my example for data school

example_for_data_school.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "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>number_of_nodes</th>\n",
       "      <th>number_of_edges</th>\n",
       "      <th>avg_shortest_path</th>\n",
       "      <th>transitivity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>58</td>\n",
       "      <td>363</td>\n",
       "      <td>11.274652</td>\n",
       "      <td>0.990460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>35</td>\n",
       "      <td>64</td>\n",
       "      <td>10.470588</td>\n",
       "      <td>0.864198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>14</td>\n",
       "      <td>19</td>\n",
       "      <td>4.252747</td>\n",
       "      <td>0.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>28</td>\n",
       "      <td>83</td>\n",
       "      <td>6.407407</td>\n",
       "      <td>0.950943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>26</td>\n",
       "      <td>55</td>\n",
       "      <td>7.030769</td>\n",
       "      <td>0.897436</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      number_of_nodes  number_of_edges  avg_shortest_path  transitivity\n",
       "2000               58              363          11.274652      0.990460\n",
       "2001               35               64          10.470588      0.864198\n",
       "2002               14               19           4.252747      0.666667\n",
       "2003               28               83           6.407407      0.950943\n",
       "2004               26               55           7.030769      0.897436"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import networkx as nx\n",
    "import pandas as pd\n",
    "import random\n",
    "\n",
    "years, graphs = list(zip(*[(year, nx.barbell_graph(random.randint(3,25),random.randint(3,25))) for year in range(2000,2005)]))\n",
    "df = pd.DataFrame({\"graph\": graphs}, index=years)\n",
    "\n",
    "df[\"number_of_nodes\"] = df.graph.apply(nx.number_of_nodes)\n",
    "df[\"number_of_edges\"] = df.graph.apply(nx.number_of_edges)\n",
    "df[\"avg_shortest_path\"] = df.graph.apply(nx.average_shortest_path_length)\n",
    "df[\"transitivity\"] = df.graph.apply(nx.transitivity)\n",
    "\n",
    "\n",
    "df.drop(\"graph\", axis=1)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The great thing about this is that you can easily compute multiple statistics at once and show them in a nice table."
   ]
  },
  {
   "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": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}