Network Graphing Notes.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "#\n",
    "import pygraphviz as pgv\n",
    "import networkx as nx\n",
    "import json\n",
    "import re\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "# \n",
    "import socket"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Network Graphing with networkx, pygraphviz**\n",
    "\n",
    "originally from\n",
    "https://www.analyticsvidhya.com/blog/2018/04/introduction-to-graph-theory-network-analysis-python-codes/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a Graph \n",
    "G = nx.Graph() # Right now G is empty\n",
    "\n",
    "# Add a node\n",
    "G.add_node(1) \n",
    "G.add_nodes_from([2,3]) # You can also add a list of nodes by passing a list argument\n",
    "\n",
    "# Add edges \n",
    "G.add_edge(1,2)\n",
    "\n",
    "e = (2,3)\n",
    "G.add_edge(*e) # * unpacks the tuple\n",
    "G.add_edges_from([(1,2), (1,3)]) # Just like nodes we can add edges from a list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NodeView((1, 2, 3))"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.nodes()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nx.draw(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "strict graph \"\" {\n",
      "\t1 -- 2;\n",
      "\t2 -- 3;\n",
      "\t3 -- 1;\n",
      "}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "d={'1': {'2': None}, '2': {'1': None, '3': None}, '3': {'1': None}}\n",
    "A = pgv.AGraph(data=d)\n",
    "print(A) # This is the 'string' or simple representation of the Graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Let us create another Graph where we can individually control the colour of each node\n",
    "B = pgv.AGraph()\n",
    "\n",
    "# Setting node attributes that are common for all nodes \n",
    "B.node_attr['style']='filled'\n",
    "B.node_attr['shape']='circle'\n",
    "B.node_attr['fixedsize']='true'\n",
    "B.node_attr['fontcolor']='#FFFFFF'\n",
    "\n",
    "# Creating and setting node attributes that vary for each node (using a for loop)\n",
    "for i in range(16):\n",
    " B.add_edge(0,i)\n",
    " n=B.get_node(i)\n",
    " n.attr['fillcolor']=\"#%2x0000\"%(i*16)\n",
    " n.attr['height']=\"%s\"%(i/16.0+0.5)\n",
    " n.attr['width']=\"%s\"%(i/16.0+0.5)\n",
    "B.draw('star.png',prog=\"circo\") # This creates a .png file in the local directory. Displayed below."
   ]
  },
  {
   "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": [
    "# weird how nx.draw(B) and B.draw do different things\n",
    "nx.draw(B)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 10,
     "metadata": {
      "image/png": {
       "width": 650
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image('star.png', width=650)\n",
    "#Image('images/network.PNG')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Analyzing sample airlines data**\n",
    "\n",
    "- We notice that origin and destination look like good choices for Nodes. Everything can then be imagined as either node or edge attributes. A single edge can be thought of as a journey. And such a journey will have various times, a flight number, an airplane tail number etc associated with it\n",
    "- We notice that the year, month, day and time information is spread over many columns. We want to create one datetime column containing all of this information. We also need to keep scheduled and actual time of arrival and departure separate. So we should finally have 4 datetime columns (Scheduled and actual times of arrival and departure)\n",
    "- Additionally, the time columns are not in a proper format. 4:30 pm is represented as 1630 instead of 16:30. There is no delimiter to split that column. One approach is to use pandas string methods and regular expressions\n",
    "- We should also note that sched_dep_time and sched_arr_time are int64 dtype and dep_time and arr_time are float64 dtype\n",
    "- An additional complication is NaN values\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('data/Airlines.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100, 16)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year                int64\n",
       "month               int64\n",
       "day                 int64\n",
       "dep_time          float64\n",
       "sched_dep_time      int64\n",
       "dep_delay         float64\n",
       "arr_time          float64\n",
       "sched_arr_time      int64\n",
       "arr_delay         float64\n",
       "carrier            object\n",
       "flight              int64\n",
       "tailnum            object\n",
       "origin             object\n",
       "dest               object\n",
       "air_time          float64\n",
       "distance            int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>dep_time</th>\n",
       "      <th>sched_dep_time</th>\n",
       "      <th>dep_delay</th>\n",
       "      <th>arr_time</th>\n",
       "      <th>sched_arr_time</th>\n",
       "      <th>arr_delay</th>\n",
       "      <th>carrier</th>\n",
       "      <th>flight</th>\n",
       "      <th>tailnum</th>\n",
       "      <th>origin</th>\n",
       "      <th>dest</th>\n",
       "      <th>air_time</th>\n",
       "      <th>distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013</td>\n",
       "      <td>2</td>\n",
       "      <td>26</td>\n",
       "      <td>1807.0</td>\n",
       "      <td>1630</td>\n",
       "      <td>97.0</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>1837</td>\n",
       "      <td>79.0</td>\n",
       "      <td>EV</td>\n",
       "      <td>4411</td>\n",
       "      <td>N13566</td>\n",
       "      <td>EWR</td>\n",
       "      <td>MEM</td>\n",
       "      <td>144.0</td>\n",
       "      <td>946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013</td>\n",
       "      <td>8</td>\n",
       "      <td>17</td>\n",
       "      <td>1459.0</td>\n",
       "      <td>1445</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1801.0</td>\n",
       "      <td>1747</td>\n",
       "      <td>14.0</td>\n",
       "      <td>B6</td>\n",
       "      <td>1171</td>\n",
       "      <td>N661JB</td>\n",
       "      <td>LGA</td>\n",
       "      <td>FLL</td>\n",
       "      <td>147.0</td>\n",
       "      <td>1076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "      <td>1812.0</td>\n",
       "      <td>1815</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>2055.0</td>\n",
       "      <td>2125</td>\n",
       "      <td>-30.0</td>\n",
       "      <td>AS</td>\n",
       "      <td>7</td>\n",
       "      <td>N403AS</td>\n",
       "      <td>EWR</td>\n",
       "      <td>SEA</td>\n",
       "      <td>315.0</td>\n",
       "      <td>2402</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  month  day  dep_time  sched_dep_time  dep_delay  arr_time  \\\n",
       "0  2013      2   26    1807.0            1630       97.0    1956.0   \n",
       "1  2013      8   17    1459.0            1445       14.0    1801.0   \n",
       "2  2013      2   13    1812.0            1815       -3.0    2055.0   \n",
       "\n",
       "   sched_arr_time  arr_delay carrier  flight tailnum origin dest  air_time  \\\n",
       "0            1837       79.0      EV    4411  N13566    EWR  MEM     144.0   \n",
       "1            1747       14.0      B6    1171  N661JB    LGA  FLL     147.0   \n",
       "2            2125      -30.0      AS       7  N403AS    EWR  SEA     315.0   \n",
       "\n",
       "   distance  \n",
       "0       946  \n",
       "1      1076  \n",
       "2      2402  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create useful date features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# converting sched_dep_time to 'std' - Scheduled time of departure\n",
    "data['std'] = data.sched_dep_time.astype(str).str.replace('(\\d{2}$)', '') + ':' + data.sched_dep_time.astype(str).str.extract('(\\d{2}$)', expand=False) + ':00'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# converting sched_arr_time to 'sta' - Scheduled time of arrival\n",
    "data['sta'] = data.sched_arr_time.astype(str).str.replace('(\\d{2}$)', '') + ':' + data.sched_arr_time.astype(str).str.extract('(\\d{2}$)', expand=False) + ':00'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# converting dep_time to 'atd' - Actual time of departure\n",
    "data['atd'] = data.dep_time.fillna(0).astype(np.int64).astype(str).str.replace('(\\d{2}$)', '') + ':' + data.dep_time.fillna(0).astype(np.int64).astype(str).str.extract('(\\d{2}$)', expand=False) + ':00'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# converting arr_time to 'ata' - Actual time of arrival\n",
    "data['ata'] = data.arr_time.fillna(0).astype(np.int64).astype(str).str.replace('(\\d{2}$)', '') + ':' + data.arr_time.fillna(0).astype(np.int64).astype(str).str.extract('(\\d{2}$)', expand=False) + ':00'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Make a single date feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['date'] = pd.to_datetime(data[['year', 'month', 'day']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# finally we drop the columns we don't need\n",
