B_04_mobility_metrics_on_od_matrices.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "01066def",
   "metadata": {},
   "outputs": [],
   "source": [
    "import community\n",
    "import statistics\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import networkx as nx\n",
    "import geopandas as gpd\n",
    "from community import community_louvain\n",
    "import notebooks_loops_script as nls"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1bfb3bfc",
   "metadata": {},
   "source": [
    "# Calculating OD-matrix based mobility indictors\n",
    "Using the OD-Matrices calculated in Notebook B_02, further metrics are calculated here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "17e5e120",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Rolling Window Parameters\n",
    "start = \"20200406\"\n",
    "end = \"20200409\"\n",
    "denom = \"3days\"\n",
    "allow_even_subsets = False\n",
    "sam = False\n",
    "del_one_tweeters = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "336e5c7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "ref = \"statistics_notebookdemo/\" + denom + \"_overlap.csv\"\n",
    "if type(sam) == int:\n",
    "    ref = ref.split('.csv')[0] + \"_\" +str(sam) + \".csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "05b36d5f",
   "metadata": {},
   "outputs": [],
   "source": [
    "path = f\"data/{ref}\"\n",
    "file = pd.read_csv(f'data/{ref}', index_col='start_date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "db769d70",
   "metadata": {},
   "outputs": [],
   "source": [
    "middle = nls.middeling(start, end, allow_even_subsets=allow_even_subsets)\n",
    "mm_path = f'./data/movement_matrices_notebookdemo/{denom}/mm_{middle}.npy'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70221754",
   "metadata": {},
   "source": [
    "### Load in Shapefiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "42864dbc",
   "metadata": {},
   "outputs": [],
   "source": [
    "barrios_path = 'data/shps/neighborhoods.shp'\n",
    "barrios_20823 = gpd.read_file(barrios_path).to_crs(20823)\n",
    "\n",
    "barrios_20823.CODBAIRRO = barrios_20823.CODBAIRRO.astype(int)\n",
    "barrios_20823['geometry'] = barrios_20823.geometry.representative_point()# oder representative_point?\n",
    "barrios_20823['lat'] = barrios_20823['geometry'].y\n",
    "barrios_20823['lon'] = barrios_20823['geometry'].x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "82379829",
   "metadata": {},
   "outputs": [],
   "source": [
    "stats = {}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a86c1e4e",
   "metadata": {},
   "source": [
    "### Load in Movement Matrices\n",
    "Here, one movement matrix (or OD-Matrix) is loaded. In the notebook_loops_script.py all relevant matrices are loaded and processed via a loop."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "3403bc4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "mm = np.load(mm_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d542ca9f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# set diagonal, if the workflow from before was executed as intended, there should be no values on teh diagonal anyway.\n",
    "for i in range(mm.shape[0]):\n",
    "    mm[i,i] = 0\n",
    "        \n",
    "mm_normal = mm / mm.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "665a62d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# The amount of registered movements can be determined by the total sum of the OD matrix\n",
