US-aiports-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": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/seth/dev/venv/system/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n",
      "  return f(*args, **kwds)\n"
     ]
    }
   ],
   "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('data/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",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\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": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1053cd2e8>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pass_air_data[pass_air_data.DEST == 'HNL'].groupby(['YEAR'])['PASSENGERS'].sum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1061ed8d0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pass_air_data[pass_air_data.DEST == 'OGG'].groupby(['YEAR'])['PASSENGERS'].sum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1062436a0>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pass_air_data[pass_air_data.DEST == 'KOA'].groupby(['YEAR'])['PASSENGERS'].sum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a MultiDiGraph from this dataset\n",
    "passenger_graph = nx.from_pandas_edgelist(pass_air_data, source='ORIGIN', target='DEST',\n",
    "                                          edge_attr=['YEAR', 'PASSENGERS', 'UNIQUE_CARRIER_NAME'],\n",
    "                                          create_using=nx.MultiDiGraph())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cleveland to Chicago, how many people fly this route?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'YEAR': 2014,\n",
       " 'PASSENGERS': 392492.0,\n",
       " 'UNIQUE_CARRIER_NAME': \"{'Frontier Airlines Inc.', 'Chautauqua Airlines Inc.', 'SkyWest Airlines Inc.', 'Republic Airlines', 'ExpressJet Airlines Inc.', 'GoJet Airlines LLC d/b/a United Express', 'Trans States Airlines', 'Envoy Air', 'Shuttle America Corp.', 'United Air Lines Inc.'}\"}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "passenger_graph['CLE']['ORD'][24]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "temp = [(i['YEAR'], i['PASSENGERS'])for i in dict(passenger_graph['JFK']['SFO']).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": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp = pass_air_data.groupby(['YEAR'\n",
    "        ])['PASSENGERS'].transform(max) == pass_air_data['PASSENGERS']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\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": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pass_air_data[temp][pass_air_data.YEAR.isin([1990, 2015])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10624cbe0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "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": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1133bfd30>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pass_air_data[(pass_air_data['ORIGIN'] == 'LAX') & (pass_air_data['DEST'] == 'SFO')].plot('YEAR', 'PASSENGERS')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Extract year graph from passenger_graph\n",
    "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": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "pass_2015 = year_network(passenger_graph, 2015)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1258"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(pass_2015)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25354"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(pass_2015.edges())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load in the GPS coordinates of all the airports\n",
    "lat_long = pd.read_csv('data/GlobalAirportDatabase.txt', delimiter=':', header=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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",
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       "      <th>3</th>\n",
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       "      <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": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lat_long[lat_long[1].isin(list(pass_2015.nodes()))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'CLF': (1.357, 52.755),\n",
       " 'ABI': (-99.682, 32.411),\n",
       " 'ABQ': (-106.609, 35.04),\n",
       " 'ACK': (-70.06, 41.253),\n",
       " 'ACT': (-97.23, 31.611),\n",
       " 'ACY': (-74.577, 39.458),\n",
       " 'ADW': (-76.867, 38.811),\n",
       " 'AEX': (-92.54799999999999, 31.326999999999998),\n",
       " 'AGS': (-81.964, 33.37),\n",
       " 'ALB': (-73.803, 42.748000000000005),\n",
       " 'AMA': (-101.706, 35.219),\n",
       " 'ANB': (-85.85799999999999, 33.588),\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",