    "data = data.drop(columns = ['year', 'month', 'day'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ingest the dataset directly into pandas from nx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "FG = nx.from_pandas_edgelist(data, source='origin', target='dest', edge_attr=True,)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NodeView(('EWR', 'MEM', 'LGA', 'FLL', 'SEA', 'JFK', 'DEN', 'ORD', 'MIA', 'PBI', 'MCO', 'CMH', 'MSP', 'IAD', 'CLT', 'TPA', 'DCA', 'SJU', 'ATL', 'BHM', 'SRQ', 'MSY', 'DTW', 'LAX', 'JAX', 'RDU', 'MDW', 'DFW', 'IAH', 'SFO', 'STL', 'CVG', 'IND', 'RSW', 'BOS', 'CLE'))"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FG.nodes()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "EdgeView([('EWR', 'MEM'), ('EWR', 'SEA'), ('EWR', 'MIA'), ('EWR', 'ORD'), ('EWR', 'MSP'), ('EWR', 'TPA'), ('EWR', 'MSY'), ('EWR', 'DFW'), ('EWR', 'IAH'), ('EWR', 'SFO'), ('EWR', 'CVG'), ('EWR', 'IND'), ('EWR', 'RDU'), ('EWR', 'IAD'), ('EWR', 'RSW'), ('EWR', 'BOS'), ('EWR', 'PBI'), ('EWR', 'LAX'), ('EWR', 'MCO'), ('EWR', 'SJU'), ('LGA', 'FLL'), ('LGA', 'ORD'), ('LGA', 'PBI'), ('LGA', 'CMH'), ('LGA', 'IAD'), ('LGA', 'CLT'), ('LGA', 'MIA'), ('LGA', 'DCA'), ('LGA', 'BHM'), ('LGA', 'RDU'), ('LGA', 'ATL'), ('LGA', 'TPA'), ('LGA', 'MDW'), ('LGA', 'DEN'), ('LGA', 'MSP'), ('LGA', 'DTW'), ('LGA', 'STL'), ('LGA', 'MCO'), ('LGA', 'CVG'), ('LGA', 'IAH'), ('FLL', 'JFK'), ('SEA', 'JFK'), ('JFK', 'DEN'), ('JFK', 'MCO'), ('JFK', 'TPA'), ('JFK', 'SJU'), ('JFK', 'ATL'), ('JFK', 'SRQ'), ('JFK', 'DCA'), ('JFK', 'DTW'), ('JFK', 'LAX'), ('JFK', 'JAX'), ('JFK', 'CLT'), ('JFK', 'PBI'), ('JFK', 'CLE'), ('JFK', 'IAD'), ('JFK', 'BOS')])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FG.edges()"
   ]
  },
  {
   "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": [
    "nx.draw_networkx(FG, with_labels=True) # Quick view of the Graph. As expected we see 3 very busy airports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.09047619047619047"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.algorithms.degree_centrality(FG) # Notice the 3 airports from which all of our 100 rows of data originates\n",
    "nx.density(FG) # Average edge density of the Graphs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.36984126984127"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.average_shortest_path_length(FG) # Average shortest path length for ALL paths in the Graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{20: 1.95, 1: 19.307692307692307, 2: 19.0625, 17: 2.0588235294117645, 3: 19.0}"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.average_degree_connectivity(FG) # For a node of degree k - What is the average of its neighbours' degree?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As is obvious from looking at the Graph visualization (way above) – There are multiple paths from some airports to others. Let us say we want to calculate the shortest possible route between 2 such airports. Right off the bat we can think of a couple of ways of doing it\n",
    "\n",
    "    There is the shortest path by distance\n",
    "    There is the shortest path by flight time\n",
    "\n",
    "What we can do is to calculate the shortest path algorithm by weighing the paths with either the distance or airtime. Please note that this is an approximate solution – The actual problem to solve is to calculate the shortest path factoring in the availability of a flight when you reach your transfer airport + wait time for the transfer. This is a more complete approach and this is how humans normally plan their travel. For the purposes of this article we will just assume that is flight is readily available when you reach an airport and calculate the shortest path using the airtime as the weight"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['JAX', 'JFK', 'DEN', 'LGA', 'ORD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DEN', 'LGA', 'PBI', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DEN', 'LGA', 'IAD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DEN', 'LGA', 'MIA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DEN', 'LGA', 'RDU', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DEN', 'LGA', 'TPA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DEN', 'LGA', 'MSP', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DEN', 'LGA', 'MCO', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DEN', 'LGA', 'CVG', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DEN', 'LGA', 'IAH', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'SEA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'MCO', 'LGA', 'ORD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'MCO', 'LGA', 'PBI', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'MCO', 'LGA', 'IAD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'MCO', 'LGA', 'MIA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'MCO', 'LGA', 'RDU', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'MCO', 'LGA', 'TPA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'MCO', 'LGA', 'MSP', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'MCO', 'LGA', 'CVG', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'MCO', 'LGA', 'IAH', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'MCO', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'TPA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'TPA', 'LGA', 'ORD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'TPA', 'LGA', 'PBI', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'TPA', 'LGA', 'IAD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'TPA', 'LGA', 'MIA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'TPA', 'LGA', 'RDU', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'TPA', 'LGA', 'MSP', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'TPA', 'LGA', 'MCO', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'TPA', 'LGA', 'CVG', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'TPA', 'LGA', 'IAH', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'SJU', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'ATL', 'LGA', 'ORD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'ATL', 'LGA', 'PBI', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'ATL', 'LGA', 'IAD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'ATL', 'LGA', 'MIA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'ATL', 'LGA', 'RDU', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'ATL', 'LGA', 'TPA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'ATL', 'LGA', 'MSP', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'ATL', 'LGA', 'MCO', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'ATL', 'LGA', 'CVG', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'ATL', 'LGA', 'IAH', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DCA', 'LGA', 'ORD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DCA', 'LGA', 'PBI', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DCA', 'LGA', 'IAD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DCA', 'LGA', 'MIA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DCA', 'LGA', 'RDU', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DCA', 'LGA', 'TPA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DCA', 'LGA', 'MSP', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DCA', 'LGA', 'MCO', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DCA', 'LGA', 'CVG', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DCA', 'LGA', 'IAH', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DTW', 'LGA', 'ORD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DTW', 'LGA', 'PBI', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DTW', 'LGA', 'IAD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DTW', 'LGA', 'MIA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DTW', 'LGA', 'RDU', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DTW', 'LGA', 'TPA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DTW', 'LGA', 'MSP', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DTW', 'LGA', 'MCO', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DTW', 'LGA', 'CVG', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'DTW', 'LGA', 'IAH', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'LAX', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'FLL', 'LGA', 'ORD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'FLL', 'LGA', 'PBI', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'FLL', 'LGA', 'IAD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'FLL', 'LGA', 'MIA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'FLL', 'LGA', 'RDU', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'FLL', 'LGA', 'TPA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'FLL', 'LGA', 'MSP', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'FLL', 'LGA', 'MCO', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'FLL', 'LGA', 'CVG', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'FLL', 'LGA', 'IAH', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'CLT', 'LGA', 'ORD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'CLT', 'LGA', 'PBI', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'CLT', 'LGA', 'IAD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'CLT', 'LGA', 'MIA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'CLT', 'LGA', 'RDU', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'CLT', 'LGA', 'TPA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'CLT', 'LGA', 'MSP', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'CLT', 'LGA', 'MCO', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'CLT', 'LGA', 'CVG', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'CLT', 'LGA', 'IAH', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'PBI', 'LGA', 'ORD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'PBI', 'LGA', 'IAD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'PBI', 'LGA', 'MIA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'PBI', 'LGA', 'RDU', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'PBI', 'LGA', 'TPA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'PBI', 'LGA', 'MSP', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'PBI', 'LGA', 'MCO', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'PBI', 'LGA', 'CVG', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'PBI', 'LGA', 'IAH', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'PBI', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'IAD', 'LGA', 'ORD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'IAD', 'LGA', 'PBI', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'IAD', 'LGA', 'MIA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'IAD', 'LGA', 'RDU', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'IAD', 'LGA', 'TPA', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'IAD', 'LGA', 'MSP', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'IAD', 'LGA', 'MCO', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'IAD', 'LGA', 'CVG', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'IAD', 'LGA', 'IAH', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'IAD', 'EWR', 'DFW']\n",
