjRo2YMmWKwo5IglOFR6SeOvvss/nmm28oKSmh\nXbt2bNq0yf61pKQkysvLa/HpaldKSgplZWUkJSVx2mmnsWjRIr766iuKiorIz89n8ODBtf2IInKS\nqcIjUk+1atWKnTt30qhRIzZt2mRXMoAGHXYgPkTR5/Ph8/koLi7mzDPPpHfv3hQVFSnsiDRQCjwi\n9VTfvn1xuVzk5ubicrnw+/26abSfw+GgRYsWOJ1Otm/fzu233w7A9OnTa/nJRKS2KPCI1HEV5+lU\n5Ha7SUlJYdy4cdx6662Ulpbagadbt24n+zHrDKfTSbdu3fB6vZx66qm0atWK4cOH1/ZjiUgtU+AR\nqeOsmTHGcMlAAAAgAElEQVQHk5KSwrRp0zj77LNxOp32EL1vvvnmZD1enTNgwACaNm1KSUkJ+fn5\nPPvss7X9SCJSB2gOj0g9dOuttzJ37lyKi4vZs2cPd911F2lpaZSVlVFeXo7L5SIWi9X7oYLW93Gk\n15imiWEY9O/fnz59+lBaWsr69evZu3evzuyICKAKj0i9NGXKFL7++mtmzpzJbbfdxooVK8jPzycQ\nCLBu3TquueYaDMOgc+fOnHnmmRQXF9OrVy8GDhxIt27dSE5OZv369bRr147U1FSaN29Op06d6NBh\nJpBM/I+GxkAO0AHoBfwTOA3wAsMBH9AUSCe+dLQF0AlwAIOBHsT/nepGoBXQd//XJAGtgSuBWftf\n0xYYAJwF/ACcA5TicLSideu2tGjRgjZt2pCens6oUaNo2bIlAH6/n1NOOYVmzZrx5ptv0rFjR4LB\nIB6Ph0GDBunMjojYVOERqYf++Mc/8tlnnxGJRCgoKKj0axWrOi1atOCLL74AYNOmTeTn59OsWTN7\n8nJ2djaffvopLpeLwsJCysoGs2FDH+ATwA9cBTwOjADuJB6CugIPAN8DZwCvAROAW4B84B7gfOAb\n4sHmf4DOwDwgBpwLXEg8FJ0KnA38AxgCmEDK/qf3E43+Eshk4MC5/PWvb3Duuefy9ttvA/Fbahdc\ncAGnnHIKd955JwBXX301AGPGjFHYEZFKFHhE6pmSkhLmzZvHF198wezZs3nrrbcA7IGDy5cvt19b\n8fxPz549efPNN/H5fLjdbnw+n/2acDhMLBajaVPr9V8DvYENQEvigeUp4gHGIF7FGQDct//1WcAy\n4oFnGVAOfAvMAC4DLgFWE68YOYHbABfxENRs/+fmVPlOHcBN/PTTBSxf3h2Px1PpV7t3787rr79+\n0J+Rwo6IVKWWlkg98Je//IUhQ4YwZMgQli1bRmpqKoMGDWLGjBl2qBk+fDgDBw5k7ty59uf69OnD\nJZdcwrx587jrrru47LLLuPDCC7nmmmvs9w4EAhiGgdvt5pxzrD8S/ka8enMt8XbVhcBAYBBwOvEA\nU9Gvgf8Chu7/2GpXuYgHpGHEA4/1/oOJV3ReBZ4jXtkZu//XxgH/Bs4DbgI6sn497Nnzc4C76KKL\n2LBhg/27T5w4kcLCQvvj6dOnV6p8LVu2jMcff/yIP2cRSVyatCyS4EKhENFoFL/fj8vlOuDzVsUn\nFovx1VerGTQoj2jUVeVd5gGfAhcQb2fNIH4ex2L9MeIg3v56CcgA9gBpQBlwO/DiIZ7yU+A74gFn\nPHA/8fNA3xJvl83jT38K8fHHw5gzZ459DmnOnDmkpKRw6aWXsmfPHj777DMARo0aRWpqKpMmTSI/\nPx+ASy+9lPfff/9of3wikiBU4RFJULFYjLKyMkzTJCUlxQ47FT+fnJyM2+2mpKSEmTNnMnnybUSj\n7xziHVcRP8fzHvGwUwxcRPxMzm+IHzjOBDYSr9b89/7/vAj4E/HzPwA7gEurvPf/7n8fixWgCoi3\ny77hP/7jLG644QYAevXqxcUXX8yMGTNYtGgRffv2tc8uBQIBTNPkV7/6FR988IH9jrm5uSxZsqTa\nPz8RSSwKPCIJKBQKEQwG8fv9+P3+Q34+EomwePFi3nzzTS677DJmzZpFu3Yv0bRpuMo7msBs4hWe\npvs/9xhwN/AZ0JxGjR4HrgOuJl6xScfpjJCd/T906vQAYIWN/ybe8qroe6DjIb6bNkCArKwirrji\nCvuzQ4cO5eOPP+aDDz7gkkt+brHNnDmToUOH0q9fPxYtWmR/vlOnTqxaterwPzgRSVg6tCySQAzD\nsOfwpKSk2J+PxWIEg0F7OrNpmmzatIlFixZx7733smrVKhwOB48//jg9evRg586N3HRTJ0pKrH8n\nchBvLX1J/GzO+cBK4C7AQUpKGc8914elS6FDh9Po0QPWrHGwevVpPPYYPPUU3Hbbmfu//n+Bd4/w\nnVQctrgZyGDjxqspLNzCU089BUCjRo0Ih8OsXLmSzp0726/+6KOP+PHHH/nrX//K6tWr2bRpE5mZ\nmcfxUxWRRKDAI5Igqp7JgfgV9VAoRCwWs8/wBAIBFi9ezLvvvstzzz0HQL9+/Zg8eTJ+v59OnTrR\nqFEjunePcuutTmbPdhHvFrmBvxI/TNwRyMfvv4Zf//o0Hn8cPJ4Ya9cup6DAyVlngWnCunXxwNSq\nFcQrP78nfqYnqcrT5wLriLew4OeW1kriN8Xa0bfvX/jkk8pfNWbMGHbs2GF/HI1G2blzJ3PmxG98\nzZo1iw8//JCJEyeydu1aRo8efTw/YhGpxxR4ROo5wzAIBoM4nU6Sk5Ptm0zRaJRQKFSpqrNmzRoW\nLFjA7bffzo4dO2jatClvvvkmfr+fDh060LJlSzweD4Zh0KFDlE8+8bNunYN774U5cxy43U2B6ezb\ndw333PMxCxbcwLff7uHCC5288sorQOWr8D/fIIPU1BxKSzfx81X2ioYTb41ZgedqoNH+/3sNgFGj\nKn+Fw+Fg2LBhlT732Wef0bNnT/vjM844gyeffJKJEyeyevVqTj311GP5EYtIAtAtLZF6LBwOE4lE\nDqjqBINBTNPE7/fjdDrZs2cPRUVFPPHEE8yePRuAcePGcdVVV9GyZUs6duyI3+/HNE1isRher/eA\nuTfHwzRNfvMbg1deGU68pXWwf9caC7xx0K9v3hw2bYIKx5GOyrJly5g1a5Y9oFBEGh5VeETqIauq\n43A4KlV1IpEI4XAYj8eD1+slFouxZMkSvvrqKyZNmkQoFCIrK4uXX34Zj8dDbm4uTZo0we12E4lE\ncLvdld6vJoTDYcLhMKtWXYnDMRjTPNQfOwcPOwC//vWxhx2IDyns3r37sb+BiNR7qvCI1DPVreps\n27aNoqIi7rrrLlauXAnA5MmT6d27N+3ataNNmzZ4vV4Mw6j0dTX9nC6XC5/Ph8Ph4Jln4Le/Pbr3\nOfNMmD0bfL4jv1ZE5FBU4RGpJw5X1QmFQni9XrxeL+FwmMWLF/P222/z7LPPAvGJy1OmTKFRo0Zk\nZ2eTnJwMxM/51HT7yqoyuVwukpKSKoWom2+GWAzuuAMM48jvNWgQ/Pd/K+yIyPFThUekHrBCjc/n\ns8NJxQBkzdrZsGEDX331FbfddhvFxcWkpaUxffp0UlNT6dSpE82bN8ftdhONRnG73Xi93hprX1mH\npJ1OJz6f77DVogUL4Omn4f33IRI58NdPPRVuvBHGjYMazGIi0oAp8IjUYaZpUl5ebocaK5xY52Ks\nABQIBCgqKmLy5Ml8+umnQPzK9pgxY2jdujXt27fH5/Nh7C+r1GT7KhaLEQqFAPD5fJXWVxzJTz/B\nO+/Ali0QDkNaGpx/PvTvXyOPJiJiU+ARqaOqU9UxTZNVq1bx+eefc/vttxMOh2nfvj0vvvgijRs3\nplOnTqSlpQHU+O2rWCxGOBzGNE28Xq99nkhEpC5S4BGpYw52ABkOPKy8c+dOvvzyS+6++26+/fZb\nAB566CEGDBhAVlaWPVOnpttXhmEQCoUwDKPSwWkRkbpMgUekDql6rRwqDxb0+XzEYjGWLVvGa6+9\nZk9K7tWrF48++igtWrQgKysLv99f4+2rilOba/qgs4jIiabAI1IHHKqqU3VdxNatW/niiy+4+eab\nKS4upnHjxrzxxhukpaWRl5dHWloaDoejRkOJaZp2dcm6CSYiUt8o8IjUMut2U8WqjrXs05phEw6H\nWbhwIY888oh9KHn06NGMHz+ezMxM2rVrh8vlwjAM3G43vhq6x20djraerSYHEoqInEwKPCK1xGoR\nGYZx0KqO9bkffviBzz//nAkTJhCLxWjfvj0vvfQSaWlp5ObmkpSUhPU/45pqX1kVnZq+ui4iUlsU\neERqwcGqOhWXffp8PkpLS+2ZOtak5AceeICzzz6bnJwc0tPTcTgcGIZRY+2rikMDvV5vjU5eFhGp\nTQo8IidRxYO/1hTiip+zBgguX76cadOm8fTTTwNw+umn8+ijj5KRkUHHjh3tjeY11b46mqGBIiL1\nkQKPyElStYJzsM/t3LmTefPmcf3111NcXExqairTpk2jVatW5Obm0rhx4xptXx3P0EARkfpEgUfk\nJAgGg3YFx+VyHXArKxaL8a9//YsHHniA2bNnAzBq1Ch+9atfkZWVRatWrexDyTUx+6Zi0NHQQBFp\nCBR4RE4g67ZVxapO1Vk7GzZs4NNPP+X6668nFovRrl07XnzxRVq1akV2djYejwfTNGukfaWhgSLS\nUCnwiJwgFW9bHayqEwqFWLhwITfccAOrV68G4oeSCwsL6dy5M02aNME0TXuNxPG0rzQ0UEQaOgUe\nkRp2qKpOKBSyw8Z3333HCy+8YB9KPu2005g8eTLt27enXbt29mHm463CaGigiEicAo9IDapa1am6\n7HP37t3MmzeP6667jh07dpCSksK0adPIzMwkLy/PXghaE+2rUChEJBLR0EARERR4RGqEYRiUl5fj\ncrnsq+XWlGLrmveyZcu4++67mTVrFgBXXHEF119/Pbm5uaSnp9dY+0pDA0VEDqTAI3Kcqu67qlrV\n2bZtG//4xz/45S9/SSwWIzMzk5deeok2bdqQlZWF2+2ukfZVxaGBPp9PQUdEpAIFHpFjVHWLucPh\nsKsrPp8PwzBYuHAh1113nX0o+d577+WCCy4gNzeX1NRUgONuX2looIjIkSnwiByDisGmYlXHCh3r\n16/n2Wef5T//8z+B+KHkKVOmkJ2dTevWrQGOO6BoaKCISPUp8IgchartKofDUamlFQqF+OKLLxgz\nZgwlJSUkJyczdepUsrOzycnJsVtWx9O+UtARETl6Cjwi1VS1qmNdP7cWba5YsYLf//73fPLJJwBc\ndtllTJw4kc6dO9OoUSMcDsdxta80NFBE5Ngp8IgcweGqOn6/n7179/LJJ58wZswYDMMgMzOTl19+\nmfbt29O+fXsA+yDxsbSvNDRQROT4KfCIHIZ188kKGhWXfbpcLhYvXsy4ceP47rvvALj77rsZMWIE\nnTt3tg8yH2s1xhoaGI1G7Vk6IiJybBR4RA7CNE3Ky8vtqg5gV1msq+ZPP/00/+///T8AevbsyR//\n+Efy8vJo3rz5cbWvNB1ZRKTmKfCIVGGtgfD5fAdUdQDmz5/PL37xC3bu3ElSUhJTp04lLy+PnJwc\nHA7HcbWvrGGFmo4sIlKzFHhE9qu43DMpKQnA/tjn87FmzRpuvfVWZs6cCcCll17KLbfcQufOnUlO\nTravmR9L+0pDA0VETiwFHhF+DhxWZaXix8FgkFmzZjFq1CgMw6B169ZMmzaNrKwsMjIycDgceDye\nY2pfaWigiMjJocAjDVrFqo51A8v62Ov1snz5ckaNGmVPSv7d737H5ZdfTm5uLi6Xyz6nc7RBJRqN\nEg6HAc3SERE5GRR4pMGyqisVqzrW2Z3du3fz1FNPMXnyZAC6devGU089RV5eHk2aNDnm9pWGBoqI\n1A4FHmlwqlZ1AHvOjtvtZuHChYwcOZLdu3fj9/uZOnUqp5xyCu3bt8fpdB5T+0pDA0VEapf+1JUG\npWpVx7oV5fP52Lx5MxMmTLAPJY8cOZLf/e539kydY2lfGYZBOBzW0EARkVqmCo80CNa0YsMwDqjq\nmKbJ7NmzufTSSzEMg1atWvH666/bM3Wsm1NHU5XR0EARkbpFgUcSXsU5Oj6fr9JQv++++47LLrvM\nPpR85513Mnr0aDp16oTL5Trq9pWGBoqI1E0KPJLQgsGgPR3Z+tjlchEIBHjqqad4+OGHATjllFN4\n5pln6Ny5MykpKXbQOZr2lYYGiojUXQo8kpCsTeZWVcda9unxePj666+54IIL2LVrFz6fjzfeeIMe\nPXqQkZFxTO0rDQ0UEan7NOVMEk4oFCIYDOL3+3G73ZSVlWGaJrt37+bSSy+lb9++7Nq1ixEjRjBv\n3jyGDBlCRkYGfr+flJSUaoedaDRKWVkZ0WiUpKQke46PiIjUParwSMKoWtWx2lkul4u5c+cyfPhw\nDMOgZcuWvPnmm+Tn59OkSZOjbl9ZQwMdDgder1ezdERE6gFdS5eEYLWs/H4/pmlSVlaG2+1m69at\njBgxgu+++w6A22+/nXHjxtGuXTs76FS3oqOhgSIi9ZcqPFKvWVUd6/xMKBQiFosRi8X485//zP33\n3w/EDyU///zz5Ofn4/P58Pv91b5BpaGBIiL1n/7klnrLqupY18YDgQAul4vVq1czaNAg+1Dy9OnT\nOf3002nevDler7faZ200NFBEJHHo0LLUO4ZhEAgEME2TpKQk+5ZUWVkZv/jFLzjttNPYtWsXw4YN\n46uvvmLIkCG0bNmSlJQUkpKSjhh2rNUT5eXluFwu+5q6iIjUX2ppSb1iDfXz+Xz2kD+Hw0FRURGD\nBw+2DyW/9dZbFBQUkJKSUu32lYYGiogkLgUeqRcMw7BXQVhndUzTpLi4mPPPP7/SoeTrrruOjIyM\no2pfaWigiEhiU+CROq9qVce6KfXMM89wzz33ANC1a1defvll8vLy7EPJ1TlcrKGBIiINgwKP1FkV\nqzper5dQKITD4eCHH37grLPOYteuXXg8Ht5++2169epFWloaSUlJ1WpFVQw6Xq/3qFZIiIhI/aM/\n5aVOCofDlJeX4/F4cLlclJeXU1ZWxlVXXUW3bt3YtWsXF1xwAYsWLWLQoEG0bNmSxo0bHzHsHGw6\nssKOiEji07V0qVNM06S8vByHw4Hf77fbV0uXLuWss87CMAxatGjB3/72N7p06UJycnK12lcVhwb6\n/X4NDRQRaWDU0pI6w2ozeb1eTNMkEomwe/duhgwZwsqVKwGYNGkSv/nNb2jZsmW12lcaGigiIqAK\nj9QB1twb0zQr3cB68cUXmTRpEgBdunTh9ddfJzs7u1qLOjU0UEREKlKFR2pVxaqOYRhEo1G2bNlC\nv3792LlzJwAffvghvXr1okmTJkdsX1m3uBR0RESkIp3WlFphndWxhvyFw2FKS0u59tprycvLY+fO\nnQwfPpzly5dz9tln06JFC1JTUw8ZdqygU1ZWhtPp1HRkERGpRBUeOemi0SihUAiPx4NhGMRiMb75\n5hsGDBiAYRg0b96cDz/8kPz8fHtS8uHaVxoaKCIiR6LAIydNxbM6brebSCTC3r17Of/881m+fDkQ\nP5R84403kp6eTnJy8mFvU2looIiIVJcCj5wUVlXH7XbbN7Bee+01br31ViB+KPnNN9+kU6dOJCcn\nH/b2lYYGiojI0VLgkRPKOltjGIZd1dm