8-US-airports-case-study-instructor.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploratory analysis of the US Airport Dataset\n",
    "\n",
    "This dataset contains data for 25 years[1995-2015] of flights between various US airports and metadata about these routes. Taken from Bureau of Transportation Statistics, United States Department of Transportation.\n",
    "\n",
    "Let's see what can we make out of this!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import networkx as nx\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "pass_air_data = pd.read_csv('datasets/passengers.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the `pass_air_data` dataframe we have the information of number of people that fly every year on a particular route on the list of airlines that fly that route."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>ORIGIN</th>\n",
       "      <th>DEST</th>\n",
       "      <th>UNIQUE_CARRIER_NAME</th>\n",
       "      <th>PASSENGERS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1990</td>\n",
       "      <td>ABE</td>\n",
       "      <td>ACY</td>\n",
       "      <td>{'US Airways Inc.'}</td>\n",
       "      <td>73.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1990</td>\n",
       "      <td>ABE</td>\n",
       "      <td>ATL</td>\n",
       "      <td>{'Eastern Air Lines Inc.'}</td>\n",
       "      <td>73172.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>1990</td>\n",
       "      <td>ABE</td>\n",
       "      <td>AVL</td>\n",
       "      <td>{'Westair Airlines Inc.'}</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>1990</td>\n",
       "      <td>ABE</td>\n",
       "      <td>AVP</td>\n",
       "      <td>{'Westair Airlines Inc.', 'US Airways Inc.', '...</td>\n",
       "      <td>8397.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>1990</td>\n",
       "      <td>ABE</td>\n",
       "      <td>BHM</td>\n",
       "      <td>{'Eastern Air Lines Inc.'}</td>\n",
       "      <td>59.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  YEAR ORIGIN DEST  \\\n",
       "0           0  1990    ABE  ACY   \n",
       "1           1  1990    ABE  ATL   \n",
       "2           2  1990    ABE  AVL   \n",
       "3           3  1990    ABE  AVP   \n",
       "4           4  1990    ABE  BHM   \n",
       "\n",
       "                                 UNIQUE_CARRIER_NAME  PASSENGERS  \n",
       "0                                {'US Airways Inc.'}        73.0  \n",
       "1                         {'Eastern Air Lines Inc.'}     73172.0  \n",
       "2                          {'Westair Airlines Inc.'}         0.0  \n",
       "3  {'Westair Airlines Inc.', 'US Airways Inc.', '...      8397.0  \n",
       "4                         {'Eastern Air Lines Inc.'}        59.0  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pass_air_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a MultiDiGraph from this dataset\n",
    "\n",
    "passenger_graph = nx.from_pandas_edgelist(pass_air_data, source='ORIGIN', target='DEST', edge_attr=['YEAR', 'PASSENGERS', 'UNIQUE_CARRIER_NAME'], create_using=nx.MultiDiGraph())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cleveland to Chicago, how many people fly this route?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'PASSENGERS': 409943.0,\n",
       " 'UNIQUE_CARRIER_NAME': \"{'Frontier Airlines Inc.', 'SkyWest Airlines Inc.', 'Republic Airlines', 'ExpressJet Airlines Inc.', 'American Airlines Inc.', 'Swift Air, LLC', 'GoJet Airlines LLC d/b/a United Express', 'Trans States Airlines', 'Envoy Air', 'Spirit Air Lines', 'United Air Lines Inc.', 'Shuttle America Corp.'}\",\n",
       " 'YEAR': 2015}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "passenger_graph['CLE']['ORD'][25]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1095a8128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "temp = [(i['YEAR'], i['PASSENGERS'])for i in dict(passenger_graph['CLE']['ORD']).values()]\n",
    "x, y = zip(*temp)\n",
    "plt.plot(x, y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise\n",
    "\n",
    "Find the busiest route in 1990 and in 2015 according to number of passengers, and plot the time series of number of passengers on these routes.\n",
    "\n",
    "You can use the DataFrame instead of working with the network. It will be faster ;)\n",
    "[5 mins]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp = pass_air_data.groupby(['YEAR'])['PASSENGERS'].transform(max) == pass_air_data['PASSENGERS']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>ORIGIN</th>\n",
       "      <th>DEST</th>\n",
       "      <th>UNIQUE_CARRIER_NAME</th>\n",
       "      <th>PASSENGERS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3917</th>\n",
       "      <td>3917</td>\n",
       "      <td>1990</td>\n",
       "      <td>LAX</td>\n",
       "      <td>HNL</td>\n",
       "      <td>{'Heavylift Cargo Airlines Lt', 'Hawaiian Airl...</td>\n",
       "      <td>1827164.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>445978</th>\n",
       "      <td>445978</td>\n",
       "      <td>2015</td>\n",
       "      <td>LAX</td>\n",
       "      <td>SFO</td>\n",
       "      <td>{'Hawaiian Airlines Inc.', 'Delta Air Lines In...</td>\n",
       "      <td>1869066.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Unnamed: 0  YEAR ORIGIN DEST  \\\n",
       "3917          3917  1990    LAX  HNL   \n",
       "445978      445978  2015    LAX  SFO   \n",
       "\n",
       "                                      UNIQUE_CARRIER_NAME  PASSENGERS  \n",
       "3917    {'Heavylift Cargo Airlines Lt', 'Hawaiian Airl...   1827164.0  \n",
       "445978  {'Hawaiian Airlines Inc.', 'Delta Air Lines In...   1869066.0  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pass_air_data[temp][pass_air_data.YEAR.isin([1990, 2015])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10996ae80>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116b966a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pass_air_data[(pass_air_data['ORIGIN'] == 'LAX') & (pass_air_data['DEST'] == 'HNL')].plot('YEAR', 'PASSENGERS')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10fee4748>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fea3550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pass_air_data[(pass_air_data['ORIGIN'] == 'LAX') & (pass_air_data['DEST'] == 'SFO')].plot('YEAR', 'PASSENGERS')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So let's have a look at the important nodes in this network, i.e. important airports in this network. We'll use pagerank, betweenness centrality and degree centrality."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# nx.pagerank(passenger_graph)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def year_network(G, year):\n",
    "    temp_g = nx.DiGraph()\n",
    "    for i in G.edges(data=True):\n",
    "        if i[2]['YEAR'] == year:\n",
    "            temp_g.add_edge(i[0], i[1], weight=i[2]['PASSENGERS'])\n",
    "    return temp_g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "pass_2015 = year_network(passenger_graph, 2015)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1258"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(pass_2015)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25354"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(pass_2015.edges())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load in the GPS coordinates of all the airports\n",
    "lat_long = pd.read_csv('datasets/GlobalAirportDatabase.txt', delimiter=':', header=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1321</th>\n",
       "      <td>EGYC</td>\n",
       "      <td>CLF</td>\n",
       "      <td>COLTISHALL</td>\n",
       "      <td>COLTISHALL</td>\n",
       "      <td>ENGLAND</td>\n",
       "      <td>52</td>\n",
       "      <td>45</td>\n",
       "      <td>17</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>26</td>\n",
       "      <td>E</td>\n",
       "      <td>21</td>\n",
       "      <td>52.755</td>\n",
       "      <td>1.357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3380</th>\n",
       "      <td>KABI</td>\n",
       "      <td>ABI</td>\n",
       "      <td>ABILENE RGNL</td>\n",
       "      <td>ABILENE</td>\n",
       "      <td>USA</td>\n",
       "      <td>32</td>\n",
       "      <td>24</td>\n",
       "      <td>40</td>\n",
       "      <td>N</td>\n",
       "      <td>99</td>\n",
       "      <td>40</td>\n",
       "      <td>54</td>\n",
       "      <td>W</td>\n",
       "      <td>546</td>\n",
       "      <td>32.411</td>\n",
       "      <td>-99.682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3381</th>\n",
       "      <td>KABQ</td>\n",
       "      <td>ABQ</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ALBUQUERQUE</td>\n",
       "      <td>USA</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>U</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>U</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3382</th>\n",
       "      <td>KACK</td>\n",
       "      <td>ACK</td>\n",
       "      <td>NANTUCKET MEM</td>\n",
       "      <td>NANTUCKET</td>\n",
       "      <td>USA</td>\n",
       "      <td>41</td>\n",
       "      <td>15</td>\n",
       "      <td>10</td>\n",
       "      <td>N</td>\n",
       "      <td>70</td>\n",
       "      <td>3</td>\n",
       "      <td>36</td>\n",
       "      <td>W</td>\n",
       "      <td>15</td>\n",
       "      <td>41.253</td>\n",
       "      <td>-70.060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3383</th>\n",
       "      <td>KACT</td>\n",
       "      <td>ACT</td>\n",
       "      <td>WACO RGNL</td>\n",
       "      <td>WACO</td>\n",
       "      <td>USA</td>\n",
       "      <td>31</td>\n",
       "      <td>36</td>\n",
       "      <td>40</td>\n",
       "      <td>N</td>\n",
       "      <td>97</td>\n",
       "      <td>13</td>\n",
       "      <td>49</td>\n",
       "      <td>W</td>\n",
       "      <td>158</td>\n",
       "      <td>31.611</td>\n",
       "      <td>-97.230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3384</th>\n",
       "      <td>KACY</td>\n",
       "      <td>ACY</td>\n",
       "      <td>ATLANTIC CITY INTERNATIONAL</td>\n",
       "      <td>ATLANTIC CITY</td>\n",
       "      <td>USA</td>\n",
       "      <td>39</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>N</td>\n",
       "      <td>74</td>\n",
       "      <td>34</td>\n",
       "      <td>37</td>\n",
       "      <td>W</td>\n",
       "      <td>23</td>\n",
       "      <td>39.458</td>\n",
       "      <td>-74.577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3386</th>\n",
       "      <td>KADW</td>\n",
       "      <td>ADW</td>\n",
       "      <td>ANDREWS AFB</td>\n",
       "      <td>CAMP SPRINGS</td>\n",
       "      <td>USA</td>\n",
       "      <td>38</td>\n",
       "      <td>48</td>\n",
       "      <td>38</td>\n",
       "      <td>N</td>\n",
       "      <td>76</td>\n",
       "      <td>52</td>\n",
       "      <td>1</td>\n",
       "      <td>W</td>\n",
       "      <td>86</td>\n",
       "      <td>38.811</td>\n",
       "      <td>-76.867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3387</th>\n",
       "      <td>KAEX</td>\n",
       "      <td>AEX</td>\n",
       "      <td>ALEXANDRIA INTERNATIONAL</td>\n",
       "      <td>ALEXANDRIA</td>\n",
       "      <td>USA</td>\n",
       "      <td>31</td>\n",
       "      <td>19</td>\n",
       "      <td>38</td>\n",
       "      <td>N</td>\n",
       "      <td>92</td>\n",
       "      <td>32</td>\n",
       "      <td>54</td>\n",
       "      <td>W</td>\n",
       "      <td>28</td>\n",
       "      <td>31.327</td>\n",
       "      <td>-92.548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3389</th>\n",
       "      <td>KAGS</td>\n",
       "      <td>AGS</td>\n",
       "      <td>AUGUSTA RGNL AT BUSH FLD</td>\n",
       "      <td>BUSH FIELD</td>\n",
       "      <td>USA</td>\n",
       "      <td>33</td>\n",
       "      <td>22</td>\n",
       "      <td>11</td>\n",
       "      <td>N</td>\n",
       "      <td>81</td>\n",
       "      <td>57</td>\n",
       "      <td>52</td>\n",
       "      <td>W</td>\n",
       "      <td>44</td>\n",
       "      <td>33.370</td>\n",
       "      <td>-81.964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3391</th>\n",
       "      <td>KALB</td>\n",
       "      <td>ALB</td>\n",
       "      <td>ALBANY INTERNATIONAL</td>\n",
       "      <td>ALBANY</td>\n",
       "      <td>USA</td>\n",
       "      <td>42</td>\n",
       "      <td>44</td>\n",
       "      <td>53</td>\n",
       "      <td>N</td>\n",
       "      <td>73</td>\n",
       "      <td>48</td>\n",
       "      <td>10</td>\n",
       "      <td>W</td>\n",
       "      <td>87</td>\n",
       "      <td>42.748</td>\n",
       "      <td>-73.803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3394</th>\n",
       "      <td>KAMA</td>\n",
       "      <td>AMA</td>\n",
       "      <td>AMARILLO INTERNATIONAL</td>\n",
       "      <td>AMARILLO</td>\n",
       "      <td>USA</td>\n",
       "      <td>35</td>\n",
       "      <td>13</td>\n",
       "      <td>9</td>\n",
       "      <td>N</td>\n",
       "      <td>101</td>\n",
       "      <td>42</td>\n",
       "      <td>21</td>\n",
       "      <td>W</td>\n",
       "      <td>1100</td>\n",
       "      <td>35.219</td>\n",
       "      <td>-101.706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3395</th>\n",
       "      <td>KANB</td>\n",