      "['JAX', 'JFK', 'BOS', 'EWR', 'DFW']\n"
     ]
    }
   ],
   "source": [
    "# Let us take the example of JAX and DFW airports:\n",
    "# Let us find all the paths available\n",
    "for path in nx.all_simple_paths(FG, source='JAX', target='DFW'):\n",
    " print(path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['JAX', 'JFK', 'SEA', 'EWR', 'DFW']"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let us find the dijkstra path from JAX to DFW.\n",
    "# You can read more in-depth on how dijkstra works from this resource - https://courses.csail.mit.edu/6.006/fall11/lectures/lecture16.pdf\n",
    "dijpath = nx.dijkstra_path(FG, source='JAX', target='DFW')\n",
    "dijpath"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['JAX', 'JFK', 'BOS', 'EWR', 'DFW']"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let us try to find the dijkstra path weighted by airtime (approximate case)\n",
    "shortpath = nx.dijkstra_path(FG, source='JAX', target='DFW', weight='air_time')\n",
    "shortpath"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Network graphs for IP networks\n",
    "\n",
    "Originally from. \n",
    "http://www.austintaylor.io/d3/python/pandas/2016/02/01/create-d3-chart-python-force-directed/\n",
    "\n",
    "the notion is to take the methodology and translate it into nx instead of d3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "pcap_data = pd.read_csv('data/test10.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>ip.src</th>\n",
       "      <th>ip.dst</th>\n",
       "      <th>ip.proto</th>\n",
       "      <th>udp.dstport</th>\n",
       "      <th>ip.len</th>\n",
       "      <th>frame.time_delta_displayed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.52.3.50</td>\n",
       "      <td>10.52.3.15</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.52.3.15</td>\n",
       "      <td>10.52.3.50</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0.000906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.52.3.50</td>\n",
       "      <td>10.52.3.15</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0.002231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10.52.3.8</td>\n",
       "      <td>10.52.3.1</td>\n",
       "      <td>17.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>1.236884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000533</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ip.src      ip.dst  ip.proto  udp.dstport  ip.len  \\\n",
       "0  10.52.3.50  10.52.3.15       6.0          NaN   104.0   \n",
       "1  10.52.3.15  10.52.3.50       6.0          NaN    80.0   \n",
       "2  10.52.3.50  10.52.3.15       6.0          NaN    52.0   \n",
       "3   10.52.3.8   10.52.3.1      17.0        137.0    78.0   \n",
       "4         NaN         NaN       NaN          NaN     NaN   \n",
       "\n",
       "   frame.time_delta_displayed  \n",
       "0                    0.000000  \n",
       "1                    0.000906  \n",
       "2                    0.002231  \n",
       "3                    1.236884  \n",
       "4                    0.000533  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pcap_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# subset source and destination only\n",
    "df = pcap_data[['ip.src','ip.dst']].dropna().copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>ip.src</th>\n",
       "      <th>ip.dst</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.52.3.50</td>\n",
       "      <td>10.52.3.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.52.3.15</td>\n",
       "      <td>10.52.3.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.52.3.50</td>\n",
       "      <td>10.52.3.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10.52.3.8</td>\n",
       "      <td>10.52.3.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10.52.3.50</td>\n",
       "      <td>239.255.255.250</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ip.src           ip.dst\n",
       "0  10.52.3.50       10.52.3.15\n",
       "1  10.52.3.15       10.52.3.50\n",
       "2  10.52.3.50       10.52.3.15\n",
       "3   10.52.3.8        10.52.3.1\n",
       "8  10.52.3.50  239.255.255.250"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.rename(columns={\"ip.src\":\"source\",\"ip.dst\":\"target\"}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>source</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.52.3.50</td>\n",
       "      <td>10.52.3.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.52.3.15</td>\n",
       "      <td>10.52.3.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.52.3.50</td>\n",
       "      <td>10.52.3.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10.52.3.8</td>\n",
       "      <td>10.52.3.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10.52.3.50</td>\n",
       "      <td>239.255.255.250</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       source           target\n",
       "0  10.52.3.50       10.52.3.15\n",
       "1  10.52.3.15       10.52.3.50\n",
       "2  10.52.3.50       10.52.3.15\n",
       "3   10.52.3.8        10.52.3.1\n",
       "8  10.52.3.50  239.255.255.250"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "source       target     \n",
       "10.52.3.1    10.52.3.255     12\n",
       "             10.52.3.8       47\n",
       "10.52.3.105  224.0.0.22      39\n",
       "             224.0.0.251    135\n",
       "10.52.3.15   10.52.3.50      73\n",
       "dtype: int64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby([\"source\",\"target\"]).size().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfgroup = df.groupby([\"source\",\"target\"]).size().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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>source</th>\n",
       "      <th>target</th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.52.3.1</td>\n",
       "      <td>10.52.3.255</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.52.3.1</td>\n",
       "      <td>10.52.3.8</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.52.3.105</td>\n",
       "      <td>224.0.0.22</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10.52.3.105</td>\n",
       "      <td>224.0.0.251</td>\n",
       "      <td>135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.52.3.15</td>\n",
       "      <td>10.52.3.50</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        source       target    0\n",
       "0    10.52.3.1  10.52.3.255   12\n",
       "1    10.52.3.1    10.52.3.8   47\n",
       "2  10.52.3.105   224.0.0.22   39\n",
       "3  10.52.3.105  224.0.0.251  135\n",
       "4   10.52.3.15   10.52.3.50   73"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfgroup.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfgroup.rename(columns={0:'count'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>source</th>\n",
       "      <th>target</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.52.3.1</td>\n",
       "      <td>10.52.3.255</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.52.3.1</td>\n",
       "      <td>10.52.3.8</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.52.3.105</td>\n",
       "      <td>224.0.0.22</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10.52.3.105</td>\n",
       "      <td>224.0.0.251</td>\n",
       "      <td>135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.52.3.15</td>\n",
       "      <td>10.52.3.50</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        source       target  count\n",
       "0    10.52.3.1  10.52.3.255     12\n",
       "1    10.52.3.1    10.52.3.8     47\n",
       "2  10.52.3.105   224.0.0.22     39\n",
       "3  10.52.3.105  224.0.0.251    135\n",
       "4   10.52.3.15   10.52.3.50     73"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfgroup.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# this will be referred to later\n",
    "unique_ips = pd.Index(dfgroup['source']\n",
    "                      .append(dfgroup['target'])\n",
    "                      .reset_index(drop=True).unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['10.52.3.1', '10.52.3.105', '10.52.3.15', '10.52.3.20', '10.52.3.50',\n",