       " '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",
       " 'BRO': (-97.426, 25.906999999999996),\n",
       " 'BTR': (-91.149, 30.533),\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",
       " 'CDC': (-113.09899999999999, 37.701),\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",
       " '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",
       " '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",
       " '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",
       " 'EDW': (-117.884, 34.905),\n",
       " 'EFD': (-95.15899999999999, 29.607),\n",
       " 'ELD': (-92.81299999999999, 33.221),\n",
       " 'ELP': (-106.37799999999999, 31.807),\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",
       " 'FAT': (-119.71799999999999, 36.775999999999996),\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",
       " 'FYV': (-94.17, 36.005),\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",
       " '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",
       " '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",
       " 'HOB': (-103.21700000000001, 32.688),\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",
       " '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",
       " 'JAN': (-90.07600000000001, 32.311),\n",
       " 'JAX': (-81.688, 30.494),\n",
       " 'JBR': (-90.646, 35.832),\n",
       " 'JFK': (-73.779, 40.64),\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",
       " 'LIT': (-92.22399999999999, 34.729),\n",
       " 'LNK': (-96.759, 40.851),\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",
       " 'MAF': (-102.20200000000001, 31.941999999999997),\n",
       " 'MCC': (-121.40100000000001, 38.667),\n",
       " 'MCF': (-82.521, 27.849),\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",
       " '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",
       " 'MSN': (-89.337, 43.14),\n",
       " 'MSP': (-93.21700000000001, 44.88),\n",
       " 'MSS': (-74.845, 44.93600000000001),\n",
       " 'MSY': (-90.258, 29.993000000000002),\n",
       " 'MWH': (-119.32, 47.208),\n",
       " 'MXF': (-86.36200000000001, 32.379),\n",
       " 'MYR': (-78.928, 33.68),\n",
       " 'ABY': (0.0, 0.0),\n",
       " 'NBG': (-90.035, 29.825),\n",
       " 'BQK': (0.0, 0.0),\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",
       " 'SFB': (0.0, 0.0),\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",
       " 'OGS': (-75.46600000000001, 44.681999999999995),\n",
       " 'OKC': (-97.601, 35.393),\n",
       " 'OMA': (-95.89399999999999, 41.302),\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",
       " 'PAE': (-122.281, 47.906000000000006),\n",
       " 'PAM': (-85.57600000000001, 30.07),\n",
       " 'PBG': (-73.468, 44.651),\n",
       " 'PBI': (-80.096, 26.683000000000003),\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",
       " 'PNE': (-75.01100000000001, 40.082),\n",
       " 'PNS': (-87.18700000000001, 30.473000000000003),\n",
       " 'POB': (-79.014, 35.171),\n",
       " 'PQI': (-68.045, 46.68899999999999),\n",
       " 'PRC': (-112.419, 34.654),\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",
       " '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",
       " 'SCK': (-121.23899999999999, 37.894),\n",
       " 'SEA': (-122.309, 47.449),\n",
       " 'SFO': (-122.375, 37.619),\n",
       " 'SFZ': (-71.491, 41.92100000000001),\n",
       " 'SHV': (-93.82600000000001, 32.446),\n",
       " 'SJC': (-121.929, 37.361999999999995),\n",
       " 'SJT': (-100.49600000000001, 31.358),\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",
       " 'SPB': (-122.86200000000001, 45.773),\n",
       " 'SPS': (-98.492, 33.989000000000004),\n",
       " 'SSC': (-80.473, 33.973),\n",
       " 'STL': (-90.36, 38.748000000000005),\n",
       " 'SUU': (-121.927, 38.263000000000005),\n",
       " 'SUX': (-96.384, 42.402),\n",
       " 'SVN': (-81.146, 32.01),\n",
       " 'SWF': (-74.105, 41.504),\n",
       " 'SYR': (-76.10600000000001, 43.111000000000004),\n",
       " 'SZL': (-93.54799999999999, 38.73),\n",
       " 'TBN': (-92.141, 37.741),\n",
       " 'TEB': (-74.061, 40.85),\n",
       " 'TIK': (-97.38600000000001, 35.415),\n",
       " 'TLH': (-84.35, 30.396),\n",
       " 'TMB': (-80.433, 25.648000000000003),\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",
       " 'VAD': (-83.193, 30.968000000000004),\n",
       " 'VCV': (-117.37899999999999, 34.593),\n",
       " 'VPS': (-86.525, 30.483),\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",
       " 'YIP': (-83.53, 42.238),\n",
       " 'YNG': (-80.679, 41.261),\n",
       " 'YUM': (-114.60600000000001, 32.656),\n",
       " 'PCA': (-98.78200000000001, 20.077),\n",
       " 'PPG': (-170.71, -14.331),\n",