       "      <td>ANB</td>\n",
       "      <td>ANNISTON METROPOLITAN</td>\n",
       "      <td>ANNISTON</td>\n",
       "      <td>USA</td>\n",
       "      <td>33</td>\n",
       "      <td>35</td>\n",
       "      <td>17</td>\n",
       "      <td>N</td>\n",
       "      <td>85</td>\n",
       "      <td>51</td>\n",
       "      <td>29</td>\n",
       "      <td>W</td>\n",
       "      <td>187</td>\n",
       "      <td>33.588</td>\n",
       "      <td>-85.858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3397</th>\n",
       "      <td>KAOO</td>\n",
       "      <td>AOO</td>\n",
       "      <td>ALTOONA BLAIR CO</td>\n",
       "      <td>ALTOONA</td>\n",
       "      <td>USA</td>\n",
       "      <td>40</td>\n",
       "      <td>17</td>\n",
       "      <td>47</td>\n",
       "      <td>N</td>\n",
       "      <td>78</td>\n",
       "      <td>19</td>\n",
       "      <td>12</td>\n",
       "      <td>W</td>\n",
       "      <td>459</td>\n",
       "      <td>40.296</td>\n",
       "      <td>-78.320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3399</th>\n",
       "      <td>KARA</td>\n",
       "      <td>ARA</td>\n",
       "      <td>ACADIANA REGIONAL</td>\n",
       "      <td>LOUISIANA</td>\n",
       "      <td>USA</td>\n",
       "      <td>30</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>N</td>\n",
       "      <td>91</td>\n",
       "      <td>53</td>\n",
       "      <td>2</td>\n",
       "      <td>W</td>\n",
       "      <td>8</td>\n",
       "      <td>30.038</td>\n",
       "      <td>-91.884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3400</th>\n",
       "      <td>KART</td>\n",
       "      <td>ART</td>\n",
       "      <td>WATERTOWN INTERNATIONAL</td>\n",
       "      <td>WATERTOWN</td>\n",
       "      <td>USA</td>\n",
       "      <td>43</td>\n",
       "      <td>59</td>\n",
       "      <td>30</td>\n",
       "      <td>N</td>\n",
       "      <td>76</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>W</td>\n",
       "      <td>100</td>\n",
       "      <td>43.992</td>\n",
       "      <td>-76.022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3401</th>\n",
       "      <td>KATL</td>\n",
       "      <td>ATL</td>\n",
       "      <td>THE WILLIAM B HARTSFIELD ATLANTA INTERNATIONAL</td>\n",
       "      <td>ATLANTA</td>\n",
       "      <td>USA</td>\n",
       "      <td>33</td>\n",
       "      <td>38</td>\n",
       "      <td>25</td>\n",
       "      <td>N</td>\n",
       "      <td>84</td>\n",
       "      <td>25</td>\n",
       "      <td>37</td>\n",
       "      <td>W</td>\n",
       "      <td>313</td>\n",
       "      <td>33.640</td>\n",
       "      <td>-84.427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3402</th>\n",
       "      <td>KAUG</td>\n",
       "      <td>AUG</td>\n",
       "      <td>AUGUSTA STATE</td>\n",
       "      <td>AUGUSTA</td>\n",
       "      <td>USA</td>\n",
       "      <td>44</td>\n",
       "      <td>19</td>\n",
       "      <td>14</td>\n",
       "      <td>N</td>\n",
       "      <td>69</td>\n",
       "      <td>47</td>\n",
       "      <td>50</td>\n",
       "      <td>W</td>\n",
       "      <td>108</td>\n",
       "      <td>44.321</td>\n",
       "      <td>-69.797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3403</th>\n",
       "      <td>KAUS</td>\n",
       "      <td>AUS</td>\n",
       "      <td>AUSTIN BERGSTROM INTERNATIONAL</td>\n",
       "      <td>AUSTIN</td>\n",
       "      <td>USA</td>\n",
       "      <td>30</td>\n",
       "      <td>11</td>\n",
       "      <td>40</td>\n",
       "      <td>N</td>\n",
       "      <td>97</td>\n",
       "      <td>40</td>\n",
       "      <td>11</td>\n",
       "      <td>W</td>\n",
       "      <td>166</td>\n",
       "      <td>30.194</td>\n",
       "      <td>-97.670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3406</th>\n",
       "      <td>KBAD</td>\n",
       "      <td>BAD</td>\n",
       "      <td>BARKSDALE AFB</td>\n",
       "      <td>SHREVEPORT</td>\n",
       "      <td>USA</td>\n",
       "      <td>32</td>\n",
       "      <td>30</td>\n",
       "      <td>6</td>\n",
       "      <td>N</td>\n",
       "      <td>93</td>\n",
       "      <td>39</td>\n",
       "      <td>45</td>\n",
       "      <td>W</td>\n",
       "      <td>51</td>\n",
       "      <td>32.502</td>\n",
       "      <td>-93.663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3407</th>\n",
       "      <td>KBCT</td>\n",
       "      <td>BCT</td>\n",
       "      <td>BOCA RATON</td>\n",
       "      <td>BOCA RATON</td>\n",
       "      <td>USA</td>\n",
       "      <td>26</td>\n",
       "      <td>22</td>\n",
       "      <td>42</td>\n",
       "      <td>N</td>\n",
       "      <td>80</td>\n",
       "      <td>6</td>\n",
       "      <td>27</td>\n",
       "      <td>W</td>\n",
       "      <td>4</td>\n",
       "      <td>26.378</td>\n",
       "      <td>-80.107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3409</th>\n",
       "      <td>KBDL</td>\n",
       "      <td>BDL</td>\n",
       "      <td>BRADLEY INTERNATIONAL</td>\n",
       "      <td>WINDSOR LOCKS</td>\n",
       "      <td>USA</td>\n",
       "      <td>41</td>\n",
       "      <td>56</td>\n",
       "      <td>20</td>\n",
       "      <td>N</td>\n",
       "      <td>72</td>\n",
       "      <td>40</td>\n",
       "      <td>59</td>\n",
       "      <td>W</td>\n",
       "      <td>53</td>\n",
       "      <td>41.939</td>\n",
       "      <td>-72.683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3410</th>\n",
       "      <td>KBDR</td>\n",
       "      <td>BDR</td>\n",
       "      <td>IGOR I SIKORSKY MEM</td>\n",
       "      <td>STRATFORD</td>\n",
       "      <td>USA</td>\n",
       "      <td>41</td>\n",
       "      <td>9</td>\n",
       "      <td>48</td>\n",
       "      <td>N</td>\n",
       "      <td>73</td>\n",
       "      <td>7</td>\n",
       "      <td>34</td>\n",
       "      <td>W</td>\n",
       "      <td>3</td>\n",
       "      <td>41.163</td>\n",
       "      <td>-73.126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3411</th>\n",
       "      <td>KBED</td>\n",
       "      <td>BED</td>\n",
       "      <td>LAURENCE G HANSCOM FLD</td>\n",
       "      <td>BEDFORD</td>\n",
       "      <td>USA</td>\n",
       "      <td>42</td>\n",
       "      <td>28</td>\n",
       "      <td>11</td>\n",
       "      <td>N</td>\n",
       "      <td>71</td>\n",
       "      <td>17</td>\n",
       "      <td>20</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>42.470</td>\n",
       "      <td>-71.289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3412</th>\n",
       "      <td>KBFI</td>\n",
       "      <td>BFI</td>\n",
       "      <td>BOEING FLD KING CO INTERNATIONAL</td>\n",
       "      <td>SEATTLE</td>\n",
       "      <td>USA</td>\n",
       "      <td>47</td>\n",
       "      <td>31</td>\n",
       "      <td>47</td>\n",
       "      <td>N</td>\n",
       "      <td>122</td>\n",
       "      <td>18</td>\n",
       "      <td>7</td>\n",
       "      <td>W</td>\n",
       "      <td>6</td>\n",
       "      <td>47.530</td>\n",
       "      <td>-122.302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3413</th>\n",
       "      <td>KBFL</td>\n",
       "      <td>BFL</td>\n",
       "      <td>MEADOWS FLD</td>\n",
       "      <td>BAKERSFIELD</td>\n",
       "      <td>USA</td>\n",
       "      <td>35</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>119</td>\n",
       "      <td>3</td>\n",
       "      <td>24</td>\n",
       "      <td>W</td>\n",
       "      <td>155</td>\n",
       "      <td>35.433</td>\n",
       "      <td>-119.057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3414</th>\n",
       "      <td>KBFM</td>\n",
       "      <td>BFM</td>\n",
       "      <td>MOBILE DOWNTOWN</td>\n",
       "      <td>MOBILE</td>\n",
       "      <td>USA</td>\n",
       "      <td>30</td>\n",
       "      <td>37</td>\n",
       "      <td>35</td>\n",
       "      <td>N</td>\n",
       "      <td>88</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>W</td>\n",
       "      <td>8</td>\n",
       "      <td>30.626</td>\n",
       "      <td>-88.068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3415</th>\n",
       "      <td>KBGR</td>\n",
       "      <td>BGR</td>\n",
       "      <td>BANGOR INTERNATIONAL</td>\n",
       "      <td>BANGOR</td>\n",
       "      <td>USA</td>\n",
       "      <td>44</td>\n",
       "      <td>48</td>\n",
       "      <td>26</td>\n",
       "      <td>N</td>\n",
       "      <td>68</td>\n",
       "      <td>49</td>\n",
       "      <td>41</td>\n",
       "      <td>W</td>\n",
       "      <td>59</td>\n",
       "      <td>44.807</td>\n",
       "      <td>-68.828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3417</th>\n",
       "      <td>KBHM</td>\n",
       "      <td>BHM</td>\n",
       "      <td>BIRMINGHAM INTERNATIONAL</td>\n",
       "      <td>BIRMINGHAM</td>\n",
       "      <td>USA</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>46</td>\n",
       "      <td>N</td>\n",
       "      <td>86</td>\n",
       "      <td>45</td>\n",
       "      <td>12</td>\n",
       "      <td>W</td>\n",
       "      <td>197</td>\n",
       "      <td>33.563</td>\n",
       "      <td>-86.753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3418</th>\n",
       "      <td>KBIF</td>\n",
       "      <td>BIF</td>\n",
       "      <td>BIGGS AAF</td>\n",
       "      <td>EL PASO</td>\n",
       "      <td>USA</td>\n",
       "      <td>31</td>\n",
       "      <td>50</td>\n",
       "      <td>58</td>\n",
       "      <td>N</td>\n",
       "      <td>106</td>\n",
       "      <td>22</td>\n",
       "      <td>48</td>\n",
       "      <td>W</td>\n",
       "      <td>1203</td>\n",
       "      <td>31.849</td>\n",
       "      <td>-106.380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3421</th>\n",
       "      <td>KBLI</td>\n",
       "      <td>BLI</td>\n",
       "      <td>BELLINGHAM INTERNATIONAL</td>\n",
       "      <td>BELLINGHAM</td>\n",
       "      <td>USA</td>\n",
       "      <td>48</td>\n",
       "      <td>47</td>\n",
       "      <td>33</td>\n",
       "      <td>N</td>\n",
       "      <td>122</td>\n",
       "      <td>32</td>\n",
       "      <td>15</td>\n",
       "      <td>W</td>\n",
       "      <td>52</td>\n",
       "      <td>48.792</td>\n",
       "      <td>-122.537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6624</th>\n",
       "      <td>PAUN</td>\n",
       "      <td>UNK</td>\n",
       "      <td>UNALAKLEET</td>\n",
       "      <td>UNALAKLEET</td>\n",
       "      <td>USA</td>\n",
       "      <td>63</td>\n",
       "      <td>53</td>\n",
       "      <td>18</td>\n",
       "      <td>N</td>\n",
       "      <td>160</td>\n",
       "      <td>47</td>\n",
       "      <td>56</td>\n",
       "      <td>W</td>\n",
       "      <td>7</td>\n",
       "      <td>63.888</td>\n",
       "      <td>-160.799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6625</th>\n",
       "      <td>PAVD</td>\n",
       "      <td>VDZ</td>\n",
       "      <td>VALDEZ PIONEER FIELD</td>\n",
       "      <td>VALDEZ</td>\n",
       "      <td>USA</td>\n",
       "      <td>61</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>N</td>\n",
       "      <td>146</td>\n",
       "      <td>14</td>\n",
       "      <td>54</td>\n",
       "      <td>W</td>\n",
       "      <td>37</td>\n",
       "      <td>61.134</td>\n",
       "      <td>-146.248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6627</th>\n",
       "      <td>PAWT</td>\n",
       "      <td>AIN</td>\n",
       "      <td>WAINWRIGHT AS</td>\n",
       "      <td>FORT WAINWRIGHT</td>\n",
       "      <td>USA</td>\n",
       "      <td>70</td>\n",
       "      <td>36</td>\n",
       "      <td>48</td>\n",
       "      <td>N</td>\n",
       "      <td>159</td>\n",
       "      <td>51</td>\n",
       "      <td>37</td>\n",
       "      <td>W</td>\n",
       "      <td>11</td>\n",
       "      <td>70.613</td>\n",
       "      <td>-159.860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6629</th>\n",
       "      <td>PAYA</td>\n",
       "      <td>YAK</td>\n",
       "      <td>YAKUTAT</td>\n",
       "      <td>YAKUTAT</td>\n",
       "      <td>USA</td>\n",
       "      <td>59</td>\n",
       "      <td>30</td>\n",
       "      <td>11</td>\n",
       "      <td>N</td>\n",
       "      <td>139</td>\n",
       "      <td>39</td>\n",
       "      <td>36</td>\n",
       "      <td>W</td>\n",
       "      <td>12</td>\n",
       "      <td>59.503</td>\n",
       "      <td>-139.660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6633</th>\n",
       "      <td>PFYU</td>\n",
       "      <td>FYU</td>\n",
       "      <td>FORT YUKON</td>\n",
       "      <td>FORT YUKON</td>\n",
       "      <td>USA</td>\n",
       "      <td>66</td>\n",
       "      <td>34</td>\n",
       "      <td>17</td>\n",
       "      <td>N</td>\n",
       "      <td>145</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>W</td>\n",
       "      <td>132</td>\n",
       "      <td>66.571</td>\n",
       "      <td>-145.250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6638</th>\n",
       "      <td>PGRO</td>\n",
       "      <td>ROP</td>\n",
       "      <td>ROTA INTERNATIONAL</td>\n",
       "      <td>ROTA</td>\n",
       "      <td>MARIANA ISLANDS</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>28</td>\n",