    "stats['no_real_movements'] = mm.sum().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7b74e0a",
   "metadata": {},
   "source": [
    "### Graph based modularity\n",
    "Caluclaute the Graph Modularity based on the community louvain package. If no graph can be constructed (that happens at some rolling windows with very few tweets) the value gets an np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d70e61bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "mm_for_modularity = mm + mm.T # This line is added after the comments of a reviever. Since G = nx.from_numpy_array(mm_for_modularity) later\n",
    "# only uses the lower triange in our OD-matrix, we need to add the transposed matrix on top of the original one. This ensures\n",
    "# that we have a symmetric matrix to calculate an undirected graph with it and all movements are taken into account. \n",
    "# We therefore do not differentiate if a user goes from district a to b or b to a. \n",
    "\n",
    "G = nx.from_numpy_array(mm_for_modularity)\n",
    "partition = community_louvain.best_partition(G, weight='weight')\n",
    "\n",
    "try:\n",
    "    stats['graph_modularity'] = community.modularity(partition, G)\n",
    "except:\n",
    "    print(\"Undefined Modularity!\")\n",
    "    stats['graph_modularity'] = np.nan\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b3d3cebb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'no_real_movements': 45.0, 'graph_modularity': 0.7965432098765433}"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58a4d8cf",
   "metadata": {},
   "source": [
    "### Inflow / Outflow per Barrio\n",
    "For each neighborhood, the inflow and outflow values get counted and saved."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "320f19db",
   "metadata": {},
   "outputs": [],
   "source": [
    "inflow = {}\n",
    "outflow = {}\n",
    "for i in range(mm.shape[0]): # y/rows\n",
    "    outflow['outflow_' + str(i+1) + '_barrio'] = mm[i, :].sum()\n",
    "\n",
    "for i in range(mm.shape[1]): # x/cols\n",
    "    inflow['inflow_' + str(i+1) + '_barrio'] = mm[:, i].sum()\n",
    "\n",
    "stats.update(inflow)\n",
    "stats.update(outflow)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acebcf23",
   "metadata": {},
   "source": [
    "### Mean \\# of Meaningful Connections (>= 5 %)\n",
    "Based on outgoing values, we calculate for each barrio the number of meaningful connections that make up 5 % or more of all outgoing connections. The mean of this number is saved."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "9cdec629",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Barrios with no outgoing/incoming connections will be ignored connections\n",
    "# [row, column]\n",
    "def number_of_meaningful_connections(outflow=False):\n",
    "    numbers_of_meaningful_connections = []\n",
    "    \n",
    "    for i in range(mm.shape[0]):\n",
    "        rel = mm[i, :]\n",
    "        if outflow:\n",
    "            rel = mm[:, i]\n",
    "    \n",
    "        outgoing_sum = rel.sum()\n",
    "        \n",
    "        # if we dont have any connections, continue -> ignore these barrios\n",
    "        if outgoing_sum == 0:\n",
    "            continue\n",
    "\n",
    "        outgoing_rel = rel / outgoing_sum\n",
    "        count = len(outgoing_rel[outgoing_rel >= 0.05])\n",
    "\n",
    "        numbers_of_meaningful_connections.append(count)\n",
    "    \n",
    "    return statistics.mean(numbers_of_meaningful_connections)\n",
    "    \n",
    "    \n",