       " 'TKF': (0.0, 0.0),\n",
       " 'PAQ': (-149.089, 61.595),\n",
       " 'BTI': (-143.577, 70.134),\n",
       " 'BET': (-161.838, 60.78),\n",
       " 'BRW': (-156.766, 71.285),\n",
       " 'BTT': (-151.528, 66.915),\n",
       " 'CDB': (-162.724, 55.206),\n",
       " 'CDV': (-145.477, 60.492),\n",
       " 'ADK': (-176.646, 51.878),\n",
       " 'DLG': (-158.503, 59.045),\n",
       " 'ADQ': (-152.494, 57.75),\n",
       " 'DUT': (-166.543, 53.9),\n",
       " 'EDF': (-149.806, 61.251000000000005),\n",
       " 'EHM': (-162.061, 58.647),\n",
       " 'EIL': (-147.101, 64.666),\n",
       " 'ENA': (-151.245, 60.573),\n",
       " 'FAI': (-147.856, 64.815),\n",
       " 'FBK': (-147.614, 64.837),\n",
       " 'GAL': (-156.937, 64.736),\n",
       " 'GKN': (-145.45600000000002, 62.155),\n",
       " 'SGY': (-135.316, 59.46),\n",
       " 'HOM': (-151.476, 59.646),\n",
       " 'ILI': (-154.911, 59.754),\n",
       " 'UTO': (-153.704, 65.993),\n",
       " 'JNU': (-134.576, 58.355),\n",
       " 'AKN': (-156.649, 58.677),\n",
       " 'KTN': (-131.714, 55.356),\n",
       " 'LUR': (-166.11, 68.875),\n",
       " 'MCG': (-155.606, 62.953),\n",
       " 'MRI': (-149.846, 61.214),\n",
       " 'ANC': (-149.996, 61.174),\n",
       " 'OME': (-165.445, 64.512),\n",
       " 'ORT': (-141.929, 62.961000000000006),\n",
       " 'OTZ': (-162.59799999999998, 66.884),\n",
       " 'PML': (-161.819, 59.011),\n",
       " 'SCC': (-148.465, 70.195),\n",
       " 'SIT': (-135.361, 57.047),\n",
       " 'SNP': (-170.22, 57.167),\n",
       " 'SVW': (-155.57399999999998, 61.097),\n",
       " 'SYA': (174.114, 52.711999999999996),\n",
       " 'TAL': (-152.109, 65.17399999999999),\n",
       " 'TNC': (-167.922, 65.563),\n",
       " 'TKA': (-150.094, 62.32),\n",
       " 'TLJ': (-155.976, 62.894),\n",
       " 'UNK': (-160.799, 63.888000000000005),\n",
       " 'VDZ': (-146.248, 61.13399999999999),\n",
       " 'AIN': (-159.86, 70.613),\n",
       " 'YAK': (-139.66, 59.503),\n",
       " 'FYU': (-145.25, 66.571),\n",
       " 'ROP': (145.243, 14.174000000000001),\n",
       " 'SPN': (145.72899999999998, 15.119000000000002),\n",
       " 'UAM': (144.93, 13.584000000000001),\n",
       " 'GUM': (144.797, 13.484000000000002),\n",
       " 'HNM': (-156.014, 20.796),\n",
       " 'JHM': (-156.674, 20.963),\n",
       " 'KOA': (-156.046, 19.739),\n",
       " 'LIH': (-159.339, 21.976),\n",
       " 'MKK': (-157.096, 21.153000000000002),\n",
       " 'MUE': (-155.668, 20.000999999999998),\n",
       " 'NGF': (-157.768, 21.449),\n",
       " 'HNL': (-157.92700000000002, 21.316),\n",
       " 'LNY': (-156.951, 20.785999999999998),\n",
       " 'OGG': (-156.431, 20.899),\n",
       " 'ITO': (-155.049, 19.72),\n",
       " 'PIZ': (-163.005, 69.733),\n",
       " 'STT': (-64.973, 18.337),\n",
       " 'STX': (-64.798, 17.702),\n",
       " 'BQN': (-67.12899999999999, 18.495),\n",
       " 'VQS': (0.0, 0.0),\n",
       " 'CPX': (0.0, 0.0),\n",
       " 'SIG': (-66.098, 18.457),\n",
       " 'MAZ': (-67.148, 18.256),\n",
       " 'PSE': (-66.563, 18.008),\n",
       " 'SJU': (-66.002, 18.439)}"
      ]
     },
     "execution_count": 20,
     "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": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x648 with 1 Axes>"
      ]
     },
     "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": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x117b6d470>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x648 with 1 Axes>"
      ]
     },
     "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": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "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": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "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": 25,
   "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": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "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": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "InDegreeView({1: 0, 2: 6, 3: 0, 4: 0, 5: 0, 6: 0, 7: 0})"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.in_degree()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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": 