       "      <td>N</td>\n",
       "      <td>145</td>\n",
       "      <td>14</td>\n",
       "      <td>36</td>\n",
       "      <td>E</td>\n",
       "      <td>186</td>\n",
       "      <td>14.174</td>\n",
       "      <td>145.243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6639</th>\n",
       "      <td>PGSN</td>\n",
       "      <td>SPN</td>\n",
       "      <td>SAIPAN INTERNATIONAL</td>\n",
       "      <td>SAIPAN</td>\n",
       "      <td>MARIANA ISLANDS</td>\n",
       "      <td>15</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>N</td>\n",
       "      <td>145</td>\n",
       "      <td>43</td>\n",
       "      <td>45</td>\n",
       "      <td>E</td>\n",
       "      <td>66</td>\n",
       "      <td>15.119</td>\n",
       "      <td>145.729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6641</th>\n",
       "      <td>PGUA</td>\n",
       "      <td>UAM</td>\n",
       "      <td>ANDERSEN AFB</td>\n",
       "      <td>ANDERSEN</td>\n",
       "      <td>MARIANA ISLANDS</td>\n",
       "      <td>13</td>\n",
       "      <td>35</td>\n",
       "      <td>2</td>\n",
       "      <td>N</td>\n",
       "      <td>144</td>\n",
       "      <td>55</td>\n",
       "      <td>48</td>\n",
       "      <td>E</td>\n",
       "      <td>192</td>\n",
       "      <td>13.584</td>\n",
       "      <td>144.930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6642</th>\n",
       "      <td>PGUM</td>\n",
       "      <td>GUM</td>\n",
       "      <td>GUAM INTERNATIONAL</td>\n",
       "      <td>AGANA</td>\n",
       "      <td>MARIANA ISLANDS</td>\n",
       "      <td>13</td>\n",
       "      <td>29</td>\n",
       "      <td>2</td>\n",
       "      <td>N</td>\n",
       "      <td>144</td>\n",
       "      <td>47</td>\n",
       "      <td>49</td>\n",
       "      <td>E</td>\n",
       "      <td>91</td>\n",
       "      <td>13.484</td>\n",
       "      <td>144.797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6649</th>\n",
       "      <td>PHHN</td>\n",
       "      <td>HNM</td>\n",
       "      <td>HANA</td>\n",
       "      <td>HANA</td>\n",
       "      <td>USA</td>\n",
       "      <td>20</td>\n",
       "      <td>47</td>\n",
       "      <td>44</td>\n",
       "      <td>N</td>\n",
       "      <td>156</td>\n",
       "      <td>0</td>\n",
       "      <td>51</td>\n",
       "      <td>W</td>\n",
       "      <td>24</td>\n",
       "      <td>20.796</td>\n",
       "      <td>-156.014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6652</th>\n",
       "      <td>PHJH</td>\n",
       "      <td>JHM</td>\n",
       "      <td>KAPALUA</td>\n",
       "      <td>LAHANIA-KAPALUA</td>\n",
       "      <td>USA</td>\n",
       "      <td>20</td>\n",
       "      <td>57</td>\n",
       "      <td>46</td>\n",
       "      <td>N</td>\n",
       "      <td>156</td>\n",
       "      <td>40</td>\n",
       "      <td>27</td>\n",
       "      <td>W</td>\n",
       "      <td>79</td>\n",
       "      <td>20.963</td>\n",
       "      <td>-156.674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6655</th>\n",
       "      <td>PHKO</td>\n",
       "      <td>KOA</td>\n",
       "      <td>KONA INTERNATIONAL AT KEAHOLE</td>\n",
       "      <td>KONA</td>\n",
       "      <td>USA</td>\n",
       "      <td>19</td>\n",
       "      <td>44</td>\n",
       "      <td>19</td>\n",
       "      <td>N</td>\n",
       "      <td>156</td>\n",
       "      <td>2</td>\n",
       "      <td>44</td>\n",
       "      <td>W</td>\n",
       "      <td>15</td>\n",
       "      <td>19.739</td>\n",
       "      <td>-156.046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6658</th>\n",
       "      <td>PHLI</td>\n",
       "      <td>LIH</td>\n",
       "      <td>LIHUE</td>\n",
       "      <td>LIHUE</td>\n",
       "      <td>USA</td>\n",
       "      <td>21</td>\n",
       "      <td>58</td>\n",
       "      <td>34</td>\n",
       "      <td>N</td>\n",
       "      <td>159</td>\n",
       "      <td>20</td>\n",
       "      <td>19</td>\n",
       "      <td>W</td>\n",
       "      <td>47</td>\n",
       "      <td>21.976</td>\n",
       "      <td>-159.339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6659</th>\n",
       "      <td>PHMK</td>\n",
       "      <td>MKK</td>\n",
       "      <td>MOLOKAI</td>\n",
       "      <td>MOLOKAI</td>\n",
       "      <td>USA</td>\n",
       "      <td>21</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>N</td>\n",
       "      <td>157</td>\n",
       "      <td>5</td>\n",
       "      <td>46</td>\n",
       "      <td>W</td>\n",
       "      <td>139</td>\n",
       "      <td>21.153</td>\n",
       "      <td>-157.096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6661</th>\n",
       "      <td>PHMU</td>\n",
       "      <td>MUE</td>\n",
       "      <td>WAIMEA KOHALA</td>\n",
       "      <td>KAMUELA</td>\n",
       "      <td>USA</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>N</td>\n",
       "      <td>155</td>\n",
       "      <td>40</td>\n",
       "      <td>5</td>\n",
       "      <td>W</td>\n",
       "      <td>815</td>\n",
       "      <td>20.001</td>\n",
       "      <td>-155.668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6665</th>\n",
       "      <td>PHNG</td>\n",
       "      <td>NGF</td>\n",
       "      <td>KANEOHE BAY MCAF</td>\n",
       "      <td>KANEOHE BAY</td>\n",
       "      <td>USA</td>\n",
       "      <td>21</td>\n",
       "      <td>26</td>\n",
       "      <td>57</td>\n",
       "      <td>N</td>\n",
       "      <td>157</td>\n",
       "      <td>46</td>\n",
       "      <td>4</td>\n",
       "      <td>W</td>\n",
       "      <td>6</td>\n",
       "      <td>21.449</td>\n",
       "      <td>-157.768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6666</th>\n",
       "      <td>PHNL</td>\n",
       "      <td>HNL</td>\n",
       "      <td>HONOLULU INTERNATIONAL</td>\n",
       "      <td>HONOLULU</td>\n",
       "      <td>USA</td>\n",
       "      <td>21</td>\n",
       "      <td>18</td>\n",
       "      <td>57</td>\n",
       "      <td>N</td>\n",
       "      <td>157</td>\n",
       "      <td>55</td>\n",
       "      <td>36</td>\n",
       "      <td>W</td>\n",
       "      <td>4</td>\n",
       "      <td>21.316</td>\n",
       "      <td>-157.927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6667</th>\n",
       "      <td>PHNY</td>\n",
       "      <td>LNY</td>\n",
       "      <td>LANAI</td>\n",
       "      <td>LANAI</td>\n",
       "      <td>USA</td>\n",
       "      <td>20</td>\n",
       "      <td>47</td>\n",
       "      <td>8</td>\n",
       "      <td>N</td>\n",
       "      <td>156</td>\n",
       "      <td>57</td>\n",
       "      <td>5</td>\n",
       "      <td>W</td>\n",
       "      <td>399</td>\n",
       "      <td>20.786</td>\n",
       "      <td>-156.951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6668</th>\n",
       "      <td>PHOG</td>\n",
       "      <td>OGG</td>\n",
       "      <td>KAHULUI</td>\n",
       "      <td>KAHULUI</td>\n",
       "      <td>USA</td>\n",
       "      <td>20</td>\n",
       "      <td>53</td>\n",
       "      <td>55</td>\n",
       "      <td>N</td>\n",
       "      <td>156</td>\n",
       "      <td>25</td>\n",
       "      <td>50</td>\n",
       "      <td>W</td>\n",
       "      <td>17</td>\n",
       "      <td>20.899</td>\n",
       "      <td>-156.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6670</th>\n",
       "      <td>PHTO</td>\n",
       "      <td>ITO</td>\n",
       "      <td>HILO INTERNATIONAL</td>\n",
       "      <td>HILO</td>\n",
       "      <td>USA</td>\n",
       "      <td>19</td>\n",
       "      <td>43</td>\n",
       "      <td>13</td>\n",
       "      <td>N</td>\n",
       "      <td>155</td>\n",
       "      <td>2</td>\n",
       "      <td>55</td>\n",
       "      <td>W</td>\n",
       "      <td>12</td>\n",
       "      <td>19.720</td>\n",
       "      <td>-155.049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6686</th>\n",
       "      <td>PPIZ</td>\n",
       "      <td>PIZ</td>\n",
       "      <td>POINT LAY LRRS</td>\n",
       "      <td>POINT LAY</td>\n",
       "      <td>USA</td>\n",
       "      <td>69</td>\n",
       "      <td>43</td>\n",
       "      <td>58</td>\n",
       "      <td>N</td>\n",
       "      <td>163</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>W</td>\n",
       "      <td>8</td>\n",
       "      <td>69.733</td>\n",
       "      <td>-163.005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8020</th>\n",
       "      <td>TIST</td>\n",
       "      <td>STT</td>\n",
       "      <td>CYRIL E KING</td>\n",
       "      <td>ST. THOMAS</td>\n",
       "      <td>VIRGIN ISL.</td>\n",
       "      <td>18</td>\n",
       "      <td>20</td>\n",
       "      <td>14</td>\n",
       "      <td>N</td>\n",
       "      <td>64</td>\n",
       "      <td>58</td>\n",
       "      <td>24</td>\n",
       "      <td>W</td>\n",
       "      <td>8</td>\n",
       "      <td>18.337</td>\n",
       "      <td>-64.973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8021</th>\n",
       "      <td>TISX</td>\n",
       "      <td>STX</td>\n",
       "      <td>HENRY E ROHLSEN</td>\n",
       "      <td>ST. CRIOX ISLAND</td>\n",
       "      <td>VIRGIN ISL.</td>\n",
       "      <td>17</td>\n",
       "      <td>42</td>\n",
       "      <td>6</td>\n",
       "      <td>N</td>\n",
       "      <td>64</td>\n",
       "      <td>47</td>\n",
       "      <td>54</td>\n",
       "      <td>W</td>\n",
       "      <td>20</td>\n",
       "      <td>17.702</td>\n",
       "      <td>-64.798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8022</th>\n",
       "      <td>TJBQ</td>\n",
       "      <td>BQN</td>\n",
       "      <td>RAFAEL HERNANDEZ</td>\n",
       "      <td>AGUADILLA</td>\n",
       "      <td>PUERTO RICO</td>\n",
       "      <td>18</td>\n",
       "      <td>29</td>\n",
       "      <td>41</td>\n",
       "      <td>N</td>\n",
       "      <td>67</td>\n",
       "      <td>7</td>\n",
       "      <td>46</td>\n",
       "      <td>W</td>\n",
       "      <td>73</td>\n",
       "      <td>18.495</td>\n",
       "      <td>-67.129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8023</th>\n",
       "      <td>TJCG</td>\n",
       "      <td>VQS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>VIEQUES</td>\n",
       "      <td>PUERTO RICO</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>U</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>U</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8024</th>\n",
       "      <td>TJCP</td>\n",
       "      <td>CPX</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CULEBRA</td>\n",
       "      <td>PUERTO RICO</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>U</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>U</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8027</th>\n",
       "      <td>TJIG</td>\n",
       "      <td>SIG</td>\n",
       "      <td>FERNANDO LUIS RIBAS DOMINICCI</td>\n",
       "      <td>SAN JUAN</td>\n",
       "      <td>PUERTO RICO</td>\n",
       "      <td>18</td>\n",
       "      <td>27</td>\n",
       "      <td>24</td>\n",
       "      <td>N</td>\n",
       "      <td>66</td>\n",
       "      <td>5</td>\n",
       "      <td>53</td>\n",
       "      <td>W</td>\n",
       "      <td>4</td>\n",
       "      <td>18.457</td>\n",
       "      <td>-66.098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8028</th>\n",
       "      <td>TJMZ</td>\n",
       "      <td>MAZ</td>\n",
       "      <td>EUGENIO MARIA DE HOSTOS</td>\n",
       "      <td>MAYAGUEZ</td>\n",
       "      <td>PUERTO RICO</td>\n",
       "      <td>18</td>\n",
       "      <td>15</td>\n",
       "      <td>20</td>\n",
       "      <td>N</td>\n",
       "      <td>67</td>\n",
       "      <td>8</td>\n",
       "      <td>54</td>\n",
       "      <td>W</td>\n",
       "      <td>9</td>\n",
       "      <td>18.256</td>\n",
       "      <td>-67.148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8030</th>\n",
       "      <td>TJPS</td>\n",
       "      <td>PSE</td>\n",
       "      <td>MERCEDITA</td>\n",
       "      <td>PONCE</td>\n",
       "      <td>PUERTO RICO</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>N</td>\n",
       "      <td>66</td>\n",
       "      <td>33</td>\n",
       "      <td>46</td>\n",
       "      <td>W</td>\n",
       "      <td>8</td>\n",
       "      <td>18.008</td>\n",
       "      <td>-66.563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8031</th>\n",
       "      <td>TJSJ</td>\n",
       "      <td>SJU</td>\n",
       "      <td>LUIS MUNOZ MARIN INTERNATIONAL</td>\n",
       "      <td>SAN JUAN</td>\n",
       "      <td>PUERTO RICO</td>\n",
       "      <td>18</td>\n",
       "      <td>26</td>\n",
       "      <td>21</td>\n",
       "      <td>N</td>\n",
       "      <td>66</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>W</td>\n",
       "      <td>3</td>\n",
       "      <td>18.439</td>\n",
       "      <td>-66.002</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>371 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        0    1                                               2   \\\n",
       "1321  EGYC  CLF                                      COLTISHALL   \n",
       "3380  KABI  ABI                                    ABILENE RGNL   \n",