2bRu9e/e2DyV//PHH9OzZk7S0tMO2r6zQ5HQ68fl8Cjoi\nIlJt+htDTphoNEogEADA4XBQXl7OtddeS3Z2tn0oeeXKlZx55pn2XJ2DhZ1YLEYgECAcDuP3+0lK\nSlLYERGRo6I5PHJCBINBYrEYLpeLWCzGqlWr6N27N6Zp0qRJE2bOnEleXh6pqamHbF9paKCIiNQU\n/Wuy1KhYLEZZWRkATqeTPXv2cMYZZ9CrVy9M02TSpEksX76cHj160LRp04OGHcMwKC8vp7y8HLfb\nTUpKisKOiIgcF/0tIjUmFAoRjUZxuVxEIhHefPNNbrzxRgDy8vJ49913ycrKIiUl5aC3rzQ0UERE\nThQdWpbjFovFCAaDOJ1OTNNkx44d9OrVi+LiYgBmzJhBnz59aNSo0UErOqZpEg6H7SGER9qPJSIi\ncrTU0pLjEgqF7LATDoe57rrr6NChA8XFxQwdOpQ1a9Zwzjnn0KxZs4MGmXA4bLfAUlJSFHZEROSE\nUIVHjolV1bFuVa1Zs4aePXtiGAaNGzdm1qxZFBQUHLJ9ZVV0NDRQREROBlV45KhZVR2Hw0EgEODM\nM8+kR48eGIbBpEmTWLVqFaeddhqNGzc+IOxEIhHKysowDKNaW89FRERqgio8Um3W7SmIn7t56623\nuP766wHo3Lkz77//PllZWQcNMRoaKCIitUm3tKRarBYUwO7du+nZs6d9KHnOnDmcdtppNGrU6ICK\nTiwWIxQKAeD3+w+7G0tERORE0b9my2EZhkEgECASiWAYBhMmTCAzM5Pi4mKGDRvGxo0bGThwIGlp\naZXCTCwWo7y8nFAohNfrPeIiUBERkRNJFR45JKuqY5omW7ZsoaCggFgsRnJyMl999RV5eXkHrIPQ\ndGQREamLVOGRA1hVnVAoRCQS4ayzzqJz587EYjHuvPNONm3aRLdu3UhOTrbDjmmaBINBTUcWEZE6\nSYeWpZJwOEw4HMY0Td577z1++ctfApCTk8OsWbPIzMysNCtHQwNFRKQ+UOARIF7VsRZ+lpWV0b17\nd/tQ8vz58znttNMOaF9Z4cjj8eD1enW9XERE6iy1tMSejRONRvntb39LRkYGxcXFjBw5km3bttG/\nf/9K7StrOrJpmqSkpGhwoIiI1Hmq8DRg1rmbcDhMSUkJ2dnZQPz6+L/+9S+ys7Px+Xz26yORCOFw\nGJfLhdfr1SwdERGpN/Q3VgMViUQoLS0lFAoxePBgO+zcc8897Nixgy5duthhJxqN2hUgazqywo6I\niNQnukbTwFSs6nz00UeMHTsWgE6dOvHVV1/RokULe16OhgaKiEiiUOBpQKLRKOXl5QQCAbp37872\n7dsBKCoq4tRTT7VvWFUMOl6vV9fLRUSk3lNfogEwTZPy8nJKS0u57bbbaN26Ndu3b+fiiy9m7969\n9O7dG6/Xa+/KCgaD9nRkhR0REUkE+tsswVlVnd27d9OhQwdM0yQpKYmVK1eSmZmJy+Wy21yxWAyv\n14vH46ntxxYREalRqvAkKCvElJaWUlhYSPv27TFNkwcffNAOP06nk1AoRFlZGU6nk5SUFIUdERFJ\nSLqWnoCi0SiBQICPPvqIMWPGAJCVlcXixYtp2rQpDofDXhuhoYEiItIQKPAkmGAwyL59++jatas9\nKXnlypXk5ubicrnsNRBut1tBR0REGgy1tBJELBZj79693HLLLbRs2ZLi4mIuueQSgsEg+fn5GIZB\nWVkZhmGQnJys6cgiItKgqMKTAILBIMXFxbRv3x6ApKQkNmzYQHp6un3F3Ol04vP5NDBQREQaJP3t\nV4/FYjH27NnDgAED7LAzZcoU9u3bR7NmzSgvLyccDuP3+0lKSlLYERGRBkvX0uupYDDIe++9Zx9K\n7tixIytXrsTj8dhDA30+n6Yji4iIoJZWvROLxSgtLSUvL8+elLxx40batGlDOBzGMAx8Pp8GBoqI\niFSgHkc9EgwGmThxImlpafak5HA4TIsWLQgGg7jdblJSUhR2REREqlCFpx4wDIPt27eTkZEBxA8l\n//TTT/h8PqLRqD1LR0RERA5OFZ46LhQK0a9fPzvs/OlPf2Lnzp04nU4cDgcpKSkKOyIiIkeg3kcd\nZRgG77//PldccQUQP5S8YsUKDMOwg47m6IiIiFSPAk8dFAwG6dChg30oedu2baSkpOB0OklKSlLQ\nEREROUpqadUhhmFwyy23kJSUxPbt27n00kvZt28fjRo1IikpCb/fr7AjIiJyDFThqUGmCTNnwt//\nDiUl4HJBq1YwejT06XP4rw0GgyQnJ2OaJsnJyWzduhW3261ZOiIiIjVAt7RqQDgMf/4zvPAC/PDD\nwV/TqxfcfDOMHVv584Zh0KtXL5YsWQLAE088wYQJExR0REREapACz3Haswcuvhjmzq3e68ePh5de\nArcbPvjgAy699FIAMjMzWblyJX6/X3N0REREapgCz3EIhWDIEJg//+i+7le/Mvnkk0y2bNkCwPbt\n20lLS8Pj8ZyApxQREREdWj4Ojz9+9GEH4NVXHWzZ0pvLLruMUChEixYtFHZEREROoIQPPHPnzsXj\n8bBjxw4A/vnPf+J0OtmwYQOzZs1ixowZbNiwwV7CeTjjx4/nh/2HdKLR+Jmd/b8LcH+VV78O/LvK\n5wLA9QCkpe2mpKSE4cOHM3bsWPsKekXnnHMOv/3tb+2PR4wYwfjx4wHo3Lkz5557LoMHD+amm26i\ntLQUgOuvv55AIHDE70VERKQhSfjAA3Dqqafy4YcfAvFzM71798bhcHD++eczbNgwjqWr99FHsHmz\n9dHBropfC5xW5XNvASMB2L3bwX/91xxmz57N+PHjmTBhwgHv4HA42LRpEwD79u1j79699rX0li1b\n8tlnn/Hpp5/St29f7r8/HrhGjhzJ22+/fdTfj4iISCJL+MDjcDg499xzmTNnDgArVqyga9eumKbJ\ntGnTePXVV+0QEY1Gufrqq/niiy8oLCzEMAwACgsLK73nBx98wG9+0xcYDHxS4Vf2AhcB3wIPAnOq\nPM0M4Bz7ow8/NO3337Nnj/37VdS7d28WLVrEjBkzDhnOxo4dy9dffw3A2Wefzccff1ydH42IiEiD\nkfCBB8Dr9eL3+ykqKqKgoMAODRWH+IXDYcaNG8f111/PWWedddj3++CDDzjllL8BnwJD9392DzAG\neAwo4OBVnxIg5eePSn5+TcuWLe22W0WXXHIJ77//PjNmzGD48OGHfCbre0lNTaWkpOSwzy8iItLQ\nNIjAAzBs2DBuuOEG+xp4VfPnz8fr9dphp2IYqlpVuffee/nhh4eB8cAawAT+m3gLq0u1n6ni0OTt\n27eTnp7OoEGDOPfcc9m2bRsAubm5rFixgkgkQuPGjQ/5XrpsJyIicmgNKvD06tWL3r17H/TXBw0a\nRLt27Xj22WcBaNKkCVu2bGHHjh389NNPlV7boUMHBg16GbgO+E/i1ZzxwMb/3979u0Qdx3Ecf3G5\niFNHeDi73Bi4OR4NIbo5uLnp4FAuzjqKBLc41I1OQlDR4CAaLtLi/5CztFmjNRwKlUr5o+h9j8dy\nHPf9fL9vbnrC93PfS/LumimaSb5cvHv0qB8pBwcHaTabaTQa2dvby/7+flqt1sVxs7Oz126q3tra\nysTERJLk9PQ0zWbzmhkAYPAMxBPuzv9dvNfrXfrZ+eva2lqWlpayvb2dhYWFzMzMZHJyMqOjoz+s\nWVvPgJ8AAAHSSURBVF1dzdHRxySn6QfPt/Tb8VWSuSQPz8/+09WmknxIMp0kefPmSXZ3hzI2NpbN\nzc0rZ5+fn0+SHB8fX8x7cnKSTqeTRqORdrud9fX1JP1fpV136wsABpEHD97Q2VkyPp58+vQnq74m\nWU7yMlNTyX3sLV5cXEy3283w8PDdnxwA/lOC5xY2NpKVlZut3dlJnj6923kAgMsNzB6e+7C8fLNo\nef5c7ADA3yR4bmFoKHn9Opme/v01z54lL17c30wAwK8Ezy2NjCRv3ya9XvL48dXHdTr947rdpOFb\nB4C/yh6eO3Z4mLx/n3z+nDx4kLRaydxc0m7/68kAYHAJHgCgPDdXAIDyBA8AUJ7gAQDKEzwAQHmC\nBwAoT/AAAOUJHgCgPMEDAJQneACA8gQPAFCe4AEAyhM8AEB5ggcAKE/wAADlCR4AoDzBAwCUJ3gA\ngPIEDwBQnuABAMoTPABAeYIHAChP8AAA5QkeAKA8wQMAlCd4AIDyBA8AUJ7gAQDKEzwAQHmCBwAo\nT/AAAOUJHgCgPMEDAJQneACA8gQPAFCe4AEAyhM8AEB5ggcAKE/wAADlCR4AoDzBAwCUJ3gAgPIE\nDwBQnuABAMoTPABAeYIHACjvOzAlGYoA0BayAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10697b790>"
       ]
      }
     ],
     "prompt_number": 101
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The spring layout tries to group nodes with large edge-weights near to each other. In this context, that means it tries to organize the Senate into similarly-voting cliques. However, there's simply too much going on in this plot -- we should simplify the representation."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Problem 3\n",
      "\n",
      "Compute the `Minimum Spanning Tree` of this graph, using the `difference` edge attribute as the weight to minimize. A [Minimum Spanning Tree](http://en.wikipedia.org/wiki/Minimum_spanning_tree) is the subset of edges which trace at least one path through all nodes (\"spanning\"), with minimum total edge weight. You can think of it as a simplification of a network.\n",
      "\n",
      "Plot this new network, making modifications as necessary to prevent the graph from becoming too busy."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#Your code here\n",
      "\n",
      "mst = nx.minimum_spanning_tree(votes, weight='difference')\n",
      "pos = nx.spring_layout(mst, iterations=900, k=.008, weight='difference')\n",
      "\n",
      "mst_edges = list(nx.minimum_spanning_edges(votes, weight='difference'))\n",
      "\n",
      "nodes = votes.nodes()\n",
      "node_color = [votes.node[node]['color'] for node in nodes]\n",
      "\n",
      "plt.figure(figsize=(20, 15))\n",
      "nx.draw_networkx_edges(votes, pos, edgelist=mst_edges, alpha=.1)\n",
      "nx.draw_networkx_nodes(votes, pos, nodelist=nodes, node_color=node_color, node_size=70)\n",
      "    \n",
      "nx.draw_networkx_labels(votes, pos, font_color='k', font_size=8)\n",
      "\n",
      "None"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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BgYFyOByKj49XdHS0Ro4cKafTqQMHDigyMlIjR47UVVddpczMTEnSuHHj1L9/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RtODw/yYmIImDgRlVYLlHWldU2DcwWbS0tLsdlsWCwWzGYzarUaX19ffH19L+q9fs6cOZdxBoQQ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ap08HLy8eBNIqrwNYJ09mxKhRbtExldFqtXTq1El5PXXqVDIzM5Wqc8eOHQPgq6++onPnztX2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\n1uXLlwlfAaCKImgCgLtEVFSU7Ha77Ha79u/fL29vb3Xt2lUxMTFl3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       "text": [
        "<matplotlib.figure.Figure at 0x10ba43650>"
       ]
      }
     ],
     "prompt_number": 116
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Problem 4\n",
      "\n",
      "While this graph has less information, the remaining information is easier to digest. What does the Minimum Spanning Tree mean in this context? How does this graph relate to partisanship in the Senate? Which nodes in this graph are the most and least bi-partisan?"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "*Your answer here*"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Problem 5\n",
      "\n",
      "(For this problem, use the full graph for centrality computation, and not the Minimum Spanning Tree)\n",
      "\n",
      "Networkx can easily compute [centrality](https://en.wikipedia.org/wiki/Centrality) measurements. \n",
      "\n",