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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bjY4cOUJYWBjLli2jd+/eTJkyJcsvFX/99dcsW7aMLVu25Ni90XXr1qV///74+fmxbt06DUHYKZWwSBa6slG7raKNjY2laNGi14zTNm7cGG9vbypWrEj+/PnNjp+rnDx5kvDwcObNm0fXrl3Zu3dvtqzUdfjwYbp06cLy5ctzfCWw999/nzVr1jB06FA+/PDDHH1vuT0qYZG7cOnSpUzvpzUM45qifeONNzJu8ylYsKDZ0XO9M2fOMGbMGD799FMCAgIydjbKDqmpqfj7+/Pee+9Rr169bHmPm8mTJw9z5syhZs2aPPPMM7z44os5nkFuTiUskonLly9z4MABm0V75swZPD09M4r2ueeeo3v37hnjtI6+HKMzOn/+PB999BEff/wxrVq1YuvWrZQrVy5b3zM4OJj77ruPAQMGZOv73IyHhwfz58+nTZs2bN68mQcffNC0LHIjlbDkaunp6Rw7dsxm0R45coSyZctmFG2NGjV4/fXX8fb2pmzZshqndRAJCQlMnTqVMWPG8MILL7Bx40Y8PT2z/X1/+OEHZs+ezZYtW0z/u9KoUSN69OhB27ZtWbVqFS4uLqbmkX+phCVXuNk4beHCha+5fPzss8/i7e1NpUqVNE7rwFJSUpgxYwYjR47kqaeeYs2aNVSrVi1H3vvEiRN07NiR+fPnU6JEiRx5z1sZMmQIa9euZfjw4QQHB5sdR/6hEhancenSJWJjY22WbWpq6jX307722msZ47SFChUyO7pkodTUVObNm0dISAhVq1bl66+/ztb7cq+XlpZG27Zt6dKlC88991yOve+tuLi4sGDBAmrVqkWjRo145plnzI4kqITFwVy+fJmDBw/aLNq///6bypUrZxRto0aN6NKlC97e3nh4eGic1smlp6ezZMkSgoODKV26NAsWLKB+/fo5niM8PJy0tDSCgoJy/L1vpXTp0nz++ee0a9eOLVu24OHhYXakXE8lLHbHMAyOHz9us2gPHTrEgw8+mFG01apVo2XLlnh7e1OuXDmNdeVChmHw9ddfM3ToUNzc3JgyZQqNGzc25Zeun3/+mcmTJ7N582a7/bvYtGlTAgICaN++Pf/73/9MH6/O7VTCYpozZ87csAzjlT8XLFjwmnHahg0bZozTurq6mh1d7IBhGKxatYrAwECSkpIYPnw4L7/8smlXPP7++2/atm3LZ599RpkyZUzJcLtCQ0N55plnGDduHP379zc7Tq6mEpZslZCQkOk4bUpKSsY4rZeXF6+++mrGnwsXLmx2dLFjv/76K0OGDOHEiROEhobyxhtvmHpGl56eTseOHfHz86N58+am5bhd+fLlY9GiRfj4+NCgQQOeeuopsyPlWiphuWepqamZjtOeOnWKSpUqXXNG27lzZ7y9vSlRooTGaeWObNq0iaFDh7Jnzx6Cg4Np167dPe9slBUmTJjA33//zYgRI8yOctvKly/PjBkz8PPzY8uWLRQtWtTsSLmS+X97xSEYhsFff/1ls2gPHjxI6dKlM4r2kUceyTirLV++vN2OjYnj2LFjB0FBQfz+++8MGTKEr776ym5uH/v9998ZNWoUf/zxh8Otz/zKK6+wZs0aOnfuzNKlS/VLsQlUwnKNs2fP2izamJgY3N3drxmnrV+/Pt7e3lSuXFnjtJItYmNjCQ4OZtWqVQwYMIAFCxbg5uZmdqwMZ8+exc/Pj+nTp/PQQw+ZHeeujBo1ivr16zNlyhTeeecds+PkOirh2xEXB7Nnw7ZtcO4cFC4MNWpAp07ggFP8ExMT2bdvn82yTUxMvKZoX3755Yxx2iJFipgdXXKJw4cPExYWxvLly+nTpw/Tp0+3u/u5DcPgrbfeonnz5rRq1crsOHetQIECLF68mLp161KvXj1q1qxpdqRcRSV8M5GREB4O335r/Twp6d/Hli2D4GBo1gwGDQIfH3MyZiI1NZVDhw7ZPKM9ceIEFStWzCjap556ig4dOuDt7U2pUqV0SUpMc+LECUaOHMmCBQvo1q1btu1slBWmTZvGvn37mD9/vtlR7lnlypWZNGkSvr6+REVF2d0vPM5MJZyZadOgXz9ITATDuPHxxETrf1esgO+/h7FjoUePHI1oGAYnTpyweUZ74MABSpYsec1ZbYsWLfD29qZChQp2MZlF5IrTp08zevRoZsyYQYcOHdi1axclS5Y0O1amtm7dSnBwMOvXr3eaoZg2bdrw008/0a1bNxYsWKBfxnOI/iW25UoBJyTc+ljDsB7Xr5/182wo4rNnz2a6bZ6rq+s1Rdu+fXu8vb3x9PS0q7EzEVvOnz/PhAkTmDRpEq+99hp//vlntu9sdK8uXLiAr68vH330Ed7e3mbHyVIfffQRderU4bPPPqNz585mx8kVVMLXi4y8aQHHANWB14FrLkJdKWIfH6hd+47fNikpKdNx2kuXLl1TtM2bN6dPnz54eXnZ7aU6kZtJSEhg8uTJjB07lhdffJHff/+dypUrmx3rlgzD4O2336ZBgwa0bdvW7DhZzs3NjcWLF9OoUSPq1q2bYxte5GYq4euFh/97qdmGnkCmo7+JidbnL11q8+G0tDQOHz5ss2j/+usvHnrooYyiffLJJwkICMDb25vSpUvr0pA4heTk5IydjerXr8/atWupWrWq2bFu25w5c4iKiuKPP/4wO0q2qVq1KmPGjKF169ZERkbi7u5udiSnphK+WlycdRKWrTFgIAIoAtQDYm0dYBgYK1cSt2MHe+Pjbyja/fv34+Hhcc1ZbbNmzfD29uahhx7SOK04rdTUVObMmUNoaCiPPvoo33zzjcPNwt21axf9+/dn7dq13HfffWbHyVYdOnRg9erV9O7dm5kzZ5odx6npX/2rzZ6d6UPngSBgDXCzv5KJSUlMrVOHHx9/PKNo27ZtmzFOq98qJTdJT09n8eLFBAcHU7ZsWRYtWkS9evXMjnXHEhMT8fX1JTw8PFdcorVYLEydOpXatWuzcOFC/P39zY7ktFTCV9u27drbkK4yFOgMlL3FS7gDIa+/TsjcuVkcTsRxGIbBV199xdChQ7nvvvuYNm0ajRs3NjvWXevTpw/Vq1fPVZOVChUqxOLFi3n++efx8fHBy8vL7EhOSSV8tXPnbH55K7AK2HK7rxMfn0WBRByLYRj88MMPBAYGcvnyZcLDw3nppZccek5DREQEa9asYfPmzQ79fdyNxx9/nJCQEHx9fdmwYQMFChQwO5LT0UaSV8tk5561wEGgPFAKGAssBTId0dJC6JIL/fLLLzRq1Ih3332X/v37ExUVRYsWLRy6uGJjY+nVqxeLFy/m/vvvNzuOKXr06EGlSpW05WE2UQlfrUYNsHHjfVdgH9Yz4q1Ad+Al4Htbr+HmBtWrZ2NIEfsSGRlJ06ZNad++PZ07d2bHjh20bt3a4TeLT05Opk2bNgQFBTncJLKsZLFYmDlzJt988w3Lly83O47TceyfkqzWsaPNL7tjPQO+8lEQcAVsrhptGJm+jogz2b59Oy1btqRly5b85z//ITo6mg4dOjjNLP8PPviAcuXKaVMDoEiRIkRERNC9e3cOHjxodhynohK+WokS1rWgb3H5bBjXLdRxhcUCzZs75KYOIrcrJiYGf39/mjRpQsOGDYmJiaFHjx52s7VgVvjqq69YsWIFn332mUNfTs9KderUYcCAAfj5+XH58mWz4zgNlfD1Bg2yXlK+G25u1ueLOKFDhw7RuXNnnnrqKapVq0ZsbCzvv/++0y2PevjwYbp27cqiRYu00f113nvvPYoXL05gYKDZUZyGSvh6Pj7WzRju9H5ed3fr8+5iyUoRe/bXX3/Rq1cvatasSenSpYmJiWHIkCFOudPO5cuX8fPzo2/fvjz11FNmx7E7efLkYfbs2SxatIhvr+wuJ/dEJWxLjx7/FvGtLkVZLP8WcA7voiSSnU6fPs2AAQOoVq0a+fLlY/fu3QwfPtypzw6DgoIoVKgQ/a5syCI3eOCBB1iwYAFvvvkmx48fNzuOw1MJZ6ZHD1i3Dlq2tM6Yvv6Sm5ub9estW1qPUwGLkzh37hzBwcF4e3tz4cIFtm/fzvjx4ylRooTZ0bLV999/z7x585g7d67Dz+zObg0bNqRnz574+/uTlpZmdhyH5hzTGLNL7drWzRhOnbIuabl9u3UhjqJFrbchdeyoSVjiNC5dusTkyZMZN24czZs3JzIykkqVKpkdK0f89ddfdOzYkUWLFjn9LxtZZdCgQaxdu5awsDCGDRtmdhyHpRK+HR4eoBvVxUklJyfzySefEB4eTsOGDVm3bh2PPPKI2bFyTFpaGm3btqVbt24888wzZsdxGC4uLsyfP5+aNWvSqFEjnn32WbMjOSRdcxHJpS5fvszMmTPx8vLihx9+YOXKlSxZsiRXFTDAyJEjMQyDoUOHmh3F4ZQqVYo5c+YQEBBAXFyc2XEcks6ERXKZtLQ0IiIiGDZsGOXLl2fx4sW5dibwunXrmDp1Kps3b8bFxcXsOA7p+eefp0OHDrRv356VK1dqPP0O6f+WSC5hGAbLli3jscceY/LkyXzyySesXr061xbwqVOnaNeuHZ9//jkPPvig2XEcWkhICBcvXmTs2LFmR3E4OhMWcXKGYfD9998TGBhIWloao0aNonnz5rl6Jaj09HQ6dOiAv78/L774otlxHF7evHlZtGgRtWvXpkGDBg65Z7RZVMIiTmzdunUEBgZy+vRpQkNDadWqlS4XAuPHjyc+Pp7hw4ebHcVplCtXjpkzZ+Lv709UVBTFihUzO5JD0E+jiBP6448/eOGFF+jUqRNdunRh+/btvP766ypgYOPGjYwePZqIiAjy5ctndhyn8vLLL9OyZUs6d+6MYRhmx3EI+okUcSLbtm3j1Vdf5bXXXuO1114jOjqa9u3ba9LRP+Lj4/Hz8+OTTz6hQoUKZsdxSqNGjeLo0aNMnjzZ7CgOQSUs4gSio6Np06YNL7zwAs8++ywxMTF069ZNZ3pXMQyDt956K+NsTbJH/vz5iYiIICwsjKioKLPj2D2VsIgDO3jwIG+++SYNGjSgRo0axMbG0qdPH1xdXc2OZnemTp3KwYMHGTNmjNlRnF7lypWZPHkyvr6+nD9/3uw4dk0lLOKAjh8/Ts+ePalVqxZlypQhJiaGwYMHU7BgQbOj2aUtW7YwbNgwIiIiKFCggNlxcoXWrVvTuHFjunXrpvHhm1AJiziQv//+m379+vHoo4/i6urKnj17CAsLo0iRImZHs1sXLlzA19eXjz/+GC8vL7Pj5CoTJkxg586dzJo1y+wodkslLOIAzp49S1BQEA8//DAJCQls376dcePG4aENRG7KMAy6d+9Oo0aN8PPzMztOruPm5saSJUsYNGgQO3bsMDuOXVIJi9ixS5cuER4ejpeXF0eOHGHTpk1MnTqVMmXKmB3NIXz++ef8+eefTJw40ewouVaVKlUYO3Ysvr6+XLp0yew4dkclLGKHkpKSmDhxIp6enmzdupVffvmFzz//nIoVK5odzWHs2rWLDz74gMWLF+Pu7m52nFytQ4cO1K5dm969e5sdxe6ohEXsyOXLl/n000/x8vJi9erVfPfddyxevJgqVaqYHc2hJCQk0Lp1a0aNGkW1atXMjiPAlClTWL9+PQsWLDA7il3RspUidiAtLY2FCxcybNgwKlWqxBdffEHdunXNjuWw3n33XR577DE6depkdhT5R8GCBVmyZAmNGzfGx8cHb29vsyPZBZWwiInS09NZvnw5QUFBFClShFmzZmlj+Xu0aNEi1q1bx+bNm3P1JhX2qEaNGoSFheHr68uGDRt0Pzu6HC1iCsMwWLlyJbVr12bEiBGMGTOGX3/9VQV8j2JiYujduzeLFy+mUKFCZscRG7p164aXlxf9+vUzO4pd0JmwSA776aefCAwMJD4+nrCwMFq2bKmNFbJAcnIybdq0ITg4mCeeeMLsOJIJi8XCjBkzqFmzJsuWLaNVq1ZmRzKVSlgkh2zcuJHAwEAOHDjAsGHD8Pf318YKWWjAgAFUqFCBnj17mh1FbqFw4cJERETw0ksv8cQTT+TqWf/69Vskm23dupWXX36ZN954g9atW7Nnzx4CAgJUwFloxYoVfP3118yaNUvjwA7Cx8eHQYMG4efnx+UNClNBAAAgAElEQVTLl82OYxqVsEg22bNnD76+vrz44os0adKEmJgYunbtqp2NstihQ4fo2rUrixYtomjRombHkTvQp08fPDw8GDJkiNlRTKMSFsliBw4coGPHjjRs2JDHH3+c2NhY3n33Xc0EzQaXL1/Gz8+P/v3765YuB2SxWJg9ezYRERGsXLnS7DimUAmLZJFjx47Ro0cPateuTfny5YmJiWHQoEHa2SgbDR06lCJFitC3b1+zo8hdKl68OAsXLuTNN9/k2LFjZsfJcSphkXt06tQp+vbtS/Xq1SlYsCB79uwhNDRUOxtls++++4758+czZ84czS53cA0aNKBXr174+/uTmppqdpwcpb+5Infp7NmzBAYGUqVKFZKSktixYwdjxozRzkY54Pjx43Tq1IkFCxbo/7eTGDhwIPnz5ycsLMzsKDlKJSxyhy5evMjIkSPx8vLi+PHjbN68mSlTpvDggw+aHS1XSEtLo23btvTo0YNGjRqZHUeyiIuLC/PmzWPmzJmsWbPG7Dg5RiUscpuSkpKYMGECnp6ebNu2jV9//ZXPPvuMhx56yOxoucrw4cOxWCy5ekatsypVqhRz5swhICCAuLg4s+PkCJWwyC2kpKTwySef4OXlxdq1a/nhhx+IiIjg4YcfNjtarrN27VqmT5/OggULdJ+1k2rSpAmdOnUiICCA9PR0s+NkO5WwSCbS0tKYO3cuVapUYenSpXz55Zd89dVX1KhRw+xoudKpU6do164ds2fPpnTp0mbHkWw0bNgwEhISGD16tNlRsp2WrRS5Tnp6OkuXLiUoKIjixYvz+eefa+zRZOnp6bRv356AgACaNm1qdhzJZnnz5mXRokXUrl2bp59+mnr16pkdKduohEX+cWVno8DAQFxcXJgwYQJNmzbVMoh2YNy4cZw7d47Q0FCzo0gOKVu2LDNmzMDPz48tW7ZQrFgxsyNlC5WwCLBmzRoCAwM5d+5cxs5GKl/7sGHDBsaOHcsff/yhJT9zmZdffpm1a9fSqVMnVqxY4ZQ/kyphydU2bNhAYGAghw4dIiQkhDZt2mjCjx2Jj4/Hz8+PTz/9lAoVKpgdR0wQHh5OgwYNmDRpEr1797Z+MS4OZs+Gbdvg3DkoXBhq1IBOncDB7htXCUuutHXrVgIDA9m2bRtBQUF06NBBZ1l2xjAMOnfuzKuvvsqrr75qdhwxSf78+YmIiKBu3bo0KVyYql99Bd9+a30wKenfA5ctg+BgaNYMBg0CHx9zAt8hzY6WXGX37t20bt2aZs2a8cILL7B3717eeustFbAdmjJlCocOHcoVM2Tl5ipVqsS3r75KxU6dMFassJbv1QUMkJho/dqKFfDMMzBtmilZ75RKWHKF/fv306FDBxo1akStWrWIjY2ld+/e2tnITkVFRRESEsLixYspUKCA2XHEbNOmUWvhQtwMA4th3PxYw4CEBOjXzyGKWCUsTu3o0aN0794dHx8fKlasSExMDB988AH33Xef2dEkExcuXMDX15dJkybh6elpdhwxW2SktVATEjK+NBmoDRQAOmb2vCtFvGlTtke8FyphcUpxcXG8//771KhRg/vvv5/o6GiGDRtG4cKFzY4mN2EYBt26dePZZ5+lTZs2ZscRexAebr3UfJUHgUDgzVs9NzHR+nw7polZ4lTi4+MZO3Ys06dPx9/fn507d2p1JQfy2WefsX37dn7//Xezo4g9iIuzTsK67hJ0q3/+uwk4erPnGwasXAmnTtntrGmdCYtTuHDhAsOHD8fLy4sTJ04QFRXFpEmTVMAOZOfOnQwcOJDFixfj7u5udhyxB7Nn3/trWCxZ8zrZRCUsDi0xMZHx48fj6enJrl27+O2335g1a5buKXUwCQkJtG7dmtGjR1O1alWz44i92LbtxlnQdyoxEbZvz5o82UCXo8UhpaSkMGvWLEaMGEHt2rVZtWoV1atXNzuW3KXevXtTs2ZNOnbsaHYUsSfnzmXN68THZ83rZAOVsDiU1NRU5s+fT0hICN7e3ixfvhwfB7kpX2xbuHAhP//8M5s3b3bKZQnlHmTVRMqiRbPmdbKBSlgcQnp6Ol9++SVBQUF4eHgwZ84cnn76abNjyT2KiYnh3Xff5ccff6RQoUJmxxF7U6MGLF16wyXp1H8+0v75SMJaZjYLzc0N7PgqmcaExa4ZhsE333xDzZo1GTNmDBMnTuTnn39WATuBpKQkWrduTUhICI8//rjZccQeZTI8MRxwAz4E5v/z5+GZvYZhZPo69kBnwmK3Vq9eTWBgIBcvXiQsLIxXX31VlyudSP/+/alcuTI9evQwO4rYqxIlrGtBr1hxzW1Kw/75uCWLBZo3t9vbk0AlLHbot99+IzAwkKNHjxISEkLr1q21s5GTWb58Od988w1btmzRL1Zyc4MGwfffX7Ni1m1zc7M+347pcrTYjaioKF566SX8/Pxo27Ytu3btws/PTwXsZA4ePEi3bt2IiIigSJEiZscRe+fjA2PHwp3eO+7ubn1e7drZkyuLqITFdLt27eL111+nRYsWNGvWjL1799K5c2fy5tWFGmdz+fJl/Pz8+OCDD3jyySfNjiOOokePf4v4VldOLJZ/C9gBhjpUwmKaffv2ERAQwDPPPMOTTz5JbGws77zzjnbNcWKBgYEUK1aM9957z+wo4mh69IB166BlS3B1tV5qvpqbm/XrLVtaj3OAAgaNCYsJjhw5wvDhw1m6dCm9evViypQp3H///WbHkmz27bffsnDhQrZs2UKePPr9X+5C7drWW5ZOnbIuRbl9u3UhjqJFrbchdexo15OwbFEJS445efIk4eHhzJ07l65duxIdHU3x4sXNjiU54NixY3Tq1IklS5bwwAMPmB1HHJ2HB/Tvb3aKLKFfRyXbxcfHM3jwYKpWrUp6ejq7du3iww8/VAHnEmlpabRt25aePXvq/m6R66iEJdtcuHCBsLAwvLy8OHXqFFu2bOHjjz+mVKlSZkeTHBQWFoaLiwuDBw82O4qI3dHlaMlyiYmJTJ06ldGjR9OkSRM2bNiAl5eX2bHEBD/99BOffvopmzdv1q1mIjaohCXLpKSkMHPmTEaMGMGTTz7J6tWrefTRR82OJSaJi4sjICCA2bNna19nkUyohOWepaamMm/ePEJDQ6lSpQpfffUVte38BnnJXunp6bRv356AgABeeOEFs+OI2C2VsNy19PR0vvjiC4KDgylZsiRz586lYcOGZscSOzBmzJiMNb9FJHMqYbljhmHw3//+l6FDh1KgQAEmTZpEkyZNtAawANa1v8ePH09kZKRWPRO5Bf2EyG0zDINVq1YRGBhIYmIiYWFhvPLKKypfyXDmzBn8/PyYMWMG5cuXNzuOiN1TCcttWb9+PUOGDOGvv/7K2NlIqx7J1QzDoHPnzrRq1YpXXnnF7DgiDkElLDe1efNmAgMD2b17N8HBwQQEBOgSo9g0efJkjhw5QkREhNlRRByG/jUVm3bu3ElQUBAbN25k8ODBrFixQhsrSKY2b95MWFgYGzZs0N8TkTug64lyjdjYWNq1a8dzzz3HU089RUxMDD179tQ/rJKp8+fP4+vry+TJk6lcubLZcUQcikpYAOvORl27dqVu3bp4e3sTExNDv379cL/TjbQlVzEMg27dutG4cWNat25tdhwRh6PL0bncyZMnGTlyJPPnz6dr167s3buXYsWKmR1LHMSsWbPYsWMHf/zxh9lRRBySzoRzqTNnzjBw4EAeeeQRLBYLO3fuJDw8