       "       '10.52.3.7', '10.52.3.8', '10.52.3.9', '131.186.113.70',\n",
       "       '131.186.161.70', '162.88.193.70', '17.142.169.199', '17.248.130.8',\n",
       "       '17.253.16.125', '17.253.16.253', '17.253.26.125', '17.253.4.253',\n",
       "       '17.57.144.180', '17.57.144.181', '172.217.14.202', '172.217.14.227',\n",
       "       '172.217.14.238', '172.217.3.170', '184.26.80.199', '209.197.193.112',\n",
       "       '209.197.193.90', '216.146.43.70', '216.146.43.71', '23.204.60.203',\n",
       "       '23.52.168.63', '23.52.169.148', '3.213.160.221', '64.68.120.47',\n",
       "       '72.21.91.29', '91.189.94.4', '10.52.3.255', '224.0.0.22',\n",
       "       '224.0.0.251', '239.255.255.250'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_ips"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create subnet group\n",
    "Note: We use regular expression here to group the various subnets to the third octect. For example, if you have 2 IP addresses (192.168.1.5, 192.168.2.5), they’d both be treated as 2 networks. We’ll use this to group the subnets by color and create our groups."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "group_dict = {}\n",
    "counter = 0\n",
    "for ip in unique_ips:\n",
    "    breakout_ip = re.match(\"^(\\d{1,3})\\.(\\d{1,3})\\.(\\d{1,3})\\.(\\d{1,3})$\", ip)\n",
    "    if breakout_ip:\n",
    "        net_id = '.'.join(breakout_ip.group(1,2,3))\n",
    "        if net_id not in group_dict:\n",
    "            counter += 1\n",
    "            group_dict[net_id] = counter\n",
    "        else:\n",
    "            pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<re.Match object; span=(0, 15), match='239.255.255.250'>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "breakout_ip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp_links_list = list(dfgroup.apply(lambda row: {\"source\": row['source'], \"target\": row['target'], \"value\": row['count']}, axis=1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'source': '10.52.3.1', 'target': '10.52.3.255', 'value': 12},\n",
       " {'source': '10.52.3.1', 'target': '10.52.3.8', 'value': 47},\n",
       " {'source': '10.52.3.105', 'target': '224.0.0.22', 'value': 39},\n",
       " {'source': '10.52.3.105', 'target': '224.0.0.251', 'value': 135},\n",
       " {'source': '10.52.3.15', 'target': '10.52.3.50', 'value': 73},\n",
       " {'source': '10.52.3.15', 'target': '224.0.0.251', 'value': 4},\n",
       " {'source': '10.52.3.15', 'target': '91.189.94.4', 'value': 4},\n",
       " {'source': '10.52.3.20', 'target': '10.52.3.50', 'value': 63},\n",
       " {'source': '10.52.3.20', 'target': '224.0.0.251', 'value': 65},\n",
       " {'source': '10.52.3.50', 'target': '10.52.3.15', 'value': 146}]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_links_list[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now we need to extract the index location for each unique source and destination (target) pair and append it to our links list.\n",
    "links_list = []\n",
    "for link in temp_links_list:\n",
    "    record = {\"value\":link['value'], \"source\":unique_ips.get_loc(link['source']),\n",
    "     \"target\": unique_ips.get_loc(link['target'])}\n",
    "    links_list.append(record)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'value': 12, 'source': 0, 'target': 35},\n",
       " {'value': 47, 'source': 0, 'target': 6},\n",
       " {'value': 39, 'source': 1, 'target': 36},\n",
       " {'value': 135, 'source': 1, 'target': 37},\n",
       " {'value': 73, 'source': 2, 'target': 4},\n",
       " {'value': 4, 'source': 2, 'target': 37},\n",
       " {'value': 4, 'source': 2, 'target': 34},\n",
       " {'value': 63, 'source': 3, 'target': 4},\n",
       " {'value': 65, 'source': 3, 'target': 37},\n",
       " {'value': 146, 'source': 4, 'target': 2}]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "links_list[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "# now create nodes\n",
    "nodes_list = []\n",
    "\n",
    "for ip in unique_ips:\n",
    "    breakout_ip = re.match(\"^(\\d{1,3})\\.(\\d{1,3})\\.(\\d{1,3})\\.(\\d{1,3})$\", ip)\n",
    "    if breakout_ip:\n",
    "        net_id = '.'.join(breakout_ip.group(1,2,3))\n",
    "        nodes_list.append({\"name\":ip, \"group\": group_dict.get(net_id)})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'name': '10.52.3.1', 'group': 1},\n",
       " {'name': '10.52.3.105', 'group': 1},\n",
       " {'name': '10.52.3.15', 'group': 1},\n",
       " {'name': '10.52.3.20', 'group': 1},\n",
       " {'name': '10.52.3.50', 'group': 1},\n",
       " {'name': '10.52.3.7', 'group': 1},\n",
       " {'name': '10.52.3.8', 'group': 1},\n",
       " {'name': '10.52.3.9', 'group': 1},\n",
       " {'name': '131.186.113.70', 'group': 2},\n",
       " {'name': '131.186.161.70', 'group': 3}]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nodes_list[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['nodes', 'links'])"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# now turn the data into json for the d3 example\n",
    "json_prep = {\"nodes\":nodes_list, \"links\":links_list}\n",
    "\n",
    "json_prep.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(json_prep)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      " \"links\": [\n",
      "  {\n",
      "   \"source\": 0,\n",
      "   \"target\": 35,\n",
      "   \"value\": 12\n",
      "  },\n",
      "  {\n",
      "   \"source\": 0,\n",
      "   \"target\": 6,\n",
      "   \"value\": 47\n",
      "  },\n",
      "  {\n",
      "   \"source\": 1,\n",
      "   \"target\": 36,\n",
      "   \"value\": 39\n",
      "  },\n",
      "  {\n",
      "   \"source\": 1,\n",
      "   \"target\": 37,\n",
      "   \"value\": 135\n",
      "  },\n",
      "  {\n",
      "   \"source\": 2,\n",
      "   \"target\": 4,\n",
      "   \"value\": 73\n",
      "  },\n",
      "  {\n",
      "   \"source\": 2,\n",
      "   \"target\": 37,\n",
      "   \"value\": 4\n",
      "  },\n",
      "  {\n",
      "   \"source\": 2,\n",
      "   \"target\": 34,\n",
      "   \"value\": 4\n",
      "  },\n",
      "  {\n",
      "   \"source\": 3,\n",
      "   \"target\": 4,\n",
      "   \"value\": 63\n",
      "  },\n",
      "  {\n",
      "   \"source\": 3,\n",
      "   \"target\": 37,\n",
      "   \"value\": 65\n",
      "  },\n",
      "  {\n",
      "   \"source\": 4,\n",
      "   \"target\": 2,\n",
      "   \"value\": 146\n",
      "  },\n",
      "  {\n",
      "   \"source\": 4,\n",
      "   \"target\": 3,\n",
      "   \"value\": 63\n",
      "  },\n",
      "  {\n",
      "   \"source\": 4,\n",
      "   \"target\": 35,\n",
      "   \"value\": 16\n",
      "  },\n",
      "  {\n",
      "   \"source\": 4,\n",
      "   \"target\": 6,\n",
      "   \"value\": 4505\n",
      "  },\n",
      "  {\n",
      "   \"source\": 4,\n",
      "   \"target\": 37,\n",
      "   \"value\": 113\n",
      "  },\n",
      "  {\n",
      "   \"source\": 4,\n",
      "   \"target\": 38,\n",
      "   \"value\": 148\n",
      "  },\n",
      "  {\n",
      "   \"source\": 5,\n",
      "   \"target\": 37,\n",
      "   \"value\": 3\n",
      "  },\n",
      "  {\n",
      "   \"source\": 5,\n",
      "   \"target\": 38,\n",
      "   \"value\": 96\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 0,\n",
      "   \"value\": 61\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 1,\n",
      "   \"value\": 36\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 35,\n",
      "   \"value\": 16\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 4,\n",
      "   \"value\": 4073\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 8,\n",
      "   \"value\": 12\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 9,\n",
      "   \"value\": 18\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 10,\n",
      "   \"value\": 12\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 11,\n",
      "   \"value\": 18\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 12,\n",
      "   \"value\": 122\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 13,\n",
      "   \"value\": 2\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 14,\n",
      "   \"value\": 1\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 15,\n",
      "   \"value\": 2\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 16,\n",
      "   \"value\": 1\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 17,\n",
      "   \"value\": 36\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 19,\n",
      "   \"value\": 11\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 20,\n",
      "   \"value\": 12\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 21,\n",
      "   \"value\": 30\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 22,\n",
      "   \"value\": 6\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 23,\n",
      "   \"value\": 16\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 24,\n",
      "   \"value\": 21\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 25,\n",
      "   \"value\": 446\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 26,\n",
      "   \"value\": 30\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 27,\n",
      "   \"value\": 18\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 37,\n",