      "Briefly discuss what ``closeness_centrality`` means, both mathematically and in the context of the present graph -- how does the centrality relate to partisanship? Choose a way to visualize the `closeness_centrality` score for each member of the Senate, using edge `difference` as the distance measurement. Determine the 5 Senators with the highest and lowest centralities. \n",
      "\n",
      "Comment on your results. In particular, note the outliers John Kerry (who recently resigned his Senate seat when he became Secretary of State), Mo Cowan (Kerry's interim replacement) and Ed Markey (Kerry's permanent replacement) have low centrality scores -- why?"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "*Your discussion here*"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#Your code here\n",
      "bet = nx.closeness_centrality(votes, distance='difference')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 117
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bet = pd.Series(bet)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 119
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bet.sort()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 121
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bet.head() # Low centrality"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 123,
       "text": [
        "Kerry (D-MA)          3.951295\n",
        "Booker (D-NJ)        17.922960\n",
        "Lautenberg (D-NJ)    25.513331\n",
        "Chiesa (R-NJ)        39.967862\n",
        "Markey (D-MA)        46.296159\n",
        "dtype: float64"
       ]
      }
     ],
     "prompt_number": 123
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bet.tail() # High closeness"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 124,
       "text": [
        "Hagan (D-NC)        97.773597\n",
        "Donnelly (D-IN)     97.828705\n",
        "Pryor (D-AR)        99.232935\n",
        "Manchin (D-WV)      99.797537\n",
        "Collins (R-ME)     103.251265\n",
        "dtype: float64"
       ]
      }
     ],
     "prompt_number": 124
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.figure(figsize=(20, 5))\n",
      "bet.plot(kind='bar')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 128,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x10ecc3b10>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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8n332WW3atEmbN2/WVVddpalTp2rgwIEhny3tfmbs169f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Io73SybmidcVkMjcOZ0xY+Pj4wMfHh2eLQIlA7Nu3r8dNoKhpq1xlqqamhrdrpbtuyxZzpwt0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\nCoVCoVAoFEov5f8AWHGazmMigd4AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10ecc3b90>"
       ]
      }
     ],
     "prompt_number": 128
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Problem 6\n",
      "\n",
      "Centrality isn't a perfect proxy for bipartisanship, since it gauges how centralized a node is to the network as a whole, and not how similar a Democrat node is to the Republican sub-network (and vice versa).\n",
      "\n",
      "Can you come up with another measure that better captures bipartisanship than closeness centrality? Develop your own metric -- how does it differ from the closeness centrality? Use visualizations to support your points."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#your code here\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 13
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "*Your discussion here*"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Leadership in the Senate\n",
      "\n",
      "There are many metrics to quantify the leadership in the Senate.\n",
      "\n",
      "  1. Senate leaders sponsor and co-sponsor lots of bills\n",
      "  2. Leaders sit on many committees, as well as more important committees\n",
      "  3. Leaders usually have been in office for a long time\n",
      "  \n",