XAUst23Hjh0MGjSIJUuW4Hb9BusicltUwrnM+fPnCQ0NxdvbmzNnzvDnn3/y0UcfaWcjuSOXLl3C19eXMWPG8Mgjj5gdR8RhqYRziYSEBMaMGYOnpycxMTFs3LiRTz/9lHLlypkdTRxQ7969qVWrFh06dDA7iohD05iwk0tOTmbGjBmMHDmSevXq8dNPP1GtWjWzY4kDW7BgAb/++iubN2/Wamki90gl7KRSU1OZO3cuoaGhVK1alf/+97/UqlXL7Fji4Pbu3UufPn1YtWoVBQsWNDuOiMNTCTuZ9PR0Fi9eTHBwMGXKlGHBggXUr1/f7FjiBJKSkvD19SU0NJTHHnvM7DgiTkEl7CQMw+Drr79m6NChuLm5MXXqVBo3bqzLhZJl+vXrh6enJ927dzc7iojTUAk7OMMw+PHHHwkMDCQ5OZkRI0bQokULla9kqWXLlrFy5UqioqL0d0skC6mEHdivv/7KkCFDOHnyJKGhobz++uva2Uiy3IEDB+jevTvffPMNRYoUMTuOiFNRCTugTZs2ERgYSHR0NMHBwbRr1047G0m2uHz5Mn5+fgwcOJA6deqYHUfE6ei0yYHs2LGDVq1a8Z///IdXX32V6OhoOnbsqAKWbDNkyBA8PDx47733zI4i4pRUwg4gJiaGtm3b0rhxY+rXr09MTAw9evQgf/78ZkcTJ7Zy5UoWLVrE559/rnFgkWyiErZjhw8f5q233uKpp57ikUceITY2lr59+2qdXsl2x44d480332ThwoU88MADZscRcVoqYTt04sQJevfuzRNPPEGJEiXYu3cvgYGBFCpUyOxokgukpqbi7+9Pr169aNiwodlxRJyaStiOnD59mg8++ICqVavi4uLC7t27GTlypHY2khwVFhZGvnz5GDhwoNlRRJyeZvTYgfPnzzN+/HgmTZrEG2+8wbZt2yhbtqzZsSQXWrNmDTNmzCAqKgoXFxez44g4PZ0JmyghIYHRo0fj6enJ/v37+eOPP5g+fboKWExx8uRJAgICmDt3rra2FMkhOhM2QXJyMp9++inh4eHUr1+ftWvXUrVqVbNjSS6Wnp5O+/bt6dixI02aNDE7jkiuoRLOQampqcyZM4fQ0FCqV6/O//73P5544gmzY4kwevRoLl26REhIiNlRRHIVlfDtiIuD2bNh2zY4dw4KF4YaNaBTJ/DwuOXT09PTiYiIIDg4mHLlyrFo0SLq1auX/blFbsP69euZMGECmzZt0sIvIjlMP3E3ExkJ4eHw7bfWz5OS/n1s2TIIDoZmzWDQIPDxueHphmGwYsUKgoKCKFiwIJ988gnPPfdcDoUXubUzZ87g7+/PzJkzKVeunNlxRHIdlXBmpk2Dfv0gMREM48bHExOt/12xAr7/HsaOhR49AGv5/vDDDwQGBpKamsqHH35I8+bNteqQ2BXDMOjUqROvvfYaL7/8stlxRHIllbAtVwo4IeHWxxqG9bh+/QD4uVo1AgMDOXXqFKGhobz22mva2Ujs0scff8zx48f54osvzI4ikmuphK8XGWmzgJ8BNvLv/7AyQPTVByQkkPTOO4wrVYq3wsNp27at7rMUu7Vp0yZGjBjBxo0btQa5iIlUwtcLD//3UvN1JgNv3eSp+Q2DZXXq4NK+fbZEE8kK586do02bNkyePJlKlSqZHUckV9N10qvFxVknYdkaA74NeQwDl+++g1OnsjiYSNYwDINu3brx/PPP07p1a7PjiOR6KuGrzZ5904cHAQ8A9YG1mR1ksdzydUTMMnPmTHbv3s348ePNjiIi6HL0tbZtu/Y2pKuMAqoC+YEI4GVgK1D5+gMTE2H79mwMKXJ3tm/fzuDBg/nll1+0HaaIndCZ8NXOncv0oSeBQkABoAPWs+GVmR0cH5/VyUTuyaVLl2jdujXjxo2jSpUqZscRkX+ohK9WuPBtH2oBMh05Llo0K9KIZJlevXpRp04d2mvSoIhdUQlfrUYNcHW94ctnge+BJCAVWAD8DLxo6zXc3KB69WwMKXJn5s2bx2+//caUKVPMjiIi11EJX61jR5tfvgwEAh5YJ2ZNAlYA3jaOTU1NJS0gIJsCityZ6Oho3n//fZYsWULBggXNjiMi11EJX61ECeta0NctL+kBRAIXsJ4VbwSet/F0w2Lh10KFqP7cc3z55Zekp6dne2SRzCQlJeHr60tYWBg1atQwO46I2KASvt6gQdZLynfB4uZGo+++Y/z48Xz44YfUrl2blStXYtzlfcci96Jv3754e3vTrVs3s6OISCZUwtfz8bFuxuDufmfPc3eHsWOx+Pjw4osvEhkZSWBgIP3796dBgwb89NNP2ZNXxIalS5fy3XffMWPGDG0cImLHVMK29OjxbxHf6h8wiyWjgK/somT9soVWrVqxbds23n77bbp06UKTJk3YuHFjNoeX3O7AgQP06NGDiIgICt/BjH8RyXkq4cz06AHr1kHLltYZ09dfonZzs369ZUvrcVcV8NVcXFxo27Ytu3fvxtfXl9atW/Pyyy+zdevWHPgmJLdJSUmhTZs2DBo0CB8be1yLiH3Rilk3U7s2LF1qXQt69mzrSljx8db7gKtXt86m9vC4rZfKly8fXbp0ISAggE8//ZRmzZrx9NNPExISosUTJMsMHjyYEiVK0KdPH7OjiMhtUAnfDg8P6N8/S17K1dWV3r1707lzZyZNmkTDhg156aWXCA4OpmLFilnyHpI7/e9//2PJkiVs2bJF48AiDkKXo01y3333MXDgQGJjY6lQoQK1a9emR48eHDt2zOxo4oCOHj1K586dWbhwIcWLFzc7jojcJpWwyQoXLkxISAjR0dEUKlSIGjVq0LdvX05pO0S5Tampqfj7+9O7d28aNGhgdhwRuQMqYTvxwAMPMHr0aHbs2EFycjJVqlQhMDCQs2fPmh1N7FxoaCgFChRg4MCBZkcRkTukErYzpUuXZvLkyURFRfHXX3/h5eXFiBEjuHjxotnRxA6tXr2amTNnMm/ePPLk0Y+ziKPRT62dqlChArNmzWL9+vXs3LkTT09PJkyYQGJiotnRxE6cPHmS9u3bM3fuXEqVKmV2HBG5CyphO+ft7c3ChQv58ccfWbduHV5eXkyfPp2UlBSzo4mJ0tPTCQgIoFOnTjRp0sTsOCJyl1TCDqJ69eqsWLGC5cuXs3z5cqpUqcKcOXNIS0szO5qYYNSoUSQmJjJs2DCzo4jIPVAJOxgfHx++//57Zs+ezcyZM3n00Uf54osvtGNTLrJ+/XomTpzIokWLyJtXt/qLODKVsIN6+umn+fnnn/noo48YNWoUtWrV4ptvvtGOTU7u9OnT+Pv7M3PmTMqWLWt2HBG5RyphB2axWGjatCmRkZEEBQUxcOBA6tWrx5o1a8yOJtnAMAw6derE66+/TosWLcyOIyJZQCXsBCwWCy1btuTPP/+kV69edOvWjcaNG7Nhwwazo0kWmjhxIidOnCA8PNzsKCKSRVTCTsTFxQV/f3927dqFv78/bdq0oUWLFmzZssXsaHKPNm3axMiRI4mIiCB//vxmxxGRLKISdkL58uWjc+fO7N27l6ZNm/LSSy/xxhtvsHv3brOjyV04d+4cvr6+TJkyhUqVKpkdR0SykErYiRUoUIBevXoRGxuLj48PjRo1okOHDuzfv9/saHKbDMOga9euNG3alDfeeMPsOCKSxVTCuYC7uzsDBgwgJiaGSpUqUadOHbp3787Ro0fNjia3MGPGDPbs2cP48ePNjiIi2UAlnIsULlyY4OBgoqOjKVy4MI899hjvvfcecXFxZkcTG7Zt28aQIUNYsmQJrq6uZscRkWygEs6FihcvzqhRo9i5cydpaWk88sgjDBkyhPj4eLOjyT8uXbqEr68v48eP5+GHHzY7johkE5VwLlaqVCk+/vhjoqKiOHnyJF5eXgwfPpwLFy6YHS3Xe+edd6hbty4BAQFmRxGRbKQSFipUqMDMmTPZsGEDu3fvxtPTk3HjxmnHJpPMnTuXjRs3MnnyZLOjiEg2UwlLBi8vLxYsWMCqVatYv349np6eTJ06VTs25aA9e/bQt29fFi9ezH333Wd2HBHJZiphuUH16tVZtmwZX331FV9//TUPP/wws2fPJjU11exoTi0xMRFfX19GjBhBjRo1zI4jIjlAJSyZql27Nt999x1z587l888/59FHH2XJkiXasSmb9O3blypVqtClSxezo4hIDrEY2nZHboNhGPz4448EBgaSkpJCWFgYLVq0wGKxmB3NKXzxxRcMHDiQqKgoChcubHYcsQdxcTB7Nid+/JH9UVHUa9YMatSATp3Aw8PsdJJFVMJyRwzD4Ouvv2bo0KG4u7szfPhwGjdurDK+B/v376du3bqsXLmS2rVrmx1HzBYZCeHh8O231s+Tkv59zM0NDAOaNYNBg8DHx5yMkmVUwnJX0tPTWbJkCUFBQZQpU4YRI0ZQr149s2M5nJSUFBo0aIC/vz99+vQxO46Ybdo06NcPEhOtZZsZi8VayGPHQo8eOZdPspxKWO5Jamoqc+fOJTQ0lKpVqzJ8+HBq1qxpdiyH0bdvX2JjY1mxYoWuJuR2Vwo4IeH2n+PuriJ2cCphyRLJycnMnDkz44w4JCSEatWqmR3Lrn3zzTf07NmTLVu2UKxYMbPjiJkiI+GZZ+6sgK9wd4d160BDGQ5Js6MlSxQoUICePXsSGxvLk08+ybPPPktAQAD79u0zO5pdOnr0KG+99RYLFy5UAYt1DPi6xXEKXvfhAvSy9dzEROvzxSGphCVLubu7079/f2JjY/Hy8uLJJ5+ka9euHDlyxOxodiM1NRU/Pz/effdd6tevb3YcMVtcnHUS1nUXJS9e9XECcANsbmZpGLByJZw6ld1JJRuohCVb3H///QQFBREdHU2xYsV47LHH6NOnDydPnjQ7mumGDRuGm5sbH3zwgdlRxB7Mnn3LQ5YCJYCGmR1gsdzW64j9UQlLtipevDgffvghu3btwjAMqlatyqBBgzhz5ozZ0UyxatUqPv/8c+bNm0eePPrxE2DbtmtvQ7JhDtAeyHTqXmIibN+excEkJ+hfAckRpUqVYuLEiWzZsoXTp0/j7e1NaGgo58+fNztajjlx4gTt27dn7ty5lCxZ0uw4Yi/Onbvpw4eAdUCHW72OtiJ1SCphyVHly5fn008/ZePGjezduxcvLy/Gjh3r9Ds2paenExAQwFtvvUXjxo3NjiP25BYrpM0DGgAVb/U6RYtmUSDJSSphMYWnpyfz589nzZo1bNiwAU9PT6ZMmeK0OzZ9+OGHJCcnExQUZHYUsTc1aoCra6YPz+U2zoLd3KB69axMJTlE9wmLXdi8eTNDhw5l165dBAcHExAQQN68ec2OlSV++eUX3njjDTZt2kTZsmXNjiP2Ji4OKlSwOS78G/A81tnRhW72Gq6ucPiw1pR2QDoTFrtQq1YtVq5cyfz585kzZw7VqlUjIiLC4XdsOn36NG3btmXWrFkqYLGtRAnrWtA2VkybA7TiFgVssUDz5ipgB6UzYbE7hmGwatUqAgMDSUxMJCwsjFdeecXhlnU0DINXXnmFhx9+mLFjx5odR+yZVszKtVTCYrcMw+C///0vQ4cOxdXVleHDh9OkSROHKeMJEyYQERHBL7/8Qv78+c2OI/ZOa0fnSiphsXvp6el88cUXBAUFUapUKUaMGEGDBg3MjnVTkZGRvPTSS/z+++9UrHjLea0iVtpFKdfRmLDYvTx58uDr68vOnTvp2LEj7dq1o1mzZmzatMnsaDadO3cOX19fpk2bpgKWO9Ojh/XScsuW1slWbm7XPu7mZv16y5bW41TADk9nwuJwUlJSMnZsevLJJwkNDeXRRx81OxZgvYTeunVrSpQowZQpU8yOI47s1CnrUpTbt1sX4iha1HobUseOmoTlRFTC4rASEhKYNm0ao0ePpkmTJoSEhODp6WlqpunTpzN9+nQ2btyI603u/RQRAV2OFgfm7u5O3759iY2NpUqVKtStW5cuXbpw+PBhU/Js27aNoUOHsmTJEhWwiNwWlbA4vEKFCjF06FD27t2Lh4cHTzzxBL179+bEiRM5luHixYu0bt2aCRMm4O3tnWPvKyKOTSUsTqNYsWKMHDmSXbt24eLiQrVq1Rg4cCCnT5/O9vfu2bMn9erVo127dtn+XiLiPFTC4nRKlizJhAkT2Lp1K/Hx8Tz88MOEhIRk245Nc+bMITIykkmTJmXL64uI89LELHF6+/btIyQkhO+++47+/fvTs2dP3N3dWbBgAQcPHmTIkCGZPzkuzjpDdds265ZzhQtbF9zv1Ak8PNizZw8NGzZkzZo1VNcC+iJyh1TCkmvs2rWLoKAgfvvtN/r160doaChJSUn873//u3F7wchICA+Hb7+1fn714vpubmAYpL7wAgE7d/LcBx/QpUuXnPtGRMRpqIQl14mKisLf35/o6GgAihYtSnR0NB5X7r28zVWL0oHLLi7knzQJixZNEJG7oBKWXOf8+fM8+OCDXLp0KeNrjzzyCDt37sQyfbrW7xWRHKMSllxn//79+Pn5kZCQQFpaGufPn+fChQtEz59PqTZtbBZwBBACHAZKAbOBhlcfoJ1sROQuqIRFrmjVClasuOES9I/AW8BioA7w1z9fL3P1QRaLdT3fpUtzIqmIOAmVsAhYZ0FXqHDtBKx/1AM6//NxU66ucPiw1vUVkdum+4RFwHobkg1pwCbgFOAJlAXeARJtHWyxZPo6IiK2qIRFwHofsI2z4JPAZeBL4BdgK7AFGG7rNRITrTveiIjcJpWwCFgX4rDhym6uvYDSwAPA+8DKzF4nPj6rk4mIE1MJi4B1JSwbimK9BG256msWm0deeULRrMskIk5PJSwC1qUoM9l+sBMwCYgD4oEJQAtbB7q5WTddFxG5TZodLQI3nR19GXgXWAi4Aq2B0f/8+RqaHS0id0hnwiIAJUpAs2bWGc7XyQdMBc4CJ4CPsVHAFgs0b64CFpE7ojNhkSsiI+GZZ+5sycortGKWiNwFnQmLXOHjY10D2t39zp53Ze1oFbCI3KG8ZgcQsStXNmG4jV2UsFisk7G0eYOI3CVdjhaxZdMm637CK1dayzbxqjWy/tlPmObNYdAgnQGLyF1TCYvczKlT1qUot2+3LsRRtKj1NqSOHTUJS0TumUpYRETEJJqYJSIiYhKVsIiIiElUwiIiIiZRCYuIiO34FHEAAADcSURBVJhEJSwiImISlbCIiIhJVMIiIiImUQmLiIiYRCUsIiJiEpWwiIiISVTCIiIiJlEJi4iImEQlLCIiYhKVsIiIiElUwiIiIiZRCYuIiJhEJSwiImISlbCIiIhJVMIiIiImUQmLiIiYRCUsIiJiEpWwiIiISVTCIiIiJlEJi4iImEQlLCIiYhKVsIiIiElUwiIiIiZRCYuIiJhEJSwiImISlbCIiIhJVMIiIiImUQmLiIiYRCUsIiJiEpWwiIiISVTCIiIiJlEJi4iImEQlLCIiYhKVsIiIiEn+D6RzjEw39hGWAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "G.add_edge(5, 6)\n",
    "nx.draw_circular(G, with_labels=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.pagerank(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "G.add_edge(2, 8)\n",
    "nx.draw_circular(G, with_labels=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.pagerank(G)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Moving back to Airports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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": 33,
     "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": 34,
   "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": 34,
     "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": 35,
   "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": 35,
     "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": 36,
   "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": 36,
     "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": 37,
   "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": 37,
     "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": 38,
   "metadata": {},
   "outputs": [
    {
     "ename": "NetworkXError",
     "evalue": "Graph is not weakly connected.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNetworkXError\u001b[0m                             Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-38-1bbd89279bb2>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maverage_shortest_path_length\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpass_2015\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/dev/venv/system/lib/python3.6/site-packages/networkx/algorithms/shortest_paths/generic.py\u001b[0m in \u001b[0;36maverage_shortest_path_length\u001b[0;34m(G, weight, method)\u001b[0m\n\u001b[1;32m    389\u001b[0m     \u001b[0;31m# Shortest path length is undefined if the graph is disconnected.