    "stats['number_meaningful_incoming'] = number_of_meaningful_connections()\n",
    "stats['number_meaningful_outgoing'] = number_of_meaningful_connections(outflow=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e4e5c3e6",
   "metadata": {},
   "source": [
    "### Mean Distance to highest connection\n",
    "We calculate for each barrio the strongest partner and than the distances between its representatve points. The we calculate the mean between all barrios."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "91a30bb9",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_mean_distance_to_highest(outflow=False):\n",
    "    all_distances = []\n",
    "    for i in range(mm.shape[0]):\n",
    "        # list, in case it's multiple barrios\n",
    "        distances = []\n",
    "\n",
    "        rel = mm[i, :]\n",
    "        if outflow:\n",
    "            rel = mm[:, i]\n",
    "\n",
    "        # if we dont have any connections, continue -> ignore these barrios\n",
    "        if sum(rel) == 0:\n",
    "            continue\n",
    "\n",
    "        l = []\n",
    "        l.extend(list(np.where(rel == max(rel))[0]))\n",
    "\n",
    "        for partner in l:\n",
    "            partner += 1\n",
    "            og = barrios_20823.loc[barrios_20823.CODBAIRRO == i+1].geometry.values[0]\n",
    "            comp = barrios_20823.loc[barrios_20823.CODBAIRRO == partner].geometry.values[0]\n",
    "            distances.append(og.distance(comp))\n",
    "\n",
    "        #print(distances)\n",
    "        all_distances.append(statistics.mean(distances))\n",
    "\n",
    "    return statistics.mean(all_distances)\n",
    "\n",
    "stats['mean_distance_strongest_inflow'] = get_mean_distance_to_highest(outflow=False)\n",
    "stats['mean_distance_strongest_outflow'] = get_mean_distance_to_highest(outflow=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "49a0341a",
   "metadata": {},
   "outputs": [],
   "source": [
    "start = int(start)\n",
    "for name, val in stats.items():\n",
    "    file.loc[start, name] = val\n",
    "    \n",
    "file.to_csv(f'data/{ref}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "24cb6149",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "no_real_movements : 45.0\n",
      "graph_modularity : 0.7965432098765433\n",
      "inflow_1_barrio : 0.0\n",
      "inflow_2_barrio : 0.0\n",
      "inflow_3_barrio : 0.0\n",
      "inflow_4_barrio : 0.0\n",
      "inflow_5_barrio : 3.0\n",
      "inflow_6_barrio : 0.0\n",
      "inflow_7_barrio : 0.0\n",
      "inflow_8_barrio : 0.0\n",
      "inflow_9_barrio : 0.0\n",
      "inflow_10_barrio : 0.0\n",
      "inflow_11_barrio : 0.0\n",
      "inflow_12_barrio : 1.0\n",
      "inflow_13_barrio : 0.0\n",
      "inflow_14_barrio : 0.0\n",
      "inflow_15_barrio : 0.0\n",
      "inflow_16_barrio : 0.0\n",
      "inflow_17_barrio : 0.0\n",
      "inflow_18_barrio : 0.0\n",
      "inflow_19_barrio : 0.0\n",
      "inflow_20_barrio : 0.0\n",
      "inflow_21_barrio : 0.0\n",
      "inflow_22_barrio : 1.0\n",
      "inflow_23_barrio : 0.0\n",
      "inflow_24_barrio : 0.0\n",
      "inflow_25_barrio : 1.0\n",
      "inflow_26_barrio : 0.0\n",
      "inflow_27_barrio : 0.0\n",
      "inflow_28_barrio : 0.0\n",
      "inflow_29_barrio : 0.0\n",
      "inflow_30_barrio : 0.0\n",
      "inflow_31_barrio : 0.0\n",
      "inflow_32_barrio : 0.0\n",
      "inflow_33_barrio : 0.0\n",
      "inflow_34_barrio : 0.0\n",
      "inflow_35_barrio : 1.0\n",
      "inflow_36_barrio : 0.0\n",
      "inflow_37_barrio : 0.0\n",