       "3381  KABQ  ABQ                                             NaN   \n",
       "3382  KACK  ACK                                   NANTUCKET MEM   \n",
       "3383  KACT  ACT                                       WACO RGNL   \n",
       "3384  KACY  ACY                     ATLANTIC CITY INTERNATIONAL   \n",
       "3386  KADW  ADW                                     ANDREWS AFB   \n",
       "3387  KAEX  AEX                        ALEXANDRIA INTERNATIONAL   \n",
       "3389  KAGS  AGS                        AUGUSTA RGNL AT BUSH FLD   \n",
       "3391  KALB  ALB                            ALBANY INTERNATIONAL   \n",
       "3394  KAMA  AMA                          AMARILLO INTERNATIONAL   \n",
       "3395  KANB  ANB                           ANNISTON METROPOLITAN   \n",
       "3397  KAOO  AOO                                ALTOONA BLAIR CO   \n",
       "3399  KARA  ARA                               ACADIANA REGIONAL   \n",
       "3400  KART  ART                         WATERTOWN INTERNATIONAL   \n",
       "3401  KATL  ATL  THE WILLIAM B HARTSFIELD ATLANTA INTERNATIONAL   \n",
       "3402  KAUG  AUG                                   AUGUSTA STATE   \n",
       "3403  KAUS  AUS                  AUSTIN BERGSTROM INTERNATIONAL   \n",
       "3406  KBAD  BAD                                   BARKSDALE AFB   \n",
       "3407  KBCT  BCT                                      BOCA RATON   \n",
       "3409  KBDL  BDL                           BRADLEY INTERNATIONAL   \n",
       "3410  KBDR  BDR                             IGOR I SIKORSKY MEM   \n",
       "3411  KBED  BED                          LAURENCE G HANSCOM FLD   \n",
       "3412  KBFI  BFI                BOEING FLD KING CO INTERNATIONAL   \n",
       "3413  KBFL  BFL                                     MEADOWS FLD   \n",
       "3414  KBFM  BFM                                 MOBILE DOWNTOWN   \n",
       "3415  KBGR  BGR                            BANGOR INTERNATIONAL   \n",
       "3417  KBHM  BHM                        BIRMINGHAM INTERNATIONAL   \n",
       "3418  KBIF  BIF                                       BIGGS AAF   \n",
       "3421  KBLI  BLI                        BELLINGHAM INTERNATIONAL   \n",
       "...    ...  ...                                             ...   \n",
       "6624  PAUN  UNK                                      UNALAKLEET   \n",
       "6625  PAVD  VDZ                            VALDEZ PIONEER FIELD   \n",
       "6627  PAWT  AIN                                   WAINWRIGHT AS   \n",
       "6629  PAYA  YAK                                         YAKUTAT   \n",
       "6633  PFYU  FYU                                      FORT YUKON   \n",
       "6638  PGRO  ROP                              ROTA INTERNATIONAL   \n",
       "6639  PGSN  SPN                            SAIPAN INTERNATIONAL   \n",
       "6641  PGUA  UAM                                    ANDERSEN AFB   \n",
       "6642  PGUM  GUM                              GUAM INTERNATIONAL   \n",
       "6649  PHHN  HNM                                            HANA   \n",
       "6652  PHJH  JHM                                         KAPALUA   \n",
       "6655  PHKO  KOA                   KONA INTERNATIONAL AT KEAHOLE   \n",
       "6658  PHLI  LIH                                           LIHUE   \n",
       "6659  PHMK  MKK                                         MOLOKAI   \n",
       "6661  PHMU  MUE                                   WAIMEA KOHALA   \n",
       "6665  PHNG  NGF                                KANEOHE BAY MCAF   \n",
       "6666  PHNL  HNL                          HONOLULU INTERNATIONAL   \n",
       "6667  PHNY  LNY                                           LANAI   \n",
       "6668  PHOG  OGG                                         KAHULUI   \n",
       "6670  PHTO  ITO                              HILO INTERNATIONAL   \n",
       "6686  PPIZ  PIZ                                  POINT LAY LRRS   \n",
       "8020  TIST  STT                                    CYRIL E KING   \n",
       "8021  TISX  STX                                 HENRY E ROHLSEN   \n",
       "8022  TJBQ  BQN                                RAFAEL HERNANDEZ   \n",
       "8023  TJCG  VQS                                             NaN   \n",
       "8024  TJCP  CPX                                             NaN   \n",
       "8027  TJIG  SIG                   FERNANDO LUIS RIBAS DOMINICCI   \n",
       "8028  TJMZ  MAZ                         EUGENIO MARIA DE HOSTOS   \n",
       "8030  TJPS  PSE                                       MERCEDITA   \n",
       "8031  TJSJ  SJU                  LUIS MUNOZ MARIN INTERNATIONAL   \n",
       "\n",
       "                    3                4   5   6   7  8    9   10  11 12    13  \\\n",
       "1321        COLTISHALL          ENGLAND  52  45  17  N    1  21  26  E    21   \n",
       "3380           ABILENE              USA  32  24  40  N   99  40  54  W   546   \n",
       "3381       ALBUQUERQUE              USA   0   0   0  U    0   0   0  U     0   \n",
       "3382         NANTUCKET              USA  41  15  10  N   70   3  36  W    15   \n",
       "3383              WACO              USA  31  36  40  N   97  13  49  W   158   \n",
       "3384     ATLANTIC CITY              USA  39  27  27  N   74  34  37  W    23   \n",
       "3386      CAMP SPRINGS              USA  38  48  38  N   76  52   1  W    86   \n",
       "3387        ALEXANDRIA              USA  31  19  38  N   92  32  54  W    28   \n",
       "3389        BUSH FIELD              USA  33  22  11  N   81  57  52  W    44   \n",
       "3391            ALBANY              USA  42  44  53  N   73  48  10  W    87   \n",
       "3394          AMARILLO              USA  35  13   9  N  101  42  21  W  1100   \n",
       "3395          ANNISTON              USA  33  35  17  N   85  51  29  W   187   \n",
       "3397           ALTOONA              USA  40  17  47  N   78  19  12  W   459   \n",
       "3399         LOUISIANA              USA  30   2  15  N   91  53   2  W     8   \n",
       "3400         WATERTOWN              USA  43  59  30  N   76   1  18  W   100   \n",
       "3401           ATLANTA              USA  33  38  25  N   84  25  37  W   313   \n",
       "3402           AUGUSTA              USA  44  19  14  N   69  47  50  W   108   \n",
       "3403            AUSTIN              USA  30  11  40  N   97  40  11  W   166   \n",
       "3406        SHREVEPORT              USA  32  30   6  N   93  39  45  W    51   \n",
       "3407        BOCA RATON              USA  26  22  42  N   80   6  27  W     4   \n",
       "3409     WINDSOR LOCKS              USA  41  56  20  N   72  40  59  W    53   \n",
       "3410         STRATFORD              USA  41   9  48  N   73   7  34  W     3   \n",
       "3411           BEDFORD              USA  42  28  11  N   71  17  20  W    41   \n",
       "3412           SEATTLE              USA  47  31  47  N  122  18   7  W     6   \n",
       "3413       BAKERSFIELD              USA  35  26   0  N  119   3  24  W   155   \n",
       "3414            MOBILE              USA  30  37  35  N   88   4   4  W     8   \n",
       "3415            BANGOR              USA  44  48  26  N   68  49  41  W    59   \n",
       "3417        BIRMINGHAM              USA  33  33  46  N   86  45  12  W   197   \n",
       "3418           EL PASO              USA  31  50  58  N  106  22  48  W  1203   \n",
       "3421        BELLINGHAM              USA  48  47  33  N  122  32  15  W    52   \n",
       "...                ...              ...  ..  ..  .. ..  ...  ..  .. ..   ...   \n",
       "6624        UNALAKLEET              USA  63  53  18  N  160  47  56  W     7   \n",
       "6625            VALDEZ              USA  61   8   2  N  146  14  54  W    37   \n",
       "6627   FORT WAINWRIGHT              USA  70  36  48  N  159  51  37  W    11   \n",
       "6629           YAKUTAT              USA  59  30  11  N  139  39  36  W    12   \n",
       "6633        FORT YUKON              USA  66  34  17  N  145  15   1  W   132   \n",
       "6638              ROTA  MARIANA ISLANDS  14  10  28  N  145  14  36  E   186   \n",
       "6639            SAIPAN  MARIANA ISLANDS  15   7  10  N  145  43  45  E    66   \n",
       "6641          ANDERSEN  MARIANA ISLANDS  13  35   2  N  144  55  48  E   192   \n",
       "6642             AGANA  MARIANA ISLANDS  13  29   2  N  144  47  49  E    91   \n",
       "6649              HANA              USA  20  47  44  N  156   0  51  W    24   \n",
       "6652   LAHANIA-KAPALUA              USA  20  57  46  N  156  40  27  W    79   \n",
       "6655              KONA              USA  19  44  19  N  156   2  44  W    15   \n",
       "6658             LIHUE              USA  21  58  34  N  159  20  19  W    47   \n",
       "6659           MOLOKAI              USA  21   9  10  N  157   5  46  W   139   \n",
       "6661           KAMUELA              USA  20   0   4  N  155  40   5  W   815   \n",
       "6665       KANEOHE BAY              USA  21  26  57  N  157  46   4  W     6   \n",
       "6666          HONOLULU              USA  21  18  57  N  157  55  36  W     4   \n",
       "6667             LANAI              USA  20  47   8  N  156  57   5  W   399   \n",
       "6668           KAHULUI              USA  20  53  55  N  156  25  50  W    17   \n",
       "6670              HILO              USA  19  43  13  N  155   2  55  W    12   \n",
       "6686         POINT LAY              USA  69  43  58  N  163   0  19  W     8   \n",
       "8020        ST. THOMAS      VIRGIN ISL.  18  20  14  N   64  58  24  W     8   \n",
       "8021  ST. CRIOX ISLAND      VIRGIN ISL.  17  42   6  N   64  47  54  W    20   \n",
       "8022         AGUADILLA      PUERTO RICO  18  29  41  N   67   7  46  W    73   \n",
       "8023           VIEQUES      PUERTO RICO   0   0   0  U    0   0   0  U     0   \n",
       "8024           CULEBRA      PUERTO RICO   0   0   0  U    0   0   0  U     0   \n",
       "8027          SAN JUAN      PUERTO RICO  18  27  24  N   66   5  53  W     4   \n",
       "8028          MAYAGUEZ      PUERTO RICO  18  15  20  N   67   8  54  W     9   \n",
       "8030             PONCE      PUERTO RICO  18   0  29  N   66  33  46  W     8   \n",
       "8031          SAN JUAN      PUERTO RICO  18  26  21  N   66   0   6  W     3   \n",
       "\n",
       "          14       15  \n",
       "1321  52.755    1.357  \n",
       "3380  32.411  -99.682  \n",
       "3381   0.000    0.000  \n",
       "3382  41.253  -70.060  \n",
       "3383  31.611  -97.230  \n",
       "3384  39.458  -74.577  \n",
       "3386  38.811  -76.867  \n",
       "3387  31.327  -92.548  \n",
       "3389  33.370  -81.964  \n",
       "3391  42.748  -73.803  \n",
       "3394  35.219 -101.706  \n",
       "3395  33.588  -85.858  \n",
       "3397  40.296  -78.320  \n",
       "3399  30.038  -91.884  \n",
       "3400  43.992  -76.022  \n",
       "3401  33.640  -84.427  \n",
       "3402  44.321  -69.797  \n",
       "3403  30.194  -97.670  \n",
       "3406  32.502  -93.663  \n",
       "3407  26.378  -80.107  \n",
       "3409  41.939  -72.683  \n",
       "3410  41.163  -73.126  \n",
       "3411  42.470  -71.289  \n",
       "3412  47.530 -122.302  \n",
       "3413  35.433 -119.057  \n",
       "3414  30.626  -88.068  \n",
       "3415  44.807  -68.828  \n",
       "3417  33.563  -86.753  \n",
       "3418  31.849 -106.380  \n",
       "3421  48.792 -122.537  \n",
       "...      ...      ...  \n",
       "6624  63.888 -160.799  \n",
       "6625  61.134 -146.248  \n",
       "6627  70.613 -159.860  \n",
       "6629  59.503 -139.660  \n",
       "6633  66.571 -145.250  \n",
       "6638  14.174  145.243  \n",
       "6639  15.119  145.729  \n",
       "6641  13.584  144.930  \n",
       "6642  13.484  144.797  \n",
       "6649  20.796 -156.014  \n",
       "6652  20.963 -156.674  \n",
       "6655  19.739 -156.046  \n",
       "6658  21.976 -159.339  \n",
       "6659  21.153 -157.096  \n",
       "6661  20.001 -155.668  \n",
       "6665  21.449 -157.768  \n",
       "6666  21.316 -157.927  \n",
       "6667  20.786 -156.951  \n",
       "6668  20.899 -156.431  \n",
       "6670  19.720 -155.049  \n",
       "6686  69.733 -163.005  \n",
       "8020  18.337  -64.973  \n",
       "8021  17.702  -64.798  \n",
       "8022  18.495  -67.129  \n",
       "8023   0.000    0.000  \n",
       "8024   0.000    0.000  \n",
       "8027  18.457  -66.098  \n",
       "8028  18.256  -67.148  \n",
       "8030  18.008  -66.563  \n",
       "8031  18.439  -66.002  \n",
       "\n",
       "[371 rows x 16 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lat_long[lat_long[1].isin(list(pass_2015.nodes()))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "pos_dict = {}\n",
    "for airport in lat_long[lat_long[1].isin(list(pass_2015.nodes()))].iterrows():\n",
    "    pos_dict[airport[1][1]] = (airport[1][15], airport[1][14]) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'ABI': (-99.682, 32.411),\n",
       " 'ABQ': (-106.609, 35.04),\n",
       " 'ABY': (0.0, 0.0),\n",
       " 'ACK': (-70.06, 41.253),\n",
       " 'ACT': (-97.23, 31.611),\n",
       " 'ACY': (-74.577, 39.458),\n",
       " 'ADK': (-176.646, 51.878),\n",
       " 'ADQ': (-152.494, 57.75),\n",
       " 'ADW': (-76.867, 38.811),\n",
       " 'AEX': (-92.54799999999999, 31.326999999999998),\n",
       " 'AGS': (-81.964, 33.37),\n",
       " 'AIN': (-159.86, 70.613),\n",
       " 'AKN': (-156.649, 58.677),\n",
       " 'ALB': (-73.803, 42.748000000000005),\n",
       " 'AMA': (-101.706, 35.219),\n",
       " 'ANB': (-85.85799999999999, 33.588),\n",
       " 'ANC': (-149.996, 61.174),\n",
       " 'AOO': (-78.32, 40.296),\n",
       " 'ARA': (-91.884, 30.038),\n",
       " 'ART': (-76.02199999999999, 43.992),\n",
       " 'ATL': (-84.427, 33.64),\n",
       " 'AUG': (-69.797, 44.321000000000005),\n",
       " 'AUS': (-97.67, 30.194000000000003),\n",
       " 'BAD': (-93.663, 32.501999999999995),\n",
       " 'BCT': (-80.107, 26.378),\n",
       " 'BDL': (-72.683, 41.93899999999999),\n",
       " 'BDR': (-73.126, 41.163000000000004),\n",
       " 'BED': (-71.289, 42.47),\n",
       " 'BET': (-161.838, 60.78),\n",
       " 'BFI': (-122.302, 47.53),\n",
       " 'BFL': (-119.057, 35.433),\n",
       " 'BFM': (-88.068, 30.625999999999998),\n",
       " 'BGR': (-68.828, 44.806999999999995),\n",
       " 'BHM': (-86.75299999999999, 33.563),\n",
       " 'BIF': (-106.38, 31.849),\n",
       " 'BLI': (-122.537, 48.792),\n",
       " 'BLV': (-89.835, 38.545),\n",
       " 'BNA': (-86.678, 36.124),\n",
       " 'BOI': (-116.223, 43.56399999999999),\n",
       " 'BOS': (-71.005, 42.364),\n",
       " 'BPT': (-94.021, 29.951),\n",
       " 'BQK': (0.0, 0.0),\n",
       " 'BQN': (-67.12899999999999, 18.495),\n",
       " 'BRO': (-97.426, 25.906999999999996),\n",
       " 'BRW': (-156.766, 71.285),\n",
       " 'BTI': (-143.577, 70.134),\n",
       " 'BTR': (-91.149, 30.533),\n",
       " 'BTT': (-151.528, 66.915),\n",
       " 'BTV': (-73.153, 44.472),\n",
       " 'BUF': (-78.732, 42.94),\n",
       " 'BUR': (-118.359, 34.201),\n",
       " 'BWI': (-76.668, 39.175),\n",
       " 'CAE': (-81.119, 33.939),\n",
       " 'CDB': (-162.724, 55.206),\n",
       " 'CDC': (-113.09899999999999, 37.701),\n",
       " 'CDV': (-145.477, 60.492),\n",
       " 'CEF': (-72.53399999999999, 42.198),\n",
       " 'CEW': (-86.522, 30.779),\n",
       " 'CHA': (-85.204, 35.035),\n",
       " 'CHS': (-80.04, 32.899),\n",
       " 'CIC': (-121.85799999999999, 39.795),\n",
       " 'CLE': (-81.85, 41.412),\n",
       " 'CLF': (1.357, 52.755),\n",
       " 'CLL': (-96.36399999999999, 30.588),\n",
       " 'CLT': (-80.943, 35.214),\n",
       " 'CMH': (-82.89200000000001, 39.998000000000005),\n",
       " 'CNM': (-104.26299999999999, 32.336999999999996),\n",
       " 'COS': (-104.7, 38.806),\n",
       " 'COU': (-92.219, 38.818000000000005),\n",
       " 'CPR': (-106.464, 42.908),\n",
       " 'CPX': (0.0, 0.0),\n",
       " 'CRP': (-97.501, 27.77),\n",
       " 'CVG': (-84.662, 39.046),\n",
       " 'CVS': (-103.322, 34.383),\n",
       " 'CYS': (-104.81200000000001, 41.156000000000006),\n",
       " 'DAL': (-96.852, 32.847),\n",
       " 'DAY': (-84.219, 39.902),\n",
       " 'DCA': (-77.03699999999999, 38.852),\n",
       " 'DEN': (-104.667, 39.858000000000004),\n",
       " 'DET': (-83.01, 42.409),\n",
       " 'DFW': (-97.037, 32.896),\n",
       " 'DHN': (-85.449, 31.320999999999998),\n",
       " 'DLG': (-158.503, 59.045),\n",
       " 'DLH': (-92.194, 46.842),\n",
       " 'DMA': (-110.883, 32.166),\n",
       " 'DOV': (-75.46600000000001, 39.13),\n",
       " 'DPA': (-88.249, 41.908),\n",
       " 'DRO': (-107.75399999999999, 37.150999999999996),\n",
       " 'DRT': (-100.926, 29.373),\n",
       " 'DSM': (-93.663, 41.534),\n",
       " 'DTW': (-83.353, 42.211999999999996),\n",
       " 'DUT': (-166.543, 53.9),\n",
       " 'EDF': (-149.806, 61.251000000000005),\n",
       " 'EDW': (-117.884, 34.905),\n",
       " 'EFD': (-95.15899999999999, 29.607),\n",
       " 'EHM': (-162.061, 58.647),\n",
       " 'EIL': (-147.101, 64.666),\n",
       " 'ELD': (-92.81299999999999, 33.221),\n",
       " 'ELP': (-106.37799999999999, 31.807),\n",
       " 'ENA': (-151.245, 60.573),\n",
       " 'ENV': (-114.031, 40.719),\n",
       " 'EWN': (-77.043, 35.073),\n",
       " 'EWR': (-74.169, 40.692),\n",
       " 'EYW': (-81.759, 24.555999999999997),\n",
       " 'FAI': (-147.856, 64.815),\n",
       " 'FAT': (-119.71799999999999, 36.775999999999996),\n",
       " 'FBK': (-147.614, 64.837),\n",
       " 'FFO': (-84.04799999999999, 39.826),\n",
       " 'FLL': (-80.153, 26.072),\n",
       " 'FLO': (-79.72399999999999, 34.185),\n",
       " 'FMH': (-70.521, 41.658),\n",
       " 'FMN': (-108.23, 36.741),\n",
       " 'FMY': (-81.863, 26.586),\n",
       " 'FOD': (-94.193, 42.551),\n",
       " 'FOE': (-95.664, 38.951),\n",
       " 'FOK': (-72.632, 40.844),\n",
       " 'FSI': (-98.402, 34.65),\n",
       " 'FSM': (-94.367, 35.336),\n",
       " 'FTW': (-97.36200000000001, 32.82),\n",
       " 'FXE': (-80.171, 26.197),\n",
       " 'FYU': (-145.25, 66.571),\n",
       " 'FYV': (-94.17, 36.005),\n",
       " 'GAL': (-156.937, 64.736),\n",
       " 'GCK': (-100.72399999999999, 37.927),\n",
       " 'GEG': (-117.53399999999999, 47.62),\n",
       " 'GFK': (-97.176, 47.949),\n",
       " 'GGG': (-94.711, 32.385),\n",
       " 'GKN': (-145.45600000000002, 62.155),\n",
       " 'GNV': (-82.272, 29.69),\n",
       " 'GRB': (-88.12899999999999, 44.485),\n",
       " 'GRF': (-122.581, 47.07899999999999),\n",
       " 'GRK': (-97.829, 31.066999999999997),\n",
       " 'GRR': (-85.523, 42.881),\n",
       " 'GSB': (-77.961, 35.339),\n",
       " 'GTF': (-111.37100000000001, 47.482),\n",
       " 'GUM': (144.797, 13.484000000000002),\n",
       " 'GUS': (-86.152, 40.648),\n",
       " 'GVT': (-96.065, 33.068000000000005),\n",
       " 'HFD': (-72.65, 41.736000000000004),\n",
       " 'HIB': (-92.839, 47.386),\n",
       " 'HKY': (-81.389, 35.741),\n",
       " 'HLN': (-111.98299999999999, 46.607),\n",
       " 'HMN': (-106.10600000000001, 32.852),\n",
       " 'HNL': (-157.92700000000002, 21.316),\n",
       " 'HNM': (-156.014, 20.796),\n",
       " 'HOB': (-103.21700000000001, 32.688),\n",
       " 'HOM': (-151.476, 59.646),\n",
       " 'HON': (-98.228, 44.385),\n",
       " 'HOP': (-87.49600000000001, 36.668),\n",
       " 'HOU': (-95.279, 29.645),\n",
       " 'HPN': (-73.707, 41.067),\n",
       " 'HRL': (-97.654, 26.228),\n",
       " 'HRO': (-93.155, 36.260999999999996),\n",
       " 'HUF': (-87.307, 39.451),\n",
       " 'HVR': (-109.762, 48.543),\n",
       " 'IAB': (-97.26700000000001, 37.623000000000005),\n",
       " 'IAD': (-77.456, 38.944),\n",
       " 'IAG': (-78.946, 43.107),\n",
       " 'IAH': (-95.34, 29.98),\n",
       " 'ICT': (-97.43299999999999, 37.65),\n",
       " 'ILG': (-75.60600000000001, 39.679),\n",
       " 'ILI': (-154.911, 59.754),\n",
       " 'ILM': (-77.903, 34.271),\n",
       " 'IND': (-86.294, 39.717),\n",
       " 'INL': (-93.40299999999999, 48.566),\n",
       " 'INT': (-80.222, 36.134),\n",
       " 'IPL': (-115.579, 32.834),\n",
       " 'IPT': (-76.921, 41.242),\n",
       " 'ISN': (-103.64200000000001, 48.178000000000004),\n",
       " 'ISP': (-73.1, 40.795),\n",
       " 'ITO': (-155.049, 19.72),\n",
       " 'JAN': (-90.07600000000001, 32.311),\n",
       " 'JAX': (-81.688, 30.494),\n",
       " 'JBR': (-90.646, 35.832),\n",
       " 'JFK': (-73.779, 40.64),\n",
       " 'JHM': (-156.674, 20.963),\n",
       " 'JNU': (-134.576, 58.355),\n",
       " 'KOA': (-156.046, 19.739),\n",
       " 'KTN': (-131.714, 55.356),\n",
       " 'LAN': (-84.587, 42.778999999999996),\n",
       " 'LAS': (-115.152, 36.08),\n",
       " 'LAX': (-118.40799999999999, 33.942),\n",
       " 'LBB': (-101.823, 33.664),\n",
       " 'LCH': (-93.223, 30.125999999999998),\n",
       " 'LCK': (-82.928, 39.814),\n",
       " 'LFI': (-76.36, 37.083),\n",
       " 'LFT': (-91.98700000000001, 30.205),\n",
       " 'LGA': (-73.872, 40.777),\n",
       " 'LGB': (-118.15100000000001, 33.818000000000005),\n",
       " 'LIH': (-159.339, 21.976),\n",
       " 'LIT': (-92.22399999999999, 34.729),\n",
       " 'LNK': (-96.759, 40.851),\n",
       " 'LNY': (-156.951, 20.785999999999998),\n",
       " 'LRD': (-99.461, 27.544),\n",
       " 'LSF': (-84.991, 32.336999999999996),\n",
       " 'LSV': (-115.03399999999999, 36.236),\n",
       " 'LUK': (-84.419, 39.103),\n",
       " 'LUR': (-166.11, 68.875),\n",
       " 'MAF': (-102.20200000000001, 31.941999999999997),\n",
       " 'MAZ': (-67.148, 18.256),\n",
       " 'MCC': (-121.40100000000001, 38.667),\n",
       " 'MCF': (-82.521, 27.849),\n",
       " 'MCG': (-155.606, 62.953),\n",
       " 'MCI': (-94.714, 39.297),\n",
       " 'MCN': (-83.649, 32.693000000000005),\n",
       " 'MCO': (-81.316, 28.429000000000002),\n",
       " 'MDT': (-76.763, 40.193000000000005),\n",
       " 'MDW': (-87.75200000000001, 41.786),\n",
       " 'MEM': (-89.977, 35.042),\n",
       " 'MER': (-120.568, 37.38),\n",
       " 'MFE': (-98.23899999999999, 26.176),\n",
       " 'MHR': (-121.29700000000001, 38.554),\n",
       " 'MIA': (-80.291, 25.793000000000003),\n",
       " 'MIB': (-101.35700000000001, 48.416000000000004),\n",
       " 'MKE': (-87.896, 42.946999999999996),\n",
       " 'MKK': (-157.096, 21.153000000000002),\n",
       " 'MKL': (-88.916, 35.6),\n",
       " 'MLB': (-80.645, 28.103),\n",
       " 'MLU': (-92.037, 32.510999999999996),\n",
       " 'MOB': (-88.243, 30.691),\n",
       " 'MOD': (-120.954, 37.626),\n",
       " 'MOT': (-101.28, 48.25899999999999),\n",
       " 'MQT': (-87.56200000000001, 46.534),\n",
       " 'MRI': (-149.846, 61.214),\n",
       " 'MSN': (-89.337, 43.14),\n",
       " 'MSP': (-93.21700000000001, 44.88),\n",
       " 'MSS': (-74.845, 44.93600000000001),\n",
       " 'MSY': (-90.258, 29.993000000000002),\n",
       " 'MUE': (-155.668, 20.000999999999998),\n",
       " 'MWH': (-119.32, 47.208),\n",
       " 'MXF': (-86.36200000000001, 32.379),\n",
       " 'MYR': (-78.928, 33.68),\n",
       " 'NBG': (-90.035, 29.825),\n",
       " 'NGF': (-157.768, 21.449),\n",
       " 'NGU': (-76.289, 36.938),\n",
       " 'NIP': (-81.681, 30.236),\n",
       " 'NJK': (-115.67200000000001, 32.829),\n",
       " 'NKX': (-117.14299999999999, 32.868),\n",
       " 'NPA': (-87.319, 30.353),\n",
       " 'NQA': (-89.87, 35.357),\n",
       " 'NQX': (-81.689, 24.576),\n",
       " 'NTD': (-119.12100000000001, 34.12),\n",
       " 'NTU': (-76.033, 36.821),\n",
       " 'NUQ': (-122.04799999999999, 37.415),\n",
       " 'NUW': (-122.656, 48.352),\n",
       " 'NZC': (-81.876, 30.219),\n",
       " 'NZY': (-117.215, 32.699),\n",
       " 'OAK': (-122.221, 37.721),\n",
       " 'OFF': (-95.913, 41.118),\n",
       " 'OGG': (-156.431, 20.899),\n",
       " 'OGS': (-75.46600000000001, 44.681999999999995),\n",
       " 'OKC': (-97.601, 35.393),\n",
       " 'OMA': (-95.89399999999999, 41.302),\n",
       " 'OME': (-165.445, 64.512),\n",
       " 'ONT': (-117.601, 34.056),\n",
       " 'OPF': (-80.278, 25.906999999999996),\n",
       " 'ORD': (-87.904, 41.979),\n",
       " 'ORF': (-76.20100000000001, 36.894),\n",
       " 'ORL': (-81.333, 28.545),\n",
       " 'ORT': (-141.929, 62.961000000000006),\n",
       " 'OTZ': (-162.59799999999998, 66.884),\n",
       " 'PAE': (-122.281, 47.906000000000006),\n",
       " 'PAM': (-85.57600000000001, 30.07),\n",
       " 'PAQ': (-149.089, 61.595),\n",
       " 'PBG': (-73.468, 44.651),\n",
       " 'PBI': (-80.096, 26.683000000000003),\n",
       " 'PCA': (-98.78200000000001, 20.077),\n",
       " 'PDX': (-122.59700000000001, 45.589),\n",
       " 'PHF': (-76.493, 37.132),\n",
       " 'PHL': (-75.241, 39.872),\n",
       " 'PHN': (-82.529, 42.911),\n",
       " 'PHX': (-112.008, 33.434),\n",
       " 'PIE': (-82.68700000000001, 27.910999999999998),\n",
       " 'PIT': (-80.233, 40.491),\n",
       " 'PIZ': (-163.005, 69.733),\n",
       " 'PML': (-161.819, 59.011),\n",
       " 'PNE': (-75.01100000000001, 40.082),\n",
       " 'PNS': (-87.18700000000001, 30.473000000000003),\n",
       " 'POB': (-79.014, 35.171),\n",
       " 'PPG': (-170.71, -14.331),\n",
       " 'PQI': (-68.045, 46.68899999999999),\n",
       " 'PRC': (-112.419, 34.654),\n",
       " 'PSE': (-66.563, 18.008),\n",
       " 'PSP': (-116.507, 33.829),\n",
       " 'PUB': (-104.49600000000001, 38.289),\n",
       " 'PVD': (-71.428, 41.724),\n",
       " 'PWM': (-70.309, 43.646),\n",
       " 'RCA': (-103.103, 44.145),\n",
       " 'RDU': (-78.78699999999999, 35.876999999999995),\n",
       " 'RIC': (-77.319, 37.505),\n",
       " 'RIV': (-117.259, 33.881),\n",
       " 'RME': (-75.407, 43.233999999999995),\n",
       " 'RNO': (-119.76799999999999, 39.498000000000005),\n",
       " 'ROC': (-77.672, 43.119),\n",
       " 'ROP': (145.243, 14.174000000000001),\n",
       " 'ROW': (-104.531, 33.301),\n",
       " 'RSW': (-81.755, 26.535999999999998),\n",
       " 'SAC': (-121.493, 38.513000000000005),\n",
       " 'SAF': (-106.088, 35.617),\n",
       " 'SAN': (-117.189, 32.733000000000004),\n",
       " 'SAT': (-98.47, 29.534000000000002),\n",
       " 'SAV': (-81.202, 32.126999999999995),\n",
       " 'SBY': (-75.51, 38.34),\n",
       " 'SCC': (-148.465, 70.195),\n",
       " 'SCK': (-121.23899999999999, 37.894),\n",
       " 'SEA': (-122.309, 47.449),\n",
       " 'SFB': (0.0, 0.0),\n",
       " 'SFO': (-122.375, 37.619),\n",
       " 'SFZ': (-71.491, 41.92100000000001),\n",
       " 'SGY': (-135.316, 59.46),\n",
       " 'SHV': (-93.82600000000001, 32.446),\n",
       " 'SIG': (-66.098, 18.457),\n",
       " 'SIT': (-135.361, 57.047),\n",
       " 'SJC': (-121.929, 37.361999999999995),\n",
       " 'SJT': (-100.49600000000001, 31.358),\n",
       " 'SJU': (-66.002, 18.439),\n",
       " 'SKF': (-98.581, 29.384),\n",
       " 'SLC': (-111.978, 40.788000000000004),\n",
       " 'SMF': (-121.59100000000001, 38.695),\n",
       " 'SNA': (-117.868, 33.676),\n",
       " 'SNP': (-170.22, 57.167),\n",
       " 'SPB': (-122.86200000000001, 45.773),\n",
       " 'SPN': (145.72899999999998, 15.119000000000002),\n",