      "   \"value\": 17\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 28,\n",
      "   \"value\": 15\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 29,\n",
      "   \"value\": 28\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 30,\n",
      "   \"value\": 57\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 38,\n",
      "   \"value\": 144\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 31,\n",
      "   \"value\": 23\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 32,\n",
      "   \"value\": 42\n",
      "  },\n",
      "  {\n",
      "   \"source\": 6,\n",
      "   \"target\": 33,\n",
      "   \"value\": 12\n",
      "  },\n",
      "  {\n",
      "   \"source\": 7,\n",
      "   \"target\": 1,\n",
      "   \"value\": 41\n",
      "  },\n",
      "  {\n",
      "   \"source\": 7,\n",
      "   \"target\": 18,\n",
      "   \"value\": 4\n",
      "  },\n",
      "  {\n",
      "   \"source\": 7,\n",
      "   \"target\": 37,\n",
      "   \"value\": 10\n",
      "  },\n",
      "  {\n",
      "   \"source\": 8,\n",
      "   \"target\": 6,\n",
      "   \"value\": 10\n",
      "  },\n",
      "  {\n",
      "   \"source\": 9,\n",
      "   \"target\": 6,\n",
      "   \"value\": 15\n",
      "  },\n",
      "  {\n",
      "   \"source\": 10,\n",
      "   \"target\": 6,\n",
      "   \"value\": 10\n",
      "  },\n",
      "  {\n",
      "   \"source\": 11,\n",
      "   \"target\": 6,\n",
      "   \"value\": 14\n",
      "  },\n",
      "  {\n",
      "   \"source\": 12,\n",
      "   \"target\": 6,\n",
      "   \"value\": 75\n",
      "  },\n",
      "  {\n",
      "   \"source\": 13,\n",
      "   \"target\": 6,\n",
      "   \"value\": 2\n",
      "  },\n",
      "  {\n",
      "   \"source\": 14,\n",
      "   \"target\": 6,\n",
      "   \"value\": 1\n",
      "  },\n",
      "  {\n",
      "   \"source\": 15,\n",
      "   \"target\": 6,\n",
      "   \"value\": 2\n",
      "  },\n",
      "  {\n",
      "   \"source\": 16,\n",
      "   \"target\": 6,\n",
      "   \"value\": 1\n",
      "  },\n",
      "  {\n",
      "   \"source\": 17,\n",
      "   \"target\": 6,\n",
      "   \"value\": 22\n",
      "  },\n",
      "  {\n",
      "   \"source\": 18,\n",
      "   \"target\": 7,\n",
      "   \"value\": 2\n",
      "  },\n",
      "  {\n",
      "   \"source\": 19,\n",
      "   \"target\": 6,\n",
      "   \"value\": 9\n",
      "  },\n",
      "  {\n",
      "   \"source\": 20,\n",
      "   \"target\": 6,\n",
      "   \"value\": 8\n",
      "  },\n",
      "  {\n",
      "   \"source\": 21,\n",
      "   \"target\": 6,\n",
      "   \"value\": 18\n",
      "  },\n",
      "  {\n",
      "   \"source\": 22,\n",
      "   \"target\": 6,\n",
      "   \"value\": 5\n",
      "  },\n",
      "  {\n",
      "   \"source\": 23,\n",
      "   \"target\": 6,\n",
      "   \"value\": 12\n",
      "  },\n",
      "  {\n",
      "   \"source\": 24,\n",
      "   \"target\": 6,\n",
      "   \"value\": 17\n",
      "  },\n",
      "  {\n",
      "   \"source\": 25,\n",
      "   \"target\": 6,\n",
      "   \"value\": 319\n",
      "  },\n",
      "  {\n",
      "   \"source\": 26,\n",
      "   \"target\": 6,\n",
      "   \"value\": 25\n",
      "  },\n",
      "  {\n",
      "   \"source\": 27,\n",
      "   \"target\": 6,\n",
      "   \"value\": 15\n",
      "  },\n",
      "  {\n",
      "   \"source\": 28,\n",
      "   \"target\": 6,\n",
      "   \"value\": 10\n",
      "  },\n",
      "  {\n",
      "   \"source\": 29,\n",
      "   \"target\": 6,\n",
      "   \"value\": 20\n",
      "  },\n",
      "  {\n",
      "   \"source\": 30,\n",
      "   \"target\": 6,\n",
      "   \"value\": 36\n",
      "  },\n",
      "  {\n",
      "   \"source\": 31,\n",
      "   \"target\": 6,\n",
      "   \"value\": 17\n",
      "  },\n",
      "  {\n",
      "   \"source\": 32,\n",
      "   \"target\": 6,\n",
      "   \"value\": 34\n",
      "  },\n",
      "  {\n",
      "   \"source\": 33,\n",
      "   \"target\": 6,\n",
      "   \"value\": 10\n",
      "  },\n",
      "  {\n",
      "   \"source\": 34,\n",
      "   \"target\": 2,\n",
      "   \"value\": 3\n",
      "  }\n",
      " ],\n",
      " \"nodes\": [\n",
      "  {\n",
      "   \"group\": 1,\n",
      "   \"name\": \"10.52.3.1\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 1,\n",
      "   \"name\": \"10.52.3.105\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 1,\n",
      "   \"name\": \"10.52.3.15\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 1,\n",
      "   \"name\": \"10.52.3.20\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 1,\n",
      "   \"name\": \"10.52.3.50\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 1,\n",
      "   \"name\": \"10.52.3.7\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 1,\n",
      "   \"name\": \"10.52.3.8\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 1,\n",
      "   \"name\": \"10.52.3.9\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 2,\n",
      "   \"name\": \"131.186.113.70\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 3,\n",
      "   \"name\": \"131.186.161.70\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 4,\n",
      "   \"name\": \"162.88.193.70\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 5,\n",
      "   \"name\": \"17.142.169.199\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 6,\n",
      "   \"name\": \"17.248.130.8\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 7,\n",
      "   \"name\": \"17.253.16.125\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 7,\n",
      "   \"name\": \"17.253.16.253\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 8,\n",
      "   \"name\": \"17.253.26.125\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 9,\n",
      "   \"name\": \"17.253.4.253\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 10,\n",
      "   \"name\": \"17.57.144.180\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 10,\n",
      "   \"name\": \"17.57.144.181\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 11,\n",
      "   \"name\": \"172.217.14.202\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 11,\n",
      "   \"name\": \"172.217.14.227\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 11,\n",
      "   \"name\": \"172.217.14.238\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 12,\n",
      "   \"name\": \"172.217.3.170\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 13,\n",
      "   \"name\": \"184.26.80.199\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 14,\n",
      "   \"name\": \"209.197.193.112\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 14,\n",
      "   \"name\": \"209.197.193.90\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 15,\n",
      "   \"name\": \"216.146.43.70\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 15,\n",
      "   \"name\": \"216.146.43.71\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 16,\n",
      "   \"name\": \"23.204.60.203\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 17,\n",
      "   \"name\": \"23.52.168.63\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 18,\n",
      "   \"name\": \"23.52.169.148\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 19,\n",
      "   \"name\": \"3.213.160.221\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 20,\n",
      "   \"name\": \"64.68.120.47\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 21,\n",
      "   \"name\": \"72.21.91.29\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 22,\n",
      "   \"name\": \"91.189.94.4\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 1,\n",
      "   \"name\": \"10.52.3.255\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 23,\n",
      "   \"name\": \"224.0.0.22\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 23,\n",
      "   \"name\": \"224.0.0.251\"\n",
      "  },\n",
      "  {\n",
      "   \"group\": 24,\n",
      "   \"name\": \"239.255.255.250\"\n",
      "  }\n",
      " ]\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "json_dump = json.dumps(json_prep, indent=1, sort_keys=True)\n",
    "print(json_dump)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "filename_out = 'pcap_export.json'\n",
    "json_out = open(filename_out,'w')\n",
    "json_out.write(json_dump)\n",
    "json_out.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mapping directly from the dataframe\n",
    "\n",
    "We lose all the group information with this method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Here we try to apply the nx method\n",
    "\n",