      "inflow_38_barrio : 2.0\n",
      "inflow_39_barrio : 1.0\n",
      "inflow_40_barrio : 0.0\n",
      "inflow_41_barrio : 0.0\n",
      "inflow_42_barrio : 0.0\n",
      "inflow_43_barrio : 1.0\n",
      "inflow_44_barrio : 0.0\n",
      "inflow_45_barrio : 0.0\n",
      "inflow_46_barrio : 0.0\n",
      "inflow_47_barrio : 0.0\n",
      "inflow_48_barrio : 0.0\n",
      "inflow_49_barrio : 1.0\n",
      "inflow_50_barrio : 0.0\n",
      "inflow_51_barrio : 2.0\n",
      "inflow_52_barrio : 0.0\n",
      "inflow_53_barrio : 0.0\n",
      "inflow_54_barrio : 0.0\n",
      "inflow_55_barrio : 0.0\n",
      "inflow_56_barrio : 1.0\n",
      "inflow_57_barrio : 0.0\n",
      "inflow_58_barrio : 0.0\n",
      "inflow_59_barrio : 0.0\n",
      "inflow_60_barrio : 0.0\n",
      "inflow_61_barrio : 2.0\n",
      "inflow_62_barrio : 0.0\n",
      "inflow_63_barrio : 0.0\n",
      "inflow_64_barrio : 0.0\n",
      "inflow_65_barrio : 1.0\n",
      "inflow_66_barrio : 1.0\n",
      "inflow_67_barrio : 0.0\n",
      "inflow_68_barrio : 0.0\n",
      "inflow_69_barrio : 0.0\n",
      "inflow_70_barrio : 0.0\n",
      "inflow_71_barrio : 0.0\n",
      "inflow_72_barrio : 0.0\n",
      "inflow_73_barrio : 0.0\n",
      "inflow_74_barrio : 0.0\n",
      "inflow_75_barrio : 1.0\n",
      "inflow_76_barrio : 0.0\n",
      "inflow_77_barrio : 0.0\n",
      "inflow_78_barrio : 0.0\n",
      "inflow_79_barrio : 0.0\n",
      "inflow_80_barrio : 0.0\n",
      "inflow_81_barrio : 0.0\n",
      "inflow_82_barrio : 0.0\n",
      "inflow_83_barrio : 3.0\n",
      "inflow_84_barrio : 0.0\n",
      "inflow_85_barrio : 0.0\n",
      "inflow_86_barrio : 0.0\n",
      "inflow_87_barrio : 1.0\n",
      "inflow_88_barrio : 1.0\n",
      "inflow_89_barrio : 0.0\n",
      "inflow_90_barrio : 0.0\n",
      "inflow_91_barrio : 0.0\n",
      "inflow_92_barrio : 0.0\n",
      "inflow_93_barrio : 0.0\n",
      "inflow_94_barrio : 0.0\n",
      "inflow_95_barrio : 0.0\n",
      "inflow_96_barrio : 0.0\n",
      "inflow_97_barrio : 0.0\n",
      "inflow_98_barrio : 0.0\n",
      "inflow_99_barrio : 0.0\n",
      "inflow_100_barrio : 0.0\n",
      "inflow_101_barrio : 0.0\n",
      "inflow_102_barrio : 0.0\n",
      "inflow_103_barrio : 0.0\n",
      "inflow_104_barrio : 0.0\n",
      "inflow_105_barrio : 0.0\n",
      "inflow_106_barrio : 0.0\n",
      "inflow_107_barrio : 0.0\n",
      "inflow_108_barrio : 0.0\n",
      "inflow_109_barrio : 1.0\n",
      "inflow_110_barrio : 0.0\n",
      "inflow_111_barrio : 0.0\n",
      "inflow_112_barrio : 0.0\n",
      "inflow_113_barrio : 0.0\n",
      "inflow_114_barrio : 1.0\n",
      "inflow_115_barrio : 0.0\n",
      "inflow_116_barrio : 0.0\n",
      "inflow_117_barrio : 0.0\n",
      "inflow_118_barrio : 0.0\n",
      "inflow_119_barrio : 0.0\n",
      "inflow_120_barrio : 0.0\n",
      "inflow_121_barrio : 0.0\n",
      "inflow_122_barrio : 0.0\n",
      "inflow_123_barrio : 0.0\n",
      "inflow_124_barrio : 1.0\n",
      "inflow_125_barrio : 0.0\n",
      "inflow_126_barrio : 0.0\n",
      "inflow_127_barrio : 0.0\n",
      "inflow_128_barrio : 0.0\n",
      "inflow_129_barrio : 0.0\n",
      "inflow_130_barrio : 0.0\n",
      "inflow_131_barrio : 0.0\n",
      "inflow_132_barrio : 3.0\n",
      "inflow_133_barrio : 1.0\n",
      "inflow_134_barrio : 0.0\n",
      "inflow_135_barrio : 0.0\n",
      "inflow_136_barrio : 0.0\n",
      "inflow_137_barrio : 0.0\n",
      "inflow_138_barrio : 0.0\n",
      "inflow_139_barrio : 0.0\n",
      "inflow_140_barrio : 0.0\n",