      "Another approach uses the philosophy behind how Google ranks search results. The core idea behind Google's PageRank algorithm is:\n",
      "\n",
      "1. A \"good\" website (i.e. one to rank highly in search results) is linked to by many other websites\n",
      "2. A link found on a \"good\" website is more important than a link found on a \"bad\" website\n",
      "\n",
      "The PageRank algorithm thus assigns scores to nodes in a graph based on how many neighbors a node has, as well as the score of those neighbors.\n",
      "\n",
      "This technique can be adapted to rank Senate leadership. Here, nodes correspond to Senators, and edges correspond to a senator co-sponsoring a bill sponsored by another Senator. The weight of each edge from node A to B is the number of times Senator A has co-sponsored a bill whose primary sponsor is Senator B. If you interpret the PageRank scores of such a network to indicate Senate leadership, you are then assuming:\n",
      "\n",
      "1. Leaders sponsor more bills\n",
      "1. Leaders attract co-sponsorship from other leaders\n",
      "\n",
      "### Problem 7\n",
      "\n",
      "Govtrack stores information about each Senate bill in the current congress at http://www.govtrack.us/data/congress/113/bills/s/. As in problem 1, write two functions to scrape these data -- the first function downloads a single bill, and the second function calls the first to loop over all bills."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\"\"\"\n",
      "Function\n",
      "--------\n",
      "get_senate_bill\n",
      "\n",
      "Scrape the bill data from a single JSON page, given the bill number\n",
      "\n",
      "Parameters\n",
      "-----------\n",
      "bill : int\n",
      "   Bill number to fetch\n",
      "   \n",
      "Returns\n",
      "-------\n",
      "A dict, parsed from the JSON\n",
      "\n",
      "Examples\n",
      "--------\n",
      ">>> bill = get_senate_bill(10)\n",
      ">>> bill['sponsor']\n",
      "{u'district': None,\n",
      " u'name': u'Reid, Harry',\n",
      " u'state': u'NV',\n",
      " u'thomas_id': u'00952',\n",
      " u'title': u'Sen',\n",
      " u'type': u'person'}\n",
      ">>> bill['short_title']\n",
      "u'Agriculture Reform, Food, and Jobs Act of 2013'\n",
      "\"\"\"\n",
      "#your code here\n",
      "def get_senate_bill(bill):\n",
      "    url = 'http://www.govtrack.us/data/congress/113/bills/s/s%i/data.json' % bill\n",
      "    r = requests.get(url)\n",
      "    return r.json()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 131
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\"\"\"\n",
      "Function\n",
      "--------\n",
      "get_all_bills\n",
      "\n",
      "Scrape all Senate bills at http://www.govtrack.us/data/congress/113/bills/s\n",
      "\n",
      "Parameters\n",
      "----------\n",
      "None\n",
      "\n",
      "Returns\n",
      "-------\n",
      "A list of dicts, one for each bill\n",
      "\"\"\"\n",
      "#your code here\n",
      "def get_all_bills():\n",
      "    page = requests.get('http://www.govtrack.us/data/congress/113/bills/s/').text\n",
      "    dom = web.Element(page)\n",
      "    links = [a.attr['href'] for a in dom.by_tag('a') if a.attr['href'].startswith('s')]\n",
      "    return [get_senate_bill(i) for i in range(1, len(links) + 1)]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 132
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bill_list = get_all_bills()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 133
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Problem 8\n",
      "\n",
      "Write a function to builded a Directed Graph (DiGraph) from these data, according to the following spec:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\"\"\"\n",
      "Function\n",
      "--------\n",
      "bill_graph\n",
      "\n",