       " 'SPS': (-98.492, 33.989000000000004),\n",
       " 'SSC': (-80.473, 33.973),\n",
       " 'STL': (-90.36, 38.748000000000005),\n",
       " 'STT': (-64.973, 18.337),\n",
       " 'STX': (-64.798, 17.702),\n",
       " 'SUU': (-121.927, 38.263000000000005),\n",
       " 'SUX': (-96.384, 42.402),\n",
       " 'SVN': (-81.146, 32.01),\n",
       " 'SVW': (-155.57399999999998, 61.097),\n",
       " 'SWF': (-74.105, 41.504),\n",
       " 'SYA': (174.114, 52.711999999999996),\n",
       " 'SYR': (-76.10600000000001, 43.111000000000004),\n",
       " 'SZL': (-93.54799999999999, 38.73),\n",
       " 'TAL': (-152.109, 65.17399999999999),\n",
       " 'TBN': (-92.141, 37.741),\n",
       " 'TEB': (-74.061, 40.85),\n",
       " 'TIK': (-97.38600000000001, 35.415),\n",
       " 'TKA': (-150.094, 62.32),\n",
       " 'TKF': (0.0, 0.0),\n",
       " 'TLH': (-84.35, 30.396),\n",
       " 'TLJ': (-155.976, 62.894),\n",
       " 'TMB': (-80.433, 25.648000000000003),\n",
       " 'TNC': (-167.922, 65.563),\n",
       " 'TNT': (-80.89699999999999, 25.862),\n",
       " 'TPA': (-82.53299999999999, 27.975),\n",
       " 'TTN': (-74.813, 40.277),\n",
       " 'TUL': (-95.88799999999999, 36.198),\n",
       " 'TUS': (-110.941, 32.116),\n",
       " 'TXK': (-93.991, 33.454),\n",
       " 'TYR': (-95.402, 32.354),\n",
       " 'TYS': (-83.993, 35.812),\n",
       " 'UAM': (144.93, 13.584000000000001),\n",
       " 'UNK': (-160.799, 63.888000000000005),\n",
       " 'UTO': (-153.704, 65.993),\n",
       " 'VAD': (-83.193, 30.968000000000004),\n",
       " 'VCV': (-117.37899999999999, 34.593),\n",
       " 'VDZ': (-146.248, 61.13399999999999),\n",
       " 'VPS': (-86.525, 30.483),\n",
       " 'VQS': (0.0, 0.0),\n",
       " 'VRB': (-80.418, 27.656),\n",
       " 'WRB': (-83.59200000000001, 32.64),\n",
       " 'WRI': (-74.594, 40.016),\n",
       " 'WWD': (-74.908, 39.008),\n",
       " 'YAK': (-139.66, 59.503),\n",
       " 'YIP': (-83.53, 42.238),\n",
       " 'YNG': (-80.679, 41.261),\n",
       " 'YUM': (-114.60600000000001, 32.656)}"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pos_dict"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise\n",
    "\n",
    "Using the position dictionary `pos_dict` create a plot of the airports, only the nodes not the edges.\n",
    "\n",
    "- As we don't have coordinates for all the airports we have to create a subgraph first.\n",
    "- Use `nx.subgraph(Graph, iterable of nodes)` to create the subgraph\n",
    "- Use `nx.draw_networkx_nodes(G, pos)` to map the nodes. \n",
    "\n",
    "or \n",
    "\n",
    "- Just use a scatter plot :)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x120bc6c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 9))\n",
    "G = nx.subgraph(pass_2015, pos_dict.keys())\n",
    "nx.draw_networkx_nodes(G, pos=pos_dict, node_size=10, alpha=0.6, node_color='b')\n",
    "# nx.draw_networkx_edges(G, pos=pos_dict, width=0.1, arrows=False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x113929e80>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1138d06a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 9))\n",
    "x = [i[0] for i in pos_dict.values()]\n",
    "y = [i[1] for i in pos_dict.values()]\n",
    "plt.scatter(x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What about degree distribution of this network?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x120bc6b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(list(nx.degree_centrality(pass_2015).values()))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's plot a log log plot to get a better overview of this."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113992208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "d = {}\n",
    "for i, j in dict(nx.degree(pass_2015)).items():\n",
    "    if j in d:\n",
    "        d[j] += 1\n",
    "    else:\n",
    "        d[j] = 1\n",
    "x = np.log2(list((d.keys())))\n",
    "y = np.log2(list(d.values()))\n",
    "plt.scatter(x, y, alpha=0.4)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Directed Graphs\n",
    "\n",
    "![title](images/pagerank.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "G = nx.DiGraph()\n",
    "\n",
    "G.add_edge(1, 2, weight=1)\n",
    "\n",
    "# print(G.edges())\n",
    "# G[1][2]\n",
    "# G[2][1]\n",
    "# G.is_directed()\n",
    "# type(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1139083c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "G.add_edges_from([(1, 2), (3, 2), (4, 2), (5, 2), (6, 2), (7, 2)])\n",
    "nx.draw_circular(G, with_labels=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "InDegreeView({1: 0, 2: 6, 3: 0, 4: 0, 5: 0, 6: 0, 7: 0})"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.in_degree()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1: 0.0826448180198328,\n",
       " 2: 0.5041310918810031,\n",
       " 3: 0.0826448180198328,\n",
       " 4: 0.0826448180198328,\n",
       " 5: 0.0826448180198328,\n",
       " 6: 0.0826448180198328,\n",
       " 7: 0.0826448180198328}"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.pagerank(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1139d6438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "G.add_edge(5, 6)\n",
    "nx.draw_circular(G, with_labels=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1: 0.08024854052495894,\n",
       " 2: 0.4844028780560986,\n",
       " 3: 0.08024854052495894,\n",
       " 4: 0.08024854052495894,\n",
       " 5: 0.08024854052495894,\n",
       " 6: 0.11435441931910648,\n",
       " 7: 0.08024854052495894}"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.pagerank(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113f09ef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "G.add_edge(2, 8)\n",
    "nx.draw_circular(G, with_labels=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1: 0.05378612718073915,\n",
       " 2: 0.3246687852772877,\n",
       " 3: 0.05378612718073915,\n",
       " 4: 0.05378612718073915,\n",
       " 5: 0.05378612718073915,\n",
       " 6: 0.0766454192258098,\n",
       " 7: 0.05378612718073915,\n",
       " 8: 0.3297551595932067}"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.pagerank(G)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Moving back to Airports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('ANC', 0.010425531156396332),\n",
       " ('HPN', 0.008715287139161587),\n",
       " ('FAI', 0.007865131822111036),\n",
       " ('DFW', 0.007168038232113773),\n",
       " ('DEN', 0.006557279519803018),\n",
       " ('ATL', 0.006367579588749718),\n",
       " ('ORD', 0.006178836107660135),\n",
       " ('YIP', 0.005821525504523931),\n",
       " ('ADQ', 0.005482597083474197),\n",
       " ('MSP', 0.005481962582230961)]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(nx.pagerank(pass_2015, weight=None).items(), key=lambda x:x[1], reverse=True)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('ANC', 0.28907458480586606),\n",
       " ('FAI', 0.08042857784594384),\n",
       " ('SEA', 0.06745549919241699),\n",
       " ('HPN', 0.06046810178534726),\n",
       " ('ORD', 0.045544143864829294),\n",
       " ('ADQ', 0.040170160000905696),\n",
       " ('DEN', 0.038543251364241436),\n",
       " ('BFI', 0.03811277548952854),\n",
       " ('MSP', 0.03774809342340624),\n",
       " ('TEB', 0.036229439542316354)]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(nx.betweenness_centrality(pass_2015).items(), key=lambda x:x[1], reverse=True)[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('ATL', 0.3643595863166269),\n",
       " ('ORD', 0.354813046937152),\n",
       " ('DFW', 0.3420843277645187),\n",
       " ('MSP', 0.3261734287987271),\n",
       " ('DEN', 0.31821797931583135),\n",
       " ('ANC', 0.3046937151949085),\n",
       " ('MEM', 0.29196499602227527),\n",
       " ('LAX', 0.2840095465393795),\n",
       " ('IAH', 0.28082736674622116),\n",
       " ('DTW', 0.27446300715990457)]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(nx.degree_centrality(pass_2015).items(), key=lambda x:x[1], reverse=True)[0:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "'ANC' is the airport code of Anchorage airport, a place in Alaska, and according to pagerank and betweenness centrality it is the most important airport in this network Isn't that weird? Thoughts?\n",
    "\n",
    "related blog post: https://toreopsahl.com/2011/08/12/why-anchorage-is-not-that-important-binary-ties-and-sample-selection/\n",
    "\n",
    "Let's look at weighted version, i.e taking into account the number of people flying to these places."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('SEA', 2.2656145673621046e+50),\n",
       " ('ANC', 1.4996592705774285e+49),\n",
       " ('CDV', 1.1625885650735055e+49),\n",
       " ('ADQ', 8.328664868877188e+48),\n",
       " ('BFI', 6.99097447478957e+48),\n",
       " ('PHX', 3.84552515586718e+48),\n",
       " ('PDX', 3.120901981185909e+48),\n",
       " ('LRD', 4.583490839909188e+47),\n",
       " ('SIT', 1.7910862390475677e+46),\n",
       " ('FAI', 1.137539313512378e+46)]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(nx.betweenness_centrality(pass_2015, weight='weight').items(), key=lambda x:x[1], reverse=True)[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('ATL', 0.037535963029303135),\n",
       " ('ORD', 0.028329766122739346),\n",
       " ('SEA', 0.028274564067008245),\n",
       " ('ANC', 0.027127866647567035),\n",
       " ('DFW', 0.02570050418889442),\n",
       " ('DEN', 0.025260024346433315),\n",
       " ('LAX', 0.02394043498608451),\n",
       " ('PHX', 0.018373176636420224),\n",
       " ('CLT', 0.01780703930063076),\n",
       " ('LAS', 0.017649683141049966)]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(nx.pagerank(pass_2015, weight='weight').items(), key=lambda x:x[1], reverse=True)[0:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How reachable is this network?\n",
    "\n",
    "We calculate the average shortest path length of this network, it gives us an idea about the number of jumps we need to make around the network to go from one airport to any other airport in this network."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "# nx.average_shortest_path_length(pass_2015)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Wait, What??? This network is not connected. That seems like a really stupid thing to do."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'ARA',\n",
       "  'BWI',\n",
       "  'AL3',\n",
       "  'OHC',\n",
       "  'RAP',\n",
       "  'HOM',\n",
       "  'LAN',\n",
       "  'II3',\n",
       "  'GPM',\n",
       "  'MQJ',\n",
       "  'ITO',\n",
       "  'MSY',\n",
       "  'CKV',\n",
       "  'MVL',\n",
       "  'SWD',\n",
       "  'UKI',\n",
       "  'HHH',\n",
       "  'OLV',\n",
       "  'SKF',\n",
       "  'BTT',\n",
       "  'IYK',\n",
       "  'RNT',\n",
       "  'CDC',\n",
       "  'SPN',\n",
       "  'SAN',\n",
       "  'MKE',\n",
       "  'AMW',\n",
       "  'IKO',\n",
       "  'HGR',\n",
       "  'PBG',\n",
       "  'IN2',\n",
       "  'NZY',\n",
       "  'UIN',\n",
       "  'GCC',\n",
       "  'WWA',\n",
       "  'CSG',\n",
       "  'GA6',\n",
       "  'YKM',\n",
       "  'MTM',\n",
       "  'LNS',\n",
       "  'SGR',\n",
       "  'MER',\n",
       "  'GUF',\n",
       "  'ZXU',\n",
       "  'MDW',\n",
       "  'NAD',\n",
       "  'MDT',\n",
       "  'CT1',\n",
       "  'CON',\n",
       "  'GGW',\n",
       "  'UXI',\n",
       "  'CVN',\n",
       "  'CLE',\n",
       "  'WST',\n",
       "  'PIR',\n",
       "  'MEO',\n",
       "  'AVW',\n",
       "  'VLD',\n",
       "  'IGG',\n",
       "  'SVW',\n",
       "  'EKO',\n",
       "  'PNS',\n",
       "  'ASN',\n",
       "  'BJI',\n",
       "  '6B0',\n",
       "  '1NY',\n",
       "  'IMT',\n",
       "  'LFT',\n",
       "  'CTZ',\n",
       "  'HIO',\n",
       "  'GTR',\n",
       "  'UXP',\n",
       "  'FLT',\n",
       "  'RBG',\n",
       "  'EDE',\n",
       "  'UBF',\n",
       "  'CPX',\n",
       "  'NY7',\n",
       "  'KQA',\n",
       "  'SMF',\n",
       "  'JMS',\n",
       "  'CHA',\n",
       "  'RKS',\n",
       "  'ACK',\n",
       "  'AOH',\n",
       "  'ENW',\n",
       "  'GAM',\n",
       "  'KEB',\n",
       "  'CKB',\n",
       "  'LWS',\n",
       "  'MCI',\n",
       "  'AKI',\n",
       "  'ANC',\n",
       "  'SBP',\n",
       "  'RST',\n",
       "  'IAH',\n",
       "  'ONT',\n",
       "  'PTH',\n",
       "  'KVL',\n",
       "  'MBL',\n",
       "  'MNN',\n",
       "  'RHI',\n",
       "  'MHR',\n",
       "  'CEC',\n",
       "  'KGX',\n",
       "  'DJN',\n",
       "  'WWD',\n",
       "  '1G4',\n",
       "  'SWF',\n",
       "  'AK6',\n",
       "  'HRO',\n",
       "  'HNS',\n",
       "  'KOZ',\n",
       "  'ROW',\n",
       "  'KWK',\n",
       "  'CLU',\n",
       "  'GST',\n",
       "  'SHG',\n",
       "  'MFR',\n",
       "  'PIP',\n",
       "  'JAN',\n",
       "  'UOX',\n",
       "  'TEB',\n",
       "  'ISN',\n",
       "  'MQT',\n",
       "  'PSM',\n",
       "  'EDF',\n",
       "  'RWI',\n",
       "  'EGE',\n",
       "  'CDV',\n",
       "  'TKF',\n",
       "  'HUS',\n",
       "  'VRB',\n",
       "  'CZF',\n",
       "  'KPN',\n",
       "  'WWT',\n",
       "  'PIZ',\n",
       "  'RNO',\n",
       "  'WRL',\n",
       "  'GDC',\n",
       "  'A52',\n",
       "  'CYS',\n",
       "  'ELV',\n",
       "  'AET',\n",
       "  'SEA',\n",
       "  'DTO',\n",
       "  'FRG',\n",
       "  'CZN',\n",
       "  'FYV',\n",