      "inflow_141_barrio : 2.0\n",
      "inflow_142_barrio : 0.0\n",
      "inflow_143_barrio : 0.0\n",
      "inflow_144_barrio : 1.0\n",
      "inflow_145_barrio : 0.0\n",
      "inflow_146_barrio : 0.0\n",
      "inflow_147_barrio : 1.0\n",
      "inflow_148_barrio : 1.0\n",
      "inflow_149_barrio : 2.0\n",
      "inflow_150_barrio : 0.0\n",
      "inflow_151_barrio : 1.0\n",
      "inflow_152_barrio : 0.0\n",
      "inflow_153_barrio : 0.0\n",
      "inflow_154_barrio : 1.0\n",
      "inflow_155_barrio : 0.0\n",
      "inflow_156_barrio : 0.0\n",
      "inflow_157_barrio : 2.0\n",
      "inflow_158_barrio : 0.0\n",
      "inflow_159_barrio : 0.0\n",
      "inflow_160_barrio : 0.0\n",
      "inflow_161_barrio : 2.0\n",
      "inflow_162_barrio : 0.0\n",
      "inflow_163_barrio : 0.0\n",
      "outflow_1_barrio : 0.0\n",
      "outflow_2_barrio : 0.0\n",
      "outflow_3_barrio : 0.0\n",
      "outflow_4_barrio : 0.0\n",
      "outflow_5_barrio : 4.0\n",
      "outflow_6_barrio : 0.0\n",
      "outflow_7_barrio : 0.0\n",
      "outflow_8_barrio : 0.0\n",
      "outflow_9_barrio : 0.0\n",
      "outflow_10_barrio : 0.0\n",
      "outflow_11_barrio : 0.0\n",
      "outflow_12_barrio : 0.0\n",
      "outflow_13_barrio : 0.0\n",
      "outflow_14_barrio : 0.0\n",
      "outflow_15_barrio : 0.0\n",
      "outflow_16_barrio : 0.0\n",
      "outflow_17_barrio : 1.0\n",
      "outflow_18_barrio : 0.0\n",
      "outflow_19_barrio : 0.0\n",
      "outflow_20_barrio : 0.0\n",
      "outflow_21_barrio : 0.0\n",
      "outflow_22_barrio : 0.0\n",
      "outflow_23_barrio : 1.0\n",
      "outflow_24_barrio : 1.0\n",
      "outflow_25_barrio : 2.0\n",
      "outflow_26_barrio : 0.0\n",
      "outflow_27_barrio : 0.0\n",
      "outflow_28_barrio : 0.0\n",
      "outflow_29_barrio : 0.0\n",
      "outflow_30_barrio : 0.0\n",
      "outflow_31_barrio : 1.0\n",
      "outflow_32_barrio : 0.0\n",
      "outflow_33_barrio : 0.0\n",
      "outflow_34_barrio : 0.0\n",
      "outflow_35_barrio : 1.0\n",
      "outflow_36_barrio : 0.0\n",
      "outflow_37_barrio : 0.0\n",
      "outflow_38_barrio : 1.0\n",
      "outflow_39_barrio : 0.0\n",
      "outflow_40_barrio : 0.0\n",
      "outflow_41_barrio : 0.0\n",
      "outflow_42_barrio : 0.0\n",
      "outflow_43_barrio : 1.0\n",
      "outflow_44_barrio : 0.0\n",
      "outflow_45_barrio : 2.0\n",
      "outflow_46_barrio : 0.0\n",
      "outflow_47_barrio : 0.0\n",
      "outflow_48_barrio : 0.0\n",
      "outflow_49_barrio : 0.0\n",
      "outflow_50_barrio : 0.0\n",
      "outflow_51_barrio : 3.0\n",
      "outflow_52_barrio : 0.0\n",
      "outflow_53_barrio : 0.0\n",
      "outflow_54_barrio : 0.0\n",
      "outflow_55_barrio : 0.0\n",
      "outflow_56_barrio : 0.0\n",
      "outflow_57_barrio : 0.0\n",
      "outflow_58_barrio : 0.0\n",
      "outflow_59_barrio : 0.0\n",
      "outflow_60_barrio : 0.0\n",
      "outflow_61_barrio : 2.0\n",
      "outflow_62_barrio : 0.0\n",
      "outflow_63_barrio : 0.0\n",
      "outflow_64_barrio : 0.0\n",
      "outflow_65_barrio : 0.0\n",
      "outflow_66_barrio : 2.0\n",
      "outflow_67_barrio : 0.0\n",
      "outflow_68_barrio : 0.0\n",
      "outflow_69_barrio : 0.0\n",
      "outflow_70_barrio : 0.0\n",
      "outflow_71_barrio : 0.0\n",
      "outflow_72_barrio : 0.0\n",
      "outflow_73_barrio : 0.0\n",
      "outflow_74_barrio : 0.0\n",
      "outflow_75_barrio : 0.0\n",
      "outflow_76_barrio : 0.0\n",
      "outflow_77_barrio : 0.0\n",
      "outflow_78_barrio : 0.0\n",