    "NG = nx.from_pandas_edgelist(dfgroup, source='source', target='target', edge_attr=True,)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NodeView(('10.52.3.1', '10.52.3.255', '10.52.3.8', '10.52.3.105', '224.0.0.22', '224.0.0.251', '10.52.3.15', '10.52.3.50', '91.189.94.4', '10.52.3.20', '239.255.255.250', '10.52.3.7', '131.186.113.70', '131.186.161.70', '162.88.193.70', '17.142.169.199', '17.248.130.8', '17.253.16.125', '17.253.16.253', '17.253.26.125', '17.253.4.253', '17.57.144.180', '172.217.14.202', '172.217.14.227', '172.217.14.238', '172.217.3.170', '184.26.80.199', '209.197.193.112', '209.197.193.90', '216.146.43.70', '216.146.43.71', '23.204.60.203', '23.52.168.63', '23.52.169.148', '3.213.160.221', '64.68.120.47', '72.21.91.29', '10.52.3.9', '17.57.144.181'))"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NG.nodes()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "EdgeView([('10.52.3.1', '10.52.3.255'), ('10.52.3.1', '10.52.3.8'), ('10.52.3.255', '10.52.3.50'), ('10.52.3.255', '10.52.3.8'), ('10.52.3.8', '10.52.3.50'), ('10.52.3.8', '10.52.3.105'), ('10.52.3.8', '131.186.113.70'), ('10.52.3.8', '131.186.161.70'), ('10.52.3.8', '162.88.193.70'), ('10.52.3.8', '17.142.169.199'), ('10.52.3.8', '17.248.130.8'), ('10.52.3.8', '17.253.16.125'), ('10.52.3.8', '17.253.16.253'), ('10.52.3.8', '17.253.26.125'), ('10.52.3.8', '17.253.4.253'), ('10.52.3.8', '17.57.144.180'), ('10.52.3.8', '172.217.14.202'), ('10.52.3.8', '172.217.14.227'), ('10.52.3.8', '172.217.14.238'), ('10.52.3.8', '172.217.3.170'), ('10.52.3.8', '184.26.80.199'), ('10.52.3.8', '209.197.193.112'), ('10.52.3.8', '209.197.193.90'), ('10.52.3.8', '216.146.43.70'), ('10.52.3.8', '216.146.43.71'), ('10.52.3.8', '224.0.0.251'), ('10.52.3.8', '23.204.60.203'), ('10.52.3.8', '23.52.168.63'), ('10.52.3.8', '23.52.169.148'), ('10.52.3.8', '239.255.255.250'), ('10.52.3.8', '3.213.160.221'), ('10.52.3.8', '64.68.120.47'), ('10.52.3.8', '72.21.91.29'), ('10.52.3.105', '224.0.0.22'), ('10.52.3.105', '224.0.0.251'), ('10.52.3.105', '10.52.3.9'), ('224.0.0.251', '10.52.3.15'), ('224.0.0.251', '10.52.3.20'), ('224.0.0.251', '10.52.3.50'), ('224.0.0.251', '10.52.3.7'), ('224.0.0.251', '10.52.3.9'), ('10.52.3.15', '10.52.3.50'), ('10.52.3.15', '91.189.94.4'), ('10.52.3.50', '10.52.3.20'), ('10.52.3.50', '239.255.255.250'), ('239.255.255.250', '10.52.3.7'), ('10.52.3.9', '17.57.144.181')])"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NG.edges()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "nx.draw_networkx(NG, with_labels=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'10.52.3.1': 0.05263157894736842,\n",
       " '10.52.3.255': 0.07894736842105263,\n",
       " '10.52.3.8': 0.8157894736842105,\n",
       " '10.52.3.105': 0.10526315789473684,\n",
       " '224.0.0.22': 0.02631578947368421,\n",
       " '224.0.0.251': 0.18421052631578946,\n",
       " '10.52.3.15': 0.07894736842105263,\n",
       " '10.52.3.50': 0.15789473684210525,\n",
       " '91.189.94.4': 0.02631578947368421,\n",
       " '10.52.3.20': 0.05263157894736842,\n",
       " '239.255.255.250': 0.07894736842105263,\n",
       " '10.52.3.7': 0.05263157894736842,\n",
       " '131.186.113.70': 0.02631578947368421,\n",
       " '131.186.161.70': 0.02631578947368421,\n",
       " '162.88.193.70': 0.02631578947368421,\n",
       " '17.142.169.199': 0.02631578947368421,\n",
       " '17.248.130.8': 0.02631578947368421,\n",
       " '17.253.16.125': 0.02631578947368421,\n",
       " '17.253.16.253': 0.02631578947368421,\n",
       " '17.253.26.125': 0.02631578947368421,\n",
       " '17.253.4.253': 0.02631578947368421,\n",
       " '17.57.144.180': 0.02631578947368421,\n",
       " '172.217.14.202': 0.02631578947368421,\n",
       " '172.217.14.227': 0.02631578947368421,\n",
       " '172.217.14.238': 0.02631578947368421,\n",
       " '172.217.3.170': 0.02631578947368421,\n",
       " '184.26.80.199': 0.02631578947368421,\n",
       " '209.197.193.112': 0.02631578947368421,\n",
       " '209.197.193.90': 0.02631578947368421,\n",
       " '216.146.43.70': 0.02631578947368421,\n",
       " '216.146.43.71': 0.02631578947368421,\n",
       " '23.204.60.203': 0.02631578947368421,\n",
       " '23.52.168.63': 0.02631578947368421,\n",
       " '23.52.169.148': 0.02631578947368421,\n",
       " '3.213.160.221': 0.02631578947368421,\n",
       " '64.68.120.47': 0.02631578947368421,\n",
       " '72.21.91.29': 0.02631578947368421,\n",
       " '10.52.3.9': 0.07894736842105263,\n",
       " '17.57.144.181': 0.02631578947368421}"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.algorithms.degree_centrality(NG)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.06342780026990553"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.density(NG)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.292847503373819"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.average_shortest_path_length(NG) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{2: 9.5,\n",
       " 3: 8.666666666666666,\n",
       " 31: 1.6129032258064515,\n",
       " 4: 10.5,\n",
       " 1: 28.035714285714285,\n",
       " 7: 7.285714285714286,\n",
       " 6: 8.166666666666666}"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.average_degree_connectivity(NG) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['10.52.3.50', '10.52.3.8', '209.197.193.90']"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.dijkstra_path(NG, source='10.52.3.50', target='209.197.193.90')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### can we add colors to nodes with higher counts?\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('links',\n",
       "  [{'value': 12, 'source': 0, 'target': 35},\n",
       "   {'value': 47, 'source': 0, 'target': 6},\n",
       "   {'value': 39, 'source': 1, 'target': 36},\n",
       "   {'value': 135, 'source': 1, 'target': 37},\n",
       "   {'value': 73, 'source': 2, 'target': 4},\n",
       "   {'value': 4, 'source': 2, 'target': 37},\n",
       "   {'value': 4, 'source': 2, 'target': 34},\n",
       "   {'value': 63, 'source': 3, 'target': 4},\n",
       "   {'value': 65, 'source': 3, 'target': 37},\n",
       "   {'value': 146, 'source': 4, 'target': 2},\n",
       "   {'value': 63, 'source': 4, 'target': 3},\n",
       "   {'value': 16, 'source': 4, 'target': 35},\n",
       "   {'value': 4505, 'source': 4, 'target': 6},\n",
       "   {'value': 113, 'source': 4, 'target': 37},\n",
       "   {'value': 148, 'source': 4, 'target': 38},\n",
       "   {'value': 3, 'source': 5, 'target': 37},\n",
       "   {'value': 96, 'source': 5, 'target': 38},\n",
       "   {'value': 61, 'source': 6, 'target': 0},\n",
       "   {'value': 36, 'source': 6, 'target': 1},\n",
       "   {'value': 16, 'source': 6, 'target': 35},\n",
       "   {'value': 4073, 'source': 6, 'target': 4},\n",
       "   {'value': 12, 'source': 6, 'target': 8},\n",
       "   {'value': 18, 'source': 6, 'target': 9},\n",
       "   {'value': 12, 'source': 6, 'target': 10},\n",
       "   {'value': 18, 'source': 6, 'target': 11},\n",
       "   {'value': 122, 'source': 6, 'target': 12},\n",
       "   {'value': 2, 'source': 6, 'target': 13},\n",
       "   {'value': 1, 'source': 6, 'target': 14},\n",
       "   {'value': 2, 'source': 6, 'target': 15},\n",
       "   {'value': 1, 'source': 6, 'target': 16},\n",
       "   {'value': 36, 'source': 6, 'target': 17},\n",
       "   {'value': 11, 'source': 6, 'target': 19},\n",
       "   {'value': 12, 'source': 6, 'target': 20},\n",
       "   {'value': 30, 'source': 6, 'target': 21},\n",
       "   {'value': 6, 'source': 6, 'target': 22},\n",
       "   {'value': 16, 'source': 6, 'target': 23},\n",
       "   {'value': 21, 'source': 6, 'target': 24},\n",
       "   {'value': 446, 'source': 6, 'target': 25},\n",
       "   {'value': 30, 'source': 6, 'target': 26},\n",
       "   {'value': 18, 'source': 6, 'target': 27},\n",
       "   {'value': 17, 'source': 6, 'target': 37},\n",
       "   {'value': 15, 'source': 6, 'target': 28},\n",
       "   {'value': 28, 'source': 6, 'target': 29},\n",
       "   {'value': 57, 'source': 6, 'target': 30},\n",
       "   {'value': 144, 'source': 6, 'target': 38},\n",
       "   {'value': 23, 'source': 6, 'target': 31},\n",
       "   {'value': 42, 'source': 6, 'target': 32},\n",
       "   {'value': 12, 'source': 6, 'target': 33},\n",
       "   {'value': 41, 'source': 7, 'target': 1},\n",
       "   {'value': 4, 'source': 7, 'target': 18},\n",
       "   {'value': 10, 'source': 7, 'target': 37},\n",
       "   {'value': 10, 'source': 8, 'target': 6},\n",
       "   {'value': 15, 'source': 9, 'target': 6},\n",
       "   {'value': 10, 'source': 10, 'target': 6},\n",
       "   {'value': 14, 'source': 11, 'target': 6},\n",
       "   {'value': 75, 'source': 12, 'target': 6},\n",
       "   {'value': 2, 'source': 13, 'target': 6},\n",
       "   {'value': 1, 'source': 14, 'target': 6},\n",
       "   {'value': 2, 'source': 15, 'target': 6},\n",
       "   {'value': 1, 'source': 16, 'target': 6},\n",
       "   {'value': 22, 'source': 17, 'target': 6},\n",
       "   {'value': 2, 'source': 18, 'target': 7},\n",
       "   {'value': 9, 'source': 19, 'target': 6},\n",
       "   {'value': 8, 'source': 20, 'target': 6},\n",
       "   {'value': 18, 'source': 21, 'target': 6},\n",
       "   {'value': 5, 'source': 22, 'target': 6},\n",
       "   {'value': 12, 'source': 23, 'target': 6},\n",
       "   {'value': 17, 'source': 24, 'target': 6},\n",
       "   {'value': 319, 'source': 25, 'target': 6},\n",
       "   {'value': 25, 'source': 26, 'target': 6},\n",
       "   {'value': 15, 'source': 27, 'target': 6},\n",
       "   {'value': 10, 'source': 28, 'target': 6},\n",
       "   {'value': 20, 'source': 29, 'target': 6},\n",
       "   {'value': 36, 'source': 30, 'target': 6},\n",
       "   {'value': 17, 'source': 31, 'target': 6},\n",
       "   {'value': 34, 'source': 32, 'target': 6},\n",
       "   {'value': 10, 'source': 33, 'target': 6},\n",
       "   {'value': 3, 'source': 34, 'target': 2}]),\n",
       " ('nodes',\n",
       "  [{'name': '10.52.3.1', 'group': 1},\n",
       "   {'name': '10.52.3.105', 'group': 1},\n",
       "   {'name': '10.52.3.15', 'group': 1},\n",
       "   {'name': '10.52.3.20', 'group': 1},\n",
       "   {'name': '10.52.3.50', 'group': 1},\n",