      "Turn the bill graph data into a NetworkX Digraph\n",
      "\n",
      "Parameters\n",
      "----------\n",
      "data : list of dicts\n",
      "    The data returned from get_all_bills\n",
      "\n",
      "Returns\n",
      "-------\n",
      "graph : A NetworkX DiGraph, with the following properties\n",
      "    * Each node is a senator. For a label, use the 'name' field \n",
      "      from the 'sponsor' and 'cosponsors' dict items\n",
      "    * Each edge from A to B is assigned a weight equal to how many \n",
      "      bills are sponsored by B and co-sponsored by A\n",
      "\"\"\"\n",
      "#Your code here\n",
      "\n",
      "def bill_graph(data):    \n",
      "    graph = nx.DiGraph()\n",
      "\n",
      "    for bill in data:\n",
      "        sponsor = bill['sponsor']\n",
      "        sponsor_name = bill['sponsor']['name']\n",
      "    \n",
      "        if sponsor not in graph:\n",
      "            graph.add_node(sponsor_name, **sponsor)\n",
      "        \n",
      "        for cosponsor in bill['cosponsors']:\n",
      "            cosponsor_name = cosponsor['name']\n",
      "            if cosponsor_name not in graph:\n",
      "                graph.add_node(cosponsor_name, **cosponsor)\n",
      "            \n",
      "            # TODO make try except -> if else\n",
      "            try:\n",
      "                w = graph[cosponsor_name][sponsor_name]['weight'] + 1\n",
      "            except KeyError:\n",
      "                w = 1\n",
      "            graph.add_edge(cosponsor_name, sponsor_name, weight=w)    \n",
      "\n",
      "    return graph"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 145
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bills = bill_graph(bill_list)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 146
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Problem 9\n",
      "\n",
      "Using `nx.pagerank_numpy`, compute the PageRank score for each senator in this graph. Visualize the results. Determine the 5 Senators with the highest\n",
      "PageRank scores. How effective is this approach at identifying leaders? How does the PageRank rating compare to the degree of each node?\n",
      "\n",
      "Note: you can read about individual Senators by searching for them on the [govtrack website](https://www.govtrack.us/)."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#Your code here\n",
      "pagerank = nx.pagerank_numpy(bills)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 147
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pagerank = pd.Series(pagerank)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 149
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pagerank.sort()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 150
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pagerank.head() # Low scores"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 151,
       "text": [
        "Booker, Cory A.      0.001454\n",
        "Cowan, William M.    0.001454\n",
        "Kerry, John F.       0.001454\n",
        "Scott, Tim           0.001454\n",
        "Sessions, Jeff       0.001454\n",
        "dtype: float64"
       ]
      }
     ],
     "prompt_number": 151
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pagerank.tail() # High scores"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 152,
       "text": [
        "Menendez, Robert        0.025490\n",
        "Lautenberg, Frank R.    0.026281\n",
        "Reid, Harry             0.026814\n",
        "Harkin, Tom             0.029588\n",
        "Brown, Sherrod          0.029829\n",
        "dtype: float64"
       ]
      }
     ],
     "prompt_number": 152
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#Your code here\n",
      "deg = nx.degree(bills)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 153