       "  'TX1',\n",
       "  'NC1',\n",
       "  'ME2',\n",
       "  'KAE',\n",
       "  'PHF',\n",
       "  'MCK',\n",
       "  'MLB',\n",
       "  'ILI',\n",
       "  'TMB',\n",
       "  'LPS',\n",
       "  'KNK',\n",
       "  'PIT',\n",
       "  'EGV',\n",
       "  'MYU',\n",
       "  'SJU',\n",
       "  'MEI',\n",
       "  'FAQ',\n",
       "  'LUK',\n",
       "  'SUM',\n",
       "  'SLE',\n",
       "  'KEH',\n",
       "  'MMU',\n",
       "  'ORV',\n",
       "  'BOI',\n",
       "  'BFB',\n",
       "  'RKD',\n",
       "  'LKP',\n",
       "  'LFI',\n",
       "  'SBD',\n",
       "  'CHP',\n",
       "  'GBH',\n",
       "  'TYE',\n",
       "  'HAO',\n",
       "  'LRU',\n",
       "  'AOO',\n",
       "  'GBR',\n",
       "  'KPB',\n",
       "  'MTN',\n",
       "  'EAA',\n",
       "  'PYM',\n",
       "  'SOW',\n",
       "  'FOK',\n",
       "  'LOZ',\n",
       "  'GYY',\n",
       "  'GAI',\n",
       "  'KTN',\n",
       "  'AKK',\n",
       "  'STT',\n",
       "  'PBK',\n",
       "  'MRN',\n",
       "  'AK5',\n",
       "  'VAK',\n",
       "  'SHH',\n",
       "  'HUF',\n",
       "  'PUB',\n",
       "  'DQK',\n",
       "  'DE3',\n",
       "  'SJC',\n",
       "  'OTZ',\n",
       "  'AZ3',\n",
       "  'LZU',\n",
       "  'A27',\n",
       "  'ITH',\n",
       "  'JZT',\n",
       "  'DDC',\n",
       "  'MCW',\n",
       "  'WSN',\n",
       "  'SEE',\n",
       "  'BJC',\n",
       "  'IAD',\n",
       "  'JAX',\n",
       "  'LAS',\n",
       "  'BAD',\n",
       "  'RSN',\n",
       "  'INL',\n",
       "  'WSX',\n",
       "  'CWI',\n",
       "  'VT1',\n",
       "  'FMH',\n",
       "  'PWM',\n",
       "  'PPG',\n",
       "  'GBD',\n",
       "  'KMO',\n",
       "  'AGC',\n",
       "  'LVK',\n",
       "  'JBR',\n",
       "  'WLK',\n",
       "  'ALS',\n",
       "  'KY1',\n",
       "  'SNA',\n",
       "  'AZA',\n",
       "  'KWT',\n",
       "  'DUT',\n",
       "  'XWF',\n",
       "  'PVC',\n",
       "  'RIC',\n",
       "  'WTK',\n",
       "  'RBY',\n",
       "  'VZR',\n",
       "  'SGY',\n",
       "  'BTV',\n",
       "  'BAF',\n",
       "  'WKK',\n",
       "  'ISO',\n",
       "  'VZE',\n",
       "  'KLG',\n",
       "  'JZU',\n",
       "  'VQS',\n",
       "  'TWA',\n",
       "  'SYR',\n",
       "  'SFZ',\n",
       "  'PDX',\n",
       "  'NJK',\n",
       "  'MOB',\n",
       "  'SCH',\n",
       "  'ONH',\n",
       "  'LNY',\n",
       "  'WRI',\n",
       "  'LGU',\n",
       "  'WWP',\n",
       "  'TUS',\n",
       "  'GRK',\n",
       "  'ANB',\n",
       "  'GRF',\n",
       "  'ROP',\n",
       "  'MI2',\n",
       "  'RQZ',\n",
       "  'KZB',\n",
       "  'CEM',\n",
       "  'MSC',\n",
       "  'ZXN',\n",
       "  'BFM',\n",
       "  'HVR',\n",
       "  'WA7',\n",
       "  'SKK',\n",
       "  'HTS',\n",
       "  'GAL',\n",
       "  'UGB',\n",
       "  'HCR',\n",
       "  'AMA',\n",
       "  'MLY',\n",
       "  'AL7',\n",
       "  'CAE',\n",
       "  'JAC',\n",
       "  'CO3',\n",
       "  'MWH',\n",
       "  'IN1',\n",
       "  'CDL',\n",
       "  'KXA',\n",
       "  'HRL',\n",
       "  'MTO',\n",
       "  'EUG',\n",
       "  'MGW',\n",
       "  'PDT',\n",
       "  'IRK',\n",
       "  'MIE',\n",
       "  'CRP',\n",
       "  'FXE',\n",
       "  'DNL',\n",
       "  'CEU',\n",
       "  'CIC',\n",
       "  'AKN',\n",
       "  'JZI',\n",
       "  'SMO',\n",
       "  'PTD',\n",
       "  'ALZ',\n",
       "  'BIH',\n",
       "  'DXR',\n",
       "  'COE',\n",
       "  'CIK',\n",
       "  'KPV',\n",
       "  'STL',\n",
       "  'MHK',\n",
       "  'DSM',\n",
       "  'MCO',\n",
       "  'SAC',\n",
       "  'DHB',\n",
       "  'ORH',\n",
       "  'ADQ',\n",
       "  'CLF',\n",
       "  'ANI',\n",
       "  'FWA',\n",
       "  'ISM',\n",
       "  'GLV',\n",
       "  'HYA',\n",
       "  'IAG',\n",
       "  'PSC',\n",
       "  'NIN',\n",
       "  'OOK',\n",
       "  'APN',\n",
       "  'TN5',\n",
       "  'TN1',\n",
       "  'ZXB',\n",
       "  'NBG',\n",
       "  'MZJ',\n",
       "  'RIV',\n",
       "  'ACT',\n",
       "  'FQW',\n",
       "  'ALB',\n",
       "  'KWP',\n",
       "  'MD1',\n",
       "  'KYK',\n",
       "  'BRL',\n",
       "  'TSP',\n",
       "  'SPI',\n",
       "  'DVT',\n",
       "  'FID',\n",
       "  'CLM',\n",
       "  'BDY',\n",
       "  'HYS',\n",
       "  'TEK',\n",
       "  'FVQ',\n",
       "  'SQA',\n",
       "  'LVD',\n",
       "  'DFW',\n",
       "  'ORI',\n",
       "  'DPA',\n",
       "  'KSM',\n",
       "  'PAE',\n",
       "  'FLG',\n",
       "  'HOB',\n",
       "  'BFL',\n",
       "  'KKB',\n",
       "  'ABI',\n",
       "  'EWB',\n",
       "  'BBD',\n",
       "  'JLN',\n",
       "  'EAT',\n",
       "  'A63',\n",
       "  'FVX',\n",
       "  'HTO',\n",
       "  'KOY',\n",
       "  'MQY',\n",
       "  'LEX',\n",
       "  'LAF',\n",
       "  'VCV',\n",
       "  'SSI',\n",
       "  'HON',\n",
       "  'CLG',\n",
       "  'XXN',\n",
       "  'PUL',\n",
       "  'OAK',\n",
       "  'PVD',\n",
       "  'SFO',\n",
       "  'AA8',\n",
       "  'BFD',\n",
       "  'EKA',\n",
       "  'PGA',\n",
       "  'OSU',\n",
       "  'CMX',\n",
       "  'LBF',\n",
       "  'SFB',\n",
       "  'GSB',\n",
       "  'MCF',\n",
       "  'ERI',\n",
       "  'MGM',\n",
       "  'IAB',\n",
       "  'SBY',\n",
       "  'GVT',\n",
       "  'KWF',\n",
       "  'FDY',\n",
       "  'XXY',\n",
       "  'VGC',\n",
       "  'LUP',\n",
       "  'SCM',\n",
       "  'MJX',\n",
       "  'AST',\n",
       "  'SOV',\n",
       "  'PEC',\n",
       "  'PWK',\n",
       "  'OFF',\n",
       "  'PNE',\n",
       "  'TSG',\n",
       "  'PWT',\n",
       "  'SNS',\n",
       "  'RBW',\n",
       "  'FMY',\n",
       "  'ADK',\n",
       "  'VWX',\n",
       "  'OLE',\n",
       "  'TRM',\n",
       "  'F70',\n",
       "  'PLN',\n",
       "  'CMH',\n",
       "  'PGM',\n",
       "  'TCL',\n",
       "  'DOV',\n",
       "  'TIW',\n",
       "  'CBE',\n",
       "  'GUS',\n",
       "  'LCH',\n",
       "  'MA5',\n",
       "  'ONP',\n",
       "  'TRI',\n",
       "  'CRS',\n",
       "  'OCF',\n",
       "  'KCC',\n",
       "  'DRO',\n",
       "  'JZY',\n",
       "  'TKJ',\n",
       "  'ALW',\n",
       "  'A02',\n",
       "  'BMI',\n",
       "  'APF',\n",
       "  'YUM',\n",
       "  'XSD',\n",
       "  'VNY',\n",
       "  'PHX',\n",
       "  'TOG',\n",
       "  'BCT',\n",
       "  'SSW',\n",
       "  'KUK',\n",
       "  'BYA',\n",
       "  'TLT',\n",
       "  'CWA',\n",
       "  'LWM',\n",
       "  'PIB',\n",
       "  'AIA',\n",
       "  'MRF',\n",
       "  'PDK',\n",
       "  'SZL',\n",
       "  'BFT',\n",
       "  'CXF',\n",
       "  'LAL',\n",
       "  'ZXH',\n",
       "  'SVA',\n",
       "  'GPT',\n",
       "  'DQY',\n",
       "  'SUN',\n",
       "  'JCT',\n",
       "  'LSE',\n",
       "  'SVC',\n",
       "  'VUO',\n",
       "  'LGB',\n",
       "  'DTW',\n",
       "  'AFW',\n",
       "  'MFD',\n",
       "  'HSV',\n",
       "  'UGI',\n",
       "  'EEK',\n",
       "  'MDH',\n",
       "  'FRD',\n",
       "  'CGA',\n",
       "  'CHU',\n",
       "  'BQK',\n",
       "  'BTP',\n",
       "  'PTW',\n",
       "  'TYR',\n",
       "  'LOT',\n",
       "  'JRV',\n",
       "  'PRC',\n",
       "  'SLK',\n",
       "  'AUO',\n",
       "  'A43',\n",
       "  'TLF',\n",
       "  'TXK',\n",
       "  'LCI',\n",
       "  'SEG',\n",
       "  'MA1',\n",
       "  'GSH',\n",
       "  'WAA',\n",
       "  'MAZ',\n",
       "  'KTB',\n",
       "  'SDF',\n",
       "  'BOS',\n",
       "  'SXP',\n",
       "  'PUW',\n",
       "  'ABY',\n",
       "  'CVS',\n",
       "  'AVP',\n",
       "  'VZY',\n",
       "  'OKC',\n",
       "  'ZNC',\n",
       "  'A2K',\n",
       "  'LAX',\n",
       "  'WVI',\n",
       "  'GEK',\n",
       "  'ILN',\n",
       "  'DBQ',\n",
       "  'DRT',\n",
       "  'PWA',\n",
       "  'DQL',\n",
       "  'BYW',\n",
       "  'BKE',\n",
       "  'RLU',\n",
       "  'IWD',\n",
       "  'MTH',\n",
       "  'OLH',\n",
       "  'FAT',\n",
       "  'NHZ',\n",
       "  'AZO',\n",
       "  'QMN',\n",
       "  'AKP',\n",
       "  'KKI',\n",
       "  'RDU',\n",
       "  'LIH',\n",
       "  'BHM',\n",
       "  'VIS',\n",
       "  'DQS',\n",
       "  'BOK',\n",
       "  'JHM',\n",
       "  'ICT',\n",
       "  'NGU',\n",
       "  'SBN',\n",
       "  'STP',\n",
       "  'TVF',\n",
       "  'EYW',\n",
       "  'TIK',\n",
       "  'OXC',\n",
       "  'KMY',\n",
       "  'CBA',\n",
       "  'HLN',\n",
       "  'VPZ',\n",
       "  'SAF',\n",
       "  'BDR',\n",
       "  'ISP',\n",
       "  'PAH',\n",
       "  'WNA',\n",
       "  'CHD',\n",
       "  'SUA',\n",
       "  'GSP',\n",
       "  'OLU',\n",
       "  'EXI',\n",
       "  'SMX',\n",
       "  'DLH',\n",
       "  'PSE',\n",
       "  'HSL',\n",
       "  'ATL',\n",
       "  'HKB',\n",
       "  'TIX',\n",
       "  'MNT',\n",
       "  'MKG',\n",
       "  'HNH',\n",
       "  'MHM',\n",
       "  'KPC',\n",
       "  'SCC',\n",
       "  'MKL',\n",
       "  'GFK',\n",
       "  'NJ1',\n",
       "  'CPS',\n",
       "  'MAF',\n",
       "  'MOT',\n",
       "  'BLM',\n",
       "  'HPN',\n",
       "  'HOU',\n",
       "  'VCT',\n",
       "  'ELM',\n",
       "  'C1A',\n",
       "  'ACV',\n",
       "  'STC',\n",
       "  'SHV',\n",
       "  'SBM',\n",
       "  'WGO',\n",
       "  'BMC',\n",
       "  'BUR',\n",
       "  'BIS',\n",
       "  'AUZ',\n",
       "  'FNT',\n",
       "  'CLD',\n",
       "  'PKA',\n",
       "  'A29',\n",
       "  'CSM',\n",
       "  'BZN',\n",
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       "  'UST',\n",
       "  'MT2',\n",
       "  'RSJ',\n",
       "  'VEL',\n",
       "  'ILM',\n",
       "  'TKE',\n",
       "  'PHN',\n",
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       "  'GNU',\n",
       "  'IPT',\n",
       "  'GKN',\n",
       "  'SOP',\n",
       "  'PQS',\n",
       "  'BTI',\n",
       "  'PA7',\n",
       "  'ENV',\n",
       "  'SSC',\n",
       "  'SYB',\n",
       "  'FBK',\n",
       "  'PCA',\n",
       "  'RFD',\n",
       "  'SJT',\n",
       "  'VZM',\n",
       "  'PRB',\n",
       "  'KGK',\n",
       "  'DGB',\n",
       "  'VA6',\n",
       "  'MSO',\n",
       "  'BGR',\n",
       "  'ALN',\n",
       "  'PSG',\n",
       "  'GUM',\n",
       "  'LNI',\n",
       "  'KNB',\n",
       "  'SUX',\n",
       "  'TLA',\n",
       "  'SYA',\n",
       "  'LSV',\n",
       "  'CVG',\n",
       "  'PHO',\n",
       "  'GCK',\n",
       "  'RDD',\n",
       "  'RME',\n",
       "  'MTP',\n",
       "  'ROA',\n",
       "  'PCT',\n",
       "  'GGE',\n",
       "  'PKB',\n",
       "  'PBI',\n",
       "  'COS',\n",
       "  'ORL',\n",
       "  'ME4',\n",
       "  'FBS',\n",
       "  'SGU',\n",
       "  'NUQ',\n",
       "  'QQN',\n",
       "  'BTM',\n",
       "  'UES',\n",
       "  'DE2',\n",
       "  '7AK',\n",
       "  'TAL',\n",
       "  'BED',\n",
       "  ...},\n",
       " {'SPB', 'SSB'},\n",
       " {'AIK'}]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(nx.weakly_connected_components(pass_2015))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SPB, SSB, AIK anyone?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>ORIGIN</th>\n",
       "      <th>DEST</th>\n",
       "      <th>UNIQUE_CARRIER_NAME</th>\n",
       "      <th>PASSENGERS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>433338</th>\n",
       "      <td>433338</td>\n",
       "      <td>2015</td>\n",
       "      <td>AIK</td>\n",
       "      <td>AIK</td>\n",
       "      <td>{'Wright Air Service'}</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Unnamed: 0  YEAR ORIGIN DEST     UNIQUE_CARRIER_NAME  PASSENGERS\n",
       "433338      433338  2015    AIK  AIK  {'Wright Air Service'}         0.0"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pass_air_data[(pass_air_data['YEAR'] == 2015) & (pass_air_data['ORIGIN'] == 'AIK')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "pass_2015.remove_nodes_from(['SPB', 'SSB', 'AIK'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.is_weakly_connected(pass_2015)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.is_strongly_connected(pass_2015)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Strongly vs weakly connected graphs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113f45a20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "G = nx.DiGraph()\n",
    "G.add_edge(1, 2)\n",
    "G.add_edge(2, 3)\n",
    "G.add_edge(3, 1)\n",
    "nx.draw(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113ed3390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "G.add_edge(3, 4)\n",
    "nx.draw(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.is_strongly_connected(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'BCE'},\n",
       " {'WA3'},\n",
       " {'WA9'},\n",
       " {'TIW'},\n",
       " {'RQV'},\n",
       " {'SUA'},\n",
       " {'POU'},\n",
       " {'MA5'},\n",
       " {'MXF'},\n",
       " {'TSP'},\n",
       " {'MSV'},\n",
       " {'AST'},\n",
       " {'XXU'},\n",
       " {'OR2'},\n",
       " {'CLG'},\n",
       " {'QQN'},\n",
       " {'WVI'},\n",
       " {'CO3'},\n",
       " {'BOK'},\n",
       " {'XXY'},\n",
       " {'ZXC'},\n",
       " {'ZXT'},\n",
       " {'C1A'},\n",
       " {'ELN'},\n",
       " {'BKE'},\n",
       " {'EKI'},\n",
       " {'MA4'},\n",
       " {'MI6'},\n",
       " {'TMB'},\n",
       " {'XWF'},\n",
       " {'LZU'},\n",