       "   {'name': '10.52.3.7', 'group': 1},\n",
       "   {'name': '10.52.3.8', 'group': 1},\n",
       "   {'name': '10.52.3.9', 'group': 1},\n",
       "   {'name': '131.186.113.70', 'group': 2},\n",
       "   {'name': '131.186.161.70', 'group': 3},\n",
       "   {'name': '162.88.193.70', 'group': 4},\n",
       "   {'name': '17.142.169.199', 'group': 5},\n",
       "   {'name': '17.248.130.8', 'group': 6},\n",
       "   {'name': '17.253.16.125', 'group': 7},\n",
       "   {'name': '17.253.16.253', 'group': 7},\n",
       "   {'name': '17.253.26.125', 'group': 8},\n",
       "   {'name': '17.253.4.253', 'group': 9},\n",
       "   {'name': '17.57.144.180', 'group': 10},\n",
       "   {'name': '17.57.144.181', 'group': 10},\n",
       "   {'name': '172.217.14.202', 'group': 11},\n",
       "   {'name': '172.217.14.227', 'group': 11},\n",
       "   {'name': '172.217.14.238', 'group': 11},\n",
       "   {'name': '172.217.3.170', 'group': 12},\n",
       "   {'name': '184.26.80.199', 'group': 13},\n",
       "   {'name': '209.197.193.112', 'group': 14},\n",
       "   {'name': '209.197.193.90', 'group': 14},\n",
       "   {'name': '216.146.43.70', 'group': 15},\n",
       "   {'name': '216.146.43.71', 'group': 15},\n",
       "   {'name': '23.204.60.203', 'group': 16},\n",
       "   {'name': '23.52.168.63', 'group': 17},\n",
       "   {'name': '23.52.169.148', 'group': 18},\n",
       "   {'name': '3.213.160.221', 'group': 19},\n",
       "   {'name': '64.68.120.47', 'group': 20},\n",
       "   {'name': '72.21.91.29', 'group': 21},\n",
       "   {'name': '91.189.94.4', 'group': 22},\n",
       "   {'name': '10.52.3.255', 'group': 1},\n",
       "   {'name': '224.0.0.22', 'group': 23},\n",
       "   {'name': '224.0.0.251', 'group': 23},\n",
       "   {'name': '239.255.255.250', 'group': 24}])]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(json_prep.items())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "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>source</th>\n",
       "      <th>target</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.52.3.1</td>\n",
       "      <td>10.52.3.255</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.52.3.1</td>\n",
       "      <td>10.52.3.8</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.52.3.105</td>\n",
       "      <td>224.0.0.22</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10.52.3.105</td>\n",
       "      <td>224.0.0.251</td>\n",
       "      <td>135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.52.3.15</td>\n",
       "      <td>10.52.3.50</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        source       target  count\n",
       "0    10.52.3.1  10.52.3.255     12\n",
       "1    10.52.3.1    10.52.3.8     47\n",
       "2  10.52.3.105   224.0.0.22     39\n",
       "3  10.52.3.105  224.0.0.251    135\n",
       "4   10.52.3.15   10.52.3.50     73"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfgroup.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "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>source</th>\n",
       "      <th>target</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>10.52.3.50</td>\n",
       "      <td>10.52.3.8</td>\n",
       "      <td>4505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>10.52.3.8</td>\n",
       "      <td>10.52.3.50</td>\n",
       "      <td>4073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>10.52.3.8</td>\n",
       "      <td>209.197.193.90</td>\n",
       "      <td>446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>209.197.193.90</td>\n",
       "      <td>10.52.3.8</td>\n",
       "      <td>319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>10.52.3.50</td>\n",
       "      <td>239.255.255.250</td>\n",
       "      <td>148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10.52.3.50</td>\n",
       "      <td>10.52.3.15</td>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>10.52.3.8</td>\n",
       "      <td>239.255.255.250</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10.52.3.105</td>\n",
       "      <td>224.0.0.251</td>\n",
       "      <td>135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>10.52.3.8</td>\n",
       "      <td>17.248.130.8</td>\n",
       "      <td>122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>10.52.3.50</td>\n",
       "      <td>224.0.0.251</td>\n",
       "      <td>113</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            source           target  count\n",
       "12      10.52.3.50        10.52.3.8   4505\n",
       "20       10.52.3.8       10.52.3.50   4073\n",
       "37       10.52.3.8   209.197.193.90    446\n",
       "68  209.197.193.90        10.52.3.8    319\n",
       "14      10.52.3.50  239.255.255.250    148\n",
       "9       10.52.3.50       10.52.3.15    146\n",
       "44       10.52.3.8  239.255.255.250    144\n",
       "3      10.52.3.105      224.0.0.251    135\n",
       "25       10.52.3.8     17.248.130.8    122\n",
       "13      10.52.3.50      224.0.0.251    113"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfgroup.sort_values('count', ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "source    object\n",
       "target    object\n",
       "count      int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfgroup.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Side trip - can we get hostnames?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10.52.3.1 10.52.3.1\n",
      "10.52.3.1 10.52.3.1\n"
     ]
    }
   ],
   "source": [
    "#socket.gethostbyaddr('203.208.60.1')\n",
    "for i, v in dfgroup.head(2).iterrows():\n",
    "    print(v['source'], v['source'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('a23-204-60-203.deploy.static.akamaitechnologies.com',\n",
       " ['203.60.204.23.in-addr.arpa'],\n",
       " ['23.204.60.203'])"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "socket.gethostbyaddr('23.204.60.203')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'uslax1-ntp-001.aaplimg.com'"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "socket.gethostbyaddr('17.253.26.125')[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'203.60.204.23.in-addr.arpa'"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "socket.gethostbyaddr('23.204.60.203')[1][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "# socket.gethostbyaddr('17.253.26.125')\n",
    "# # sourcename=''\n",
    "# # targetname=''\n",
    "# for i, v in dfgroup.head(20).iterrows():\n",
    "#     print(v)\n",
    "#     try:\n",
    "#         sourcename, targetname = socket.gethostbyaddr(v['source']),socket.gethostbyaddr(v['target']) \n",
    "#     except Exception as e: \n",
    "#         print('Error at', e)\n",
    "#     if sourcename is None:\n",
    "#         sourcename = socket.gethostbyaddr(v['source'])\n",
    "#     if targetname is None:\n",
    "#         targetname = socket.gethostbyaddr(v['target'])\n",
    "#     print(sourcename)\n",
    "#     if sourcename:\n",
    "#         print(\"Source: \", sourcename[0], \"Target: \", targetname[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'10.52.3.15'"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['source'][1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "ename": "herror",
     "evalue": "[Errno 1] Unknown host",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mherror\u001b[0m                                    Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-88-87365416bbb1>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0msocket\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgethostbyaddr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'source'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mherror\u001b[0m: [Errno 1] Unknown host"
     ]
    }
   ],
   "source": [
    "socket.gethostbyaddr(df['source'][1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def hostname(ip):\n",
    "    \"attempts to resolve a hostname\"\n",
    "    mcast = ['224.0.0.251', '224.0.0.1','224.0.0.2','224.0.0.22']\n",
    "    if ip in mcast:\n",
    "        return 'multicast'\n",
    "    elif ip == '192.168.1.255':\n",
    "        return 'broadcast'\n",
    "    elif ip == '239.255.255.250':\n",
    "        return 'SSDP'\n",
    "    else:\n",
    "        try:\n",
    "            if socket.gethostbyaddr(ip):\n",
    "                return socket.gethostbyaddr(ip)[0]\n",
    "        except:\n",
    "            return ip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hostname(df['source'][1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hostname(df['source'][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['tar'][1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfgroup.drop(columns=['sourcename','targetname'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfgroup['sourcename'], dfgroup['targetname'] = dfgroup['source'].apply(hostname), dfgroup['target'].apply(hostname)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfgroup"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ok - added!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ng2 = nx.from_pandas_edgelist(dfgroup, source='sourcename', target='targetname', edge_attr=True,)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(20,15))\n",
    "nx.draw_networkx(ng2, with_labels=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(12,5))\n",