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "deg = pd.Series(deg)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 156
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data = pd.DataFrame(index=pagerank.index)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 157
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data['pagerank'] = pagerank\n",
      "data['deg'] = deg"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 158
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from ggplot import *"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 162
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ggplot(aes(x='deg', y='pagerank'), data=data) + geom_point()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 165,
       "text": [
        "<ggplot: (284397697)>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
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Ha968efzbiS7B60JwZWWljEajoqKiHMfi4uJUVFTk0ra8vFxJSUlO7Y4ePar6+noFBQU5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\nVIPlyhiuI14AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x114ff3dd0>"
       ]
      }
     ],
     "prompt_number": 165
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "*Your discussion here*"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Interactive Visualization\n",
      "\n",
      "Producing a good node link layout is not quite so simple. Nevertheless, we will give it a try. \n",
      "\n",
      "We will use [Gephi](https://gephi.org/) for interactive graph visualization. Gephi supports a wide variety of graph file formats, and NetworkX exports to several of them. We'll use the Graph Exchange XML Format (GEXF)."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "nx.write_gexf(votes, 'votes.gexf')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Problem 10: Analysis with Gephi\n",
      "\n",
      "Download and install [Gephi](https://gephi.org/). See the [lab](http://goo.gl/SzHioP) for a brief introduction. Load the exported votes file. Try to produce a layout that clearly separates Democrats from Republicans (hint: filter on edge weight and re-layout once you filtered). Run PageRank and some other statistics and try encoding them with node color and node size. Run the \"Modularity\" statistic and encode the results in color.\n",
      "\n",
      "Include a screenshot of your \"best\" visualization and embed the image here with `IPython.display.Image`. Make sure to include this image in your submission.\n",
      "\n",
      "Explain your observations. Is the network visualization very helpful? Try to visualize your LinkedIn network (see the lab) or the one provided in the lab. Which dataset is more suitable for visualization and why is there a difference?\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import Image\n",
      "\n",
      "path = 'name_of_your_screenshot'\n",
      "Image(path)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "*Your answer here*"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### How to Submit\n",
      "\n",
      "To submit your homework, create a folder named lastname_firstinitial_hw5 and place this notebook file in the folder. Double check that this file is still called HW5.ipynb, and that it contains your solutions. Also include any Gephi screenshots. Compress the folder (please use .zip compression) and submit to the CS109 dropbox in the appropriate folder. If we cannot access your work because these directions are not followed correctly, we will not grade your work."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "---\n",
      "*css tweaks in this cell*\n",
      "<style>\n",
      "div.text_cell_render {\n",
      "    line-height: 150%;\n",
      "    font-size: 110%;\n",
      "    width: 800px;\n",
      "    margin-left:50px;\n",
      "    margin-right:auto;\n",
      "    }\n",
      "</style>"
     ]
    }
   ],
   "metadata": {}
  }
 ]
}