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    390\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_directed\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mnx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_weakly_connected\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 391\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mnx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mNetworkXError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Graph is not weakly connected.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    392\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_directed\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mnx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_connected\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    393\u001b[0m         \u001b[0;32mraise\u001b[0m \u001b[0mnx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mNetworkXError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Graph is not connected.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNetworkXError\u001b[0m: Graph is not weakly connected."
     ]
    }
   ],
   "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": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "list(nx.weakly_connected_components(pass_2015))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SPB, SSB, AIK anyone?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pass_air_data[(pass_air_data['YEAR'] == 2015) & (pass_air_data['ORIGIN'] == 'AIK')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pass_2015.remove_nodes_from(['SPB', 'SSB', 'AIK'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "nx.is_weakly_connected(pass_2015)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "nx.is_strongly_connected(pass_2015)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Strongly vs weakly connected graphs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "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": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "G.add_edge(3, 4)\n",
    "nx.draw(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "nx.is_strongly_connected(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "list(nx.strongly_connected_components(pass_2015))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pass_air_data[(pass_air_data['YEAR'] == 2015) & (pass_air_data['DEST'] == 'TSP')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pass_2015_strong = max(nx.strongly_connected_component_subgraphs(pass_2015), key=len)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(pass_2015_strong)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "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": null,
   "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": null,
   "metadata": {},
   "outputs": [],
   "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": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "passenger_graph['JFK']['SFO'][25]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def str_to_list(a):\n",
    "    return a[1:-1].split(', ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in str_to_list(passenger_graph['JFK']['SFO'][25]['UNIQUE_CARRIER_NAME']):\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "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": null,
   "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": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(united_network)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(united_network.edges())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sorted(nx.pagerank(united_network, weight='weight').items(), key=lambda x:x[1], reverse=True)[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "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 New York so what should we do?\n",
    "\n",
    "Obviously we will make a time series of number of passengers flying out of EWR/JFK/LGA 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": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pass_air_data[(pass_air_data.ORIGIN == 'EWR') &\n",
    "              (pass_air_data.UNIQUE_CARRIER_NAME.str.contains('United Air Lines Inc.'))\n",
    "             ].groupby('YEAR')['PASSENGERS'].sum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pass_air_data[(pass_air_data.ORIGIN == 'JFK') &\n",
    "              (pass_air_data.UNIQUE_CARRIER_NAME.str.contains('United Air Lines Inc.'))\n",
    "             ].groupby('YEAR')['PASSENGERS'].sum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pass_air_data[(pass_air_data.ORIGIN == 'LGA') &\n",
    "              (pass_air_data.UNIQUE_CARRIER_NAME.str.contains('United Air Lines Inc.'))\n",
    "             ].groupby('YEAR')['PASSENGERS'].sum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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