    "plt.xticks(rotation=45, ha='right',horizontalalignment='right')\n",
    "plt.tight_layout(pad=0)\n",
    "sns.countplot('sourcename',data=dfgroup,palette='summer')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(12,5))\n",
    "plt.xticks(rotation=45, ha='right',horizontalalignment='right')\n",
    "plt.tight_layout(pad=0)\n",
    "sns.countplot('targetname',data=dfgroup,palette='summer')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### networkx with the extracted json\n",
    "\n",
    "Trying to make the extracted json work with networkx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "NG.nodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "from itertools import count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "g = nx.Graph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "groups = set(nx.get_node_attributes(g,'group').values())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['nodes', 'links'])"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_prep.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'name': '10.52.3.1', 'group': 1}"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_prep['nodes'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_items([('value', 47), ('source', 0), ('target', 6)])"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_prep['links'][1].items()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_prep['links'][0]['value']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "# g = nx.Graph(json_prep['nodes']) #doesn't take all in\n",
    "g = nx.Graph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "for x in range(0,len(json_prep['nodes'])):\n",
    "    g.add_node(json_prep['nodes'][x]['name'],group=json_prep['nodes'][x]['group'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "for x in range(0,len(json_prep['links'])):\n",
    "    g.add_edge(json_prep['links'][x]['source'], json_prep['links'][x]['target'],value=json_prep['links'][x]['value'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# not fantastic. Can't read groups, no directed edge lines\n",
    "nx.draw(g, with_labels=True, node_size=15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#fix the scale with pydot - still not much better. Edgelines, but no sense of group to IP\n",
    "nx.draw(g, pos = nx.nx_pydot.graphviz_layout(g), with_labels=True, node_size=15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NodeDataView({'10.52.3.1': {'group': 1}, '10.52.3.105': {'group': 1}, '10.52.3.15': {'group': 1}, '10.52.3.20': {'group': 1}, '10.52.3.50': {'group': 1}, '10.52.3.7': {'group': 1}, '10.52.3.8': {'group': 1}, '10.52.3.9': {'group': 1}, '131.186.113.70': {'group': 2}, '131.186.161.70': {'group': 3}, '162.88.193.70': {'group': 4}, '17.142.169.199': {'group': 5}, '17.248.130.8': {'group': 6}, '17.253.16.125': {'group': 7}, '17.253.16.253': {'group': 7}, '17.253.26.125': {'group': 8}, '17.253.4.253': {'group': 9}, '17.57.144.180': {'group': 10}, '17.57.144.181': {'group': 10}, '172.217.14.202': {'group': 11}, '172.217.14.227': {'group': 11}, '172.217.14.238': {'group': 11}, '172.217.3.170': {'group': 12}, '184.26.80.199': {'group': 13}, '209.197.193.112': {'group': 14}, '209.197.193.90': {'group': 14}, '216.146.43.70': {'group': 15}, '216.146.43.71': {'group': 15}, '23.204.60.203': {'group': 16}, '23.52.168.63': {'group': 17}, '23.52.169.148': {'group': 18}, '3.213.160.221': {'group': 19}, '64.68.120.47': {'group': 20}, '72.21.91.29': {'group': 21}, '91.189.94.4': {'group': 22}, '10.52.3.255': {'group': 1}, '224.0.0.22': {'group': 23}, '224.0.0.251': {'group': 23}, '239.255.255.250': {'group': 24}, 0: {}, 35: {}, 6: {}, 1: {}, 36: {}, 37: {}, 2: {}, 4: {}, 34: {}, 3: {}, 38: {}, 5: {}, 8: {}, 9: {}, 10: {}, 11: {}, 12: {}, 13: {}, 14: {}, 15: {}, 16: {}, 17: {}, 19: {}, 20: {}, 21: {}, 22: {}, 23: {}, 24: {}, 25: {}, 26: {}, 27: {}, 28: {}, 29: {}, 30: {}, 31: {}, 32: {}, 33: {}, 7: {}, 18: {}})"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g.nodes(data=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "EdgeDataView([(0, 35, {'value': 12}), (0, 6, {'value': 61}), (35, 4, {'value': 16}), (35, 6, {'value': 16}), (6, 4, {'value': 4073}), (6, 1, {'value': 36}), (6, 8, {'value': 10}), (6, 9, {'value': 15}), (6, 10, {'value': 10}), (6, 11, {'value': 14}), (6, 12, {'value': 75}), (6, 13, {'value': 2}), (6, 14, {'value': 1}), (6, 15, {'value': 2}), (6, 16, {'value': 1}), (6, 17, {'value': 22}), (6, 19, {'value': 9}), (6, 20, {'value': 8}), (6, 21, {'value': 18}), (6, 22, {'value': 5}), (6, 23, {'value': 12}), (6, 24, {'value': 17}), (6, 25, {'value': 319}), (6, 26, {'value': 25}), (6, 27, {'value': 15}), (6, 37, {'value': 17}), (6, 28, {'value': 10}), (6, 29, {'value': 20}), (6, 30, {'value': 36}), (6, 38, {'value': 144}), (6, 31, {'value': 17}), (6, 32, {'value': 34}), (6, 33, {'value': 10}), (1, 36, {'value': 39}), (1, 37, {'value': 135}), (1, 7, {'value': 41}), (37, 2, {'value': 4}), (37, 3, {'value': 65}), (37, 4, {'value': 113}), (37, 5, {'value': 3}), (37, 7, {'value': 10}), (2, 4, {'value': 146}), (2, 34, {'value': 3}), (4, 3, {'value': 63}), (4, 38, {'value': 148}), (38, 5, {'value': 96}), (7, 18, {'value': 2})])"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g.edges(data=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{(0, 35): 12,\n",
       " (0, 6): 61,\n",
       " (35, 4): 16,\n",
       " (35, 6): 16,\n",
       " (6, 4): 4073,\n",
       " (6, 1): 36,\n",
       " (6, 8): 10,\n",
       " (6, 9): 15,\n",
       " (6, 10): 10,\n",
       " (6, 11): 14,\n",
       " (6, 12): 75,\n",
       " (6, 13): 2,\n",
       " (6, 14): 1,\n",
       " (6, 15): 2,\n",
       " (6, 16): 1,\n",
       " (6, 17): 22,\n",
       " (6, 19): 9,\n",
       " (6, 20): 8,\n",
       " (6, 21): 18,\n",
       " (6, 22): 5,\n",
       " (6, 23): 12,\n",
       " (6, 24): 17,\n",
       " (6, 25): 319,\n",
       " (6, 26): 25,\n",
       " (6, 27): 15,\n",
       " (6, 37): 17,\n",
       " (6, 28): 10,\n",
       " (6, 29): 20,\n",
       " (6, 30): 36,\n",
       " (6, 38): 144,\n",
       " (6, 31): 17,\n",
       " (6, 32): 34,\n",
       " (6, 33): 10,\n",
       " (1, 36): 39,\n",
       " (1, 37): 135,\n",
       " (1, 7): 41,\n",
       " (37, 2): 4,\n",
       " (37, 3): 65,\n",
       " (37, 4): 113,\n",
       " (37, 5): 3,\n",
       " (37, 7): 10,\n",
       " (2, 4): 146,\n",
       " (2, 34): 3,\n",
       " (4, 3): 63,\n",
       " (4, 38): 148,\n",
       " (38, 5): 96,\n",
       " (7, 18): 2}"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.get_edge_attributes(g,'value')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Now to try the color example (not working yet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_values([1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 10, 11, 11, 11, 12, 13, 14, 14, 15, 15, 16, 17, 18, 19, 20, 21, 22, 1, 23, 23, 24])"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.get_node_attributes(g,'group').values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "groups = set(nx.get_node_attributes(g,'group').values())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "mapping = dict(zip(sorted(groups),count()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "nodes = g.nodes()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10.52.3.1\n",
      "10.52.3.105\n",
      "10.52.3.15\n",
      "10.52.3.20\n",
      "10.52.3.50\n",
      "10.52.3.7\n",
      "10.52.3.8\n",
      "10.52.3.9\n",
      "131.186.113.70\n",
      "131.186.161.70\n",
      "162.88.193.70\n",
      "17.142.169.199\n",
      "17.248.130.8\n",
      "17.253.16.125\n",
      "17.253.16.253\n",
      "17.253.26.125\n",
      "17.253.4.253\n",
      "17.57.144.180\n",
      "17.57.144.181\n",
      "172.217.14.202\n",
      "172.217.14.227\n",
      "172.217.14.238\n",
      "172.217.3.170\n",
      "184.26.80.199\n",
      "209.197.193.112\n",
      "209.197.193.90\n",
      "216.146.43.70\n",
      "216.146.43.71\n",
      "23.204.60.203\n",
      "23.52.168.63\n",
      "23.52.169.148\n",
      "3.213.160.221\n",
      "64.68.120.47\n",
      "72.21.91.29\n",
      "91.189.94.4\n",
      "10.52.3.255\n",
      "224.0.0.22\n",
      "224.0.0.251\n",
      "239.255.255.250\n",
      "0\n",
      "35\n",
      "6\n",
      "1\n",
      "36\n",
      "37\n",
      "2\n",
      "4\n",
      "34\n",
      "3\n",
      "38\n",
      "5\n",
      "8\n",
      "9\n",
      "10\n",
      "11\n",
      "12\n",
      "13\n",
      "14\n",
      "15\n",
      "16\n",
      "17\n",
      "19\n",
      "20\n",
      "21\n",
      "22\n",
      "23\n",
      "24\n",
      "25\n",
      "26\n",
      "27\n",
      "28\n",
      "29\n",
      "30\n",
      "31\n",
      "32\n",
      "33\n",
      "7\n",
      "18\n"
     ]
    }
   ],
   "source": [
    "for x in g.nodes():\n",
    "    print(x)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'groups'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-109-96452a0f834a>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mg\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnodes\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'groups'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m: 'groups'"
     ]
    }
   ],
   "source": [
    "g.nodes[0]['groups']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "colors = [mapping[g.nodes[n]['group']] for n in nodes]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "nodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}