       " {'GUF'},\n",
       " {'N1Y'},\n",
       " {'DKK'},\n",
       " {'TIX'},\n",
       " {'MRF'},\n",
       " {'VAD'},\n",
       " {'ARA',\n",
       "  'BWI',\n",
       "  'AL3',\n",
       "  'OHC',\n",
       "  'RAP',\n",
       "  'HOM',\n",
       "  'LAN',\n",
       "  'II3',\n",
       "  'MQJ',\n",
       "  'ITO',\n",
       "  'MSY',\n",
       "  'CKV',\n",
       "  'MVL',\n",
       "  'SWD',\n",
       "  'UKI',\n",
       "  'OLV',\n",
       "  'HHH',\n",
       "  'SKF',\n",
       "  'BTT',\n",
       "  'IYK',\n",
       "  'RNT',\n",
       "  'CDC',\n",
       "  'IKO',\n",
       "  'AMW',\n",
       "  'MKE',\n",
       "  'SAN',\n",
       "  'SPN',\n",
       "  'HGR',\n",
       "  'IN2',\n",
       "  'PBG',\n",
       "  'NZY',\n",
       "  'GCC',\n",
       "  'UIN',\n",
       "  'WWA',\n",
       "  'CSG',\n",
       "  'GA6',\n",
       "  'YKM',\n",
       "  'MTM',\n",
       "  'LNS',\n",
       "  'MER',\n",
       "  'SGR',\n",
       "  'ZXU',\n",
       "  'MDW',\n",
       "  'NAD',\n",
       "  'MDT',\n",
       "  'CT1',\n",
       "  'CON',\n",
       "  'GGW',\n",
       "  'UXI',\n",
       "  'CVN',\n",
       "  'CLE',\n",
       "  'WST',\n",
       "  'PIR',\n",
       "  'MEO',\n",
       "  'AVW',\n",
       "  'VLD',\n",
       "  'IGG',\n",
       "  'SVW',\n",
       "  'EKO',\n",
       "  'PNS',\n",
       "  'ASN',\n",
       "  'BJI',\n",
       "  '6B0',\n",
       "  '1NY',\n",
       "  'IMT',\n",
       "  'LFT',\n",
       "  'CTZ',\n",
       "  'HIO',\n",
       "  'GTR',\n",
       "  'FLT',\n",
       "  'RBG',\n",
       "  'EDE',\n",
       "  'UBF',\n",
       "  'CPX',\n",
       "  'KQA',\n",
       "  'NY7',\n",
       "  'SMF',\n",
       "  'JMS',\n",
       "  'CHA',\n",
       "  'ACK',\n",
       "  'AOH',\n",
       "  'RKS',\n",
       "  'ENW',\n",
       "  'GAM',\n",
       "  'KEB',\n",
       "  'CKB',\n",
       "  'LWS',\n",
       "  'MCI',\n",
       "  'AKI',\n",
       "  'ANC',\n",
       "  'GCK',\n",
       "  'SBP',\n",
       "  'RST',\n",
       "  'IAH',\n",
       "  'PTH',\n",
       "  'KVL',\n",
       "  'ONT',\n",
       "  'MNN',\n",
       "  'MBL',\n",
       "  'MHR',\n",
       "  'RHI',\n",
       "  'CEC',\n",
       "  'KGX',\n",
       "  'WWD',\n",
       "  '1G4',\n",
       "  'AK6',\n",
       "  'SWF',\n",
       "  'HRO',\n",
       "  'HNS',\n",
       "  'KOZ',\n",
       "  'ROW',\n",
       "  'KWK',\n",
       "  'CLU',\n",
       "  'GST',\n",
       "  'SHG',\n",
       "  'MFR',\n",
       "  'PIP',\n",
       "  'JAN',\n",
       "  'FBK',\n",
       "  'UOX',\n",
       "  'ISN',\n",
       "  'TEB',\n",
       "  'EDF',\n",
       "  'PSM',\n",
       "  'HUS',\n",
       "  'CDV',\n",
       "  'EGE',\n",
       "  'RWI',\n",
       "  'TKF',\n",
       "  'MQT',\n",
       "  'KPN',\n",
       "  'VRB',\n",
       "  'WWT',\n",
       "  'CZF',\n",
       "  'PIZ',\n",
       "  'WRL',\n",
       "  'RNO',\n",
       "  'GDC',\n",
       "  'A52',\n",
       "  'CYS',\n",
       "  'ELV',\n",
       "  'AET',\n",
       "  'SEA',\n",
       "  'DTO',\n",
       "  'FRG',\n",
       "  'CZN',\n",
       "  'FYV',\n",
       "  'TX1',\n",
       "  'NC1',\n",
       "  'ME2',\n",
       "  'KAE',\n",
       "  'MCK',\n",
       "  'PHF',\n",
       "  'ILI',\n",
       "  'MLB',\n",
       "  'LPS',\n",
       "  'MYU',\n",
       "  'EGV',\n",
       "  'FAQ',\n",
       "  'PIT',\n",
       "  'KNK',\n",
       "  'SJU',\n",
       "  'KEH',\n",
       "  'MEI',\n",
       "  'LUK',\n",
       "  'SLE',\n",
       "  'MMU',\n",
       "  'BFB',\n",
       "  'ORV',\n",
       "  'BOI',\n",
       "  'LKP',\n",
       "  'RKD',\n",
       "  'CHP',\n",
       "  'LFI',\n",
       "  'GBH',\n",
       "  'SBD',\n",
       "  'TYE',\n",
       "  'AOO',\n",
       "  'LRU',\n",
       "  'GBR',\n",
       "  'KPB',\n",
       "  'MTN',\n",
       "  'EAA',\n",
       "  'PYM',\n",
       "  'SOW',\n",
       "  'LOZ',\n",
       "  'FOK',\n",
       "  'GYY',\n",
       "  'GAI',\n",
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       "  'ME4',\n",
       "  'ROA',\n",
       "  'FBS',\n",
       "  'RME',\n",
       "  'PKB',\n",
       "  'PBI',\n",
       "  'COS',\n",
       "  'PCT',\n",
       "  'ORL',\n",
       "  'MXY',\n",
       "  'TAL',\n",
       "  '7AK',\n",
       "  'DE2',\n",
       "  'BTM',\n",
       "  'UES',\n",
       "  'SGU',\n",
       "  'JRF',\n",
       "  'WA1',\n",
       "  'BED',\n",
       "  'ELI',\n",
       "  'PTV',\n",
       "  'SAV',\n",
       "  'T1X',\n",
       "  'SLC',\n",
       "  'JZM',\n",
       "  'BLI',\n",
       "  'PTU',\n",
       "  'FLO',\n",
       "  'UNK',\n",
       "  'CMI',\n",
       "  'SGF',\n",
       "  'VIK',\n",
       "  'NTU',\n",
       "  'T2X',\n",
       "  'GUP',\n",
       "  'OTH',\n",
       "  'ISS',\n",
       "  'LAW',\n",
       "  'ARB',\n",
       "  'SWO',\n",
       "  'UTO',\n",
       "  'TVL',\n",
       "  'KLS',\n",
       "  'RIL',\n",
       "  'AGN',\n",
       "  'SPS',\n",
       "  'BKL',\n",
       "  'FAR',\n",
       "  'MVN',\n",
       "  'GRR',\n",
       "  'HII',\n",
       "  'LIV',\n",
       "  'RIW',\n",
       "  'C01',\n",
       "  'BLD',\n",
       "  'JNU',\n",
       "  'AVL',\n",
       "  'BTL',\n",
       "  'AK2',\n",
       "  'SDX',\n",
       "  'PSF',\n",
       "  'DEN',\n",
       "  'LWB',\n",
       "  'OPF',\n",
       "  'A04',\n",
       "  'OME',\n",
       "  'PA2',\n",
       "  'BUF',\n",
       "  'QMA',\n",
       "  ...},\n",
       " {'LSV'},\n",
       " {'FFO'},\n",
       " {'NGF'},\n",
       " {'NPA'},\n",
       " {'NUQ'},\n",
       " {'UXP'},\n",
       " {'GSB'},\n",
       " {'VWX'},\n",
       " {'PAM'},\n",
       " {'GRF'},\n",
       " {'FPR'},\n",
       " {'HAO'},\n",
       " {'NJK'},\n",
       " {'DJN'},\n",
       " {'SUM'},\n",
       " {'NBG'},\n",
       " {'OFF'},\n",
       " {'AWM'},\n",
       " {'ISM'},\n",
       " {'KY3'},\n",
       " {'MMT'},\n",
       " {'QMN'},\n",
       " {'CDW'},\n",
       " {'MA1'},\n",
       " {'HIE'},\n",
       " {'B19'},\n",
       " {'F70'},\n",
       " {'DQY'}]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(nx.strongly_connected_components(pass_2015))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>ORIGIN</th>\n",
       "      <th>DEST</th>\n",
       "      <th>UNIQUE_CARRIER_NAME</th>\n",
       "      <th>PASSENGERS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>450245</th>\n",
       "      <td>450245</td>\n",
       "      <td>2015</td>\n",
       "      <td>ONT</td>\n",
       "      <td>TSP</td>\n",
       "      <td>{'Federal Express Corporation'}</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Unnamed: 0  YEAR ORIGIN DEST              UNIQUE_CARRIER_NAME  \\\n",
       "450245      450245  2015    ONT  TSP  {'Federal Express Corporation'}   \n",
       "\n",
       "        PASSENGERS  \n",
       "450245         0.0  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pass_air_data[(pass_air_data['YEAR'] == 2015) & (pass_air_data['DEST'] == 'TSP')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "pass_2015_strong = max(nx.strongly_connected_component_subgraphs(pass_2015), key=len)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1190"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(pass_2015_strong)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.174661992635574"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.average_shortest_path_length(pass_2015_strong)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Exercise! (Actually this is a game :D)\n",
    "\n",
    "How can we decrease the avg shortest path length of this network?\n",
    "\n",
    "Think of an effective way to add new edges to decrease the avg shortest path length.\n",
    "Let's see if we can come up with a nice way to do this, and the one who gets the highest decrease wins!!!\n",
    "\n",
    "The rules are simple:\n",
    "- You can't add more than 2% of the current edges( ~500 edges)\n",
    "\n",
    "[10 mins]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "sort_degree = sorted(nx.degree_centrality(pass_2015_strong).items(), key=lambda x:x[1], reverse=True)\n",
    "top_count = 0\n",
    "for n, v in sort_degree:\n",
    "    count = 0\n",
    "    for node, val in sort_degree:\n",
    "        if node != n:\n",
    "            if node not in pass_2015_strong.adj[n]:\n",
    "                pass_2015_strong.add_edge(n, node)\n",
    "                count += 1\n",
    "                if count == 25:\n",
    "                    break\n",
    "    top_count += 1\n",
    "    if top_count == 20:\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.0887724307553133"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.average_shortest_path_length(pass_2015_strong)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What about airlines? Can we find airline specific reachability?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'PASSENGERS': 1179941.0,\n",
       " 'UNIQUE_CARRIER_NAME': \"{'Delta Air Lines Inc.', 'Virgin America', 'American Airlines Inc.', 'Sun Country Airlines d/b/a MN Airlines', 'JetBlue Airways', 'Vision Airlines', 'United Air Lines Inc.'}\",\n",
       " 'YEAR': 2015}"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "passenger_graph['JFK']['SFO'][25]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "def str_to_list(a):\n",
    "    return a[1:-1].split(', ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'Delta Air Lines Inc.'\n",
      "'Virgin America'\n",
      "'American Airlines Inc.'\n",
      "'Sun Country Airlines d/b/a MN Airlines'\n",
      "'JetBlue Airways'\n",
      "'Vision Airlines'\n",
      "'United Air Lines Inc.'\n"
     ]
    }
   ],
   "source": [
    "for i in str_to_list(passenger_graph['JFK']['SFO'][25]['UNIQUE_CARRIER_NAME']):\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 52.9 s, sys: 722 ms, total: 53.6 s\n",
      "Wall time: 56.3 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "for origin, dest in passenger_graph.edges():\n",
    "    for key in passenger_graph[origin][dest]:\n",
    "        passenger_graph[origin][dest][key]['airlines'] = str_to_list(passenger_graph[origin][dest][key]['UNIQUE_CARRIER_NAME'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercise\n",
    "\n",
    "Play around with United Airlines network.\n",
    "\n",
    "- Extract a network for United Airlines flights from the metagraph `passenger_graph` for the year 2015\n",
    "- Make sure it's a weighted network, where weight is the number of passengers.\n",
    "- Find the number of airports and connections in this network\n",
    "- Find the most important airport, according to PageRank and degree centrality."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "united_network = nx.DiGraph()\n",
    "for origin, dest in passenger_graph.edges():\n",
    "    if 25 in passenger_graph[origin][dest]:\n",
    "        if \"'United Air Lines Inc.'\" in passenger_graph[origin][dest][25]['airlines']:\n",
    "            united_network.add_edge(origin, dest, weight=passenger_graph[origin][dest][25]['PASSENGERS'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "134"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(united_network)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1097"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(united_network.edges())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('ORD', 0.09229686412847604),\n",
       " ('DEN', 0.06951536832747153),\n",
       " ('LAX', 0.05547087049076451),\n",
       " ('SFO', 0.04520212084776551),\n",
       " ('IAH', 0.04398280474534501),\n",
       " ('EWR', 0.03754166218607773),\n",
       " ('ATL', 0.034778751100523315),\n",
       " ('DFW', 0.03419728511206331),\n",
       " ('PHX', 0.025365344038763896),\n",
       " ('MSP', 0.022269133819322266)]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(nx.pagerank(united_network, weight='weight').items(), key=lambda x:x[1], reverse=True)[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('ORD', 1.1729323308270676),\n",
       " ('DEN', 0.9172932330827067),\n",
       " ('IAH', 0.8195488721804511),\n",
       " ('EWR', 0.744360902255639),\n",
       " ('SFO', 0.5789473684210527),\n",
       " ('LAX', 0.5338345864661653),\n",
       " ('IAD', 0.5112781954887218),\n",
       " ('CLE', 0.39849624060150374),\n",
       " ('STL', 0.3609022556390977),\n",
       " ('PHL', 0.3308270676691729)]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(nx.degree_centrality(united_network).items(), key=lambda x:x[1], reverse=True)[0:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercise\n",
    "\n",
    "We are in Cleveland so what should we do?\n",
    "\n",
    "Obviously we will make a time series of number of passengers flying out of Cleveland with United Airlines over the years.\n",
    "\n",
    "There are 2 ways of doing it.\n",
    "- Create a new multidigraph specifically for this exercise.\n",
    "\n",
    "OR\n",
    "\n",
    "- exploit the `pass_air_data` dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12808ec18>"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12808e390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pass_air_data[(pass_air_data.ORIGIN == 'CLE') &\n",
    "              (pass_air_data.UNIQUE_CARRIER_NAME.str.contains('United Air Lines Inc.'))\n",
    "             ].groupby('YEAR')['PASSENGERS'].sum().plot()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}