      "outflow_79_barrio : 0.0\n",
      "outflow_80_barrio : 0.0\n",
      "outflow_81_barrio : 0.0\n",
      "outflow_82_barrio : 0.0\n",
      "outflow_83_barrio : 1.0\n",
      "outflow_84_barrio : 0.0\n",
      "outflow_85_barrio : 0.0\n",
      "outflow_86_barrio : 0.0\n",
      "outflow_87_barrio : 0.0\n",
      "outflow_88_barrio : 1.0\n",
      "outflow_89_barrio : 0.0\n",
      "outflow_90_barrio : 1.0\n",
      "outflow_91_barrio : 0.0\n",
      "outflow_92_barrio : 0.0\n",
      "outflow_93_barrio : 0.0\n",
      "outflow_94_barrio : 0.0\n",
      "outflow_95_barrio : 0.0\n",
      "outflow_96_barrio : 0.0\n",
      "outflow_97_barrio : 0.0\n",
      "outflow_98_barrio : 0.0\n",
      "outflow_99_barrio : 0.0\n",
      "outflow_100_barrio : 0.0\n",
      "outflow_101_barrio : 0.0\n",
      "outflow_102_barrio : 0.0\n",
      "outflow_103_barrio : 0.0\n",
      "outflow_104_barrio : 0.0\n",
      "outflow_105_barrio : 0.0\n",
      "outflow_106_barrio : 0.0\n",
      "outflow_107_barrio : 0.0\n",
      "outflow_108_barrio : 0.0\n",
      "outflow_109_barrio : 0.0\n",
      "outflow_110_barrio : 1.0\n",
      "outflow_111_barrio : 0.0\n",
      "outflow_112_barrio : 0.0\n",
      "outflow_113_barrio : 1.0\n",
      "outflow_114_barrio : 1.0\n",
      "outflow_115_barrio : 0.0\n",
      "outflow_116_barrio : 0.0\n",
      "outflow_117_barrio : 1.0\n",
      "outflow_118_barrio : 0.0\n",
      "outflow_119_barrio : 0.0\n",
      "outflow_120_barrio : 0.0\n",
      "outflow_121_barrio : 0.0\n",
      "outflow_122_barrio : 0.0\n",
      "outflow_123_barrio : 0.0\n",
      "outflow_124_barrio : 0.0\n",
      "outflow_125_barrio : 0.0\n",
      "outflow_126_barrio : 0.0\n",
      "outflow_127_barrio : 0.0\n",
      "outflow_128_barrio : 0.0\n",
      "outflow_129_barrio : 0.0\n",
      "outflow_130_barrio : 0.0\n",
      "outflow_131_barrio : 0.0\n",
      "outflow_132_barrio : 3.0\n",
      "outflow_133_barrio : 2.0\n",
      "outflow_134_barrio : 0.0\n",
      "outflow_135_barrio : 0.0\n",
      "outflow_136_barrio : 0.0\n",
      "outflow_137_barrio : 0.0\n",
      "outflow_138_barrio : 0.0\n",
      "outflow_139_barrio : 0.0\n",
      "outflow_140_barrio : 0.0\n",
      "outflow_141_barrio : 1.0\n",
      "outflow_142_barrio : 0.0\n",
      "outflow_143_barrio : 0.0\n",
      "outflow_144_barrio : 2.0\n",
      "outflow_145_barrio : 0.0\n",
      "outflow_146_barrio : 0.0\n",
      "outflow_147_barrio : 2.0\n",
      "outflow_148_barrio : 0.0\n",
      "outflow_149_barrio : 2.0\n",
      "outflow_150_barrio : 0.0\n",
      "outflow_151_barrio : 0.0\n",
      "outflow_152_barrio : 0.0\n",
      "outflow_153_barrio : 0.0\n",
      "outflow_154_barrio : 0.0\n",
      "outflow_155_barrio : 1.0\n",
      "outflow_156_barrio : 0.0\n",
      "outflow_157_barrio : 2.0\n",
      "outflow_158_barrio : 0.0\n",
      "outflow_159_barrio : 0.0\n",
      "outflow_160_barrio : 0.0\n",
      "outflow_161_barrio : 0.0\n",
      "outflow_162_barrio : 1.0\n",
      "outflow_163_barrio : 0.0\n",
      "number_meaningful_incoming : 1.4137931034482758\n",
      "number_meaningful_outgoing : 1.28125\n",
      "mean_distance_strongest_inflow : 10971.916376811465\n",
      "mean_distance_strongest_outflow : 10590.6470769989\n"
     ]
    }
   ],
   "source": [
    "for key, val in stats.items():\n",
    "    print(key, \":\", val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c50ca3f8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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