combined_risk_score.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9e873bfc",
   "metadata": {},
   "outputs": [],
   "source": [
    "import osmnx as ox\n",
    "import networkx as nx\n",
    "import geopandas as gpd\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "54df7337",
   "metadata": {},
   "outputs": [],
   "source": [
    "G=ox.graph_from_place(\"Nakagawa-ku,Nagoya,Japan\",network_type='drive')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "bdf43154",
   "metadata": {},
   "outputs": [],
   "source": [
    "nodes,edges=ox.graph_to_gdfs(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b03c2c6f",
   "metadata": {},
   "outputs": [],
   "source": [
    "invalid_cols=['osmid','highway','bridge','lanes','ref','name']\n",
    "edges[invalid_cols] = edges[invalid_cols].astype(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c3313df1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['residential', 'motorway', 'motorway_link', 'unclassified',\n",
       "       'trunk', 'secondary', 'tertiary', 'primary',\n",
       "       \"['residential', 'unclassified']\", \"['unclassified', 'tertiary']\",\n",
       "       'primary_link', 'trunk_link', \"['residential', 'tertiary']\"],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges['highway'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "24163564",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NaN    22354\n",
       "40       140\n",
       "30        20\n",
       "60         6\n",
       "Name: maxspeed, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges[\"maxspeed\"].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "456e7101",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "unclassified                       15591\n",
       "residential                         3041\n",
       "tertiary                            2663\n",
       "primary                              500\n",
       "secondary                            407\n",
       "trunk                                216\n",
       "['residential', 'unclassified']       26\n",
       "motorway_link                         23\n",
       "primary_link                          16\n",
       "motorway                              13\n",
       "['unclassified', 'tertiary']          12\n",
       "trunk_link                            10\n",
       "['residential', 'tertiary']            2\n",
       "Name: highway, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges['highway'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "04200bf7",
   "metadata": {},
   "outputs": [],
   "source": [
    "def road_class_to_kmph(road_class):\n",
    "    if road_class=='residential':\n",
    "        return 30\n",
    "    elif road_class=='motorway':\n",
    "        return 60\n",
    "    elif road_class=='motorway_link':\n",
    "        return 60\n",
    "    elif road_class in ['trunk','trunk_link']:\n",
    "        return 60\n",
    "    elif road_class=='secondary':\n",
    "        return 50\n",
    "    elif road_class=='tertiary':\n",
    "        return 40\n",
    "    elif road_class in ['primary','primary_link']:\n",
    "        return 50\n",
    "    elif road_class==['tertiary', 'residential']:\n",
    "        return 40\n",
    "    elif road_class==['unclassified', 'residential']:\n",
    "        return 30\n",
    "    else :\n",
    "        return 30"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "40ea9ae8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<IntegerArray>\n",
       "[<NA>, 30, 40, 60]\n",
       "Length: 4, dtype: Int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges[\"maxspeed\"] = edges[\"maxspeed\"].astype(float).astype(pd.Int64Dtype())\n",
    "edges[\"maxspeed\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "0cadaf04",
   "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></th>\n",
       "      <th></th>\n",
       "      <th>maxspeed</th>\n",
       "      <th>highway</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>u</th>\n",
       "      <th>v</th>\n",
       "      <th>key</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>265835867</th>\n",
       "      <th>1583801850</th>\n",
       "      <th>0</th>\n",
       "      <td>30</td>\n",
       "      <td>residential</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">287037206</th>\n",
       "      <th>6418759114</th>\n",
       "      <th>0</th>\n",
       "      <td>60</td>\n",
       "      <td>motorway</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8687399278</th>\n",
       "      <th>0</th>\n",
       "      <td>60</td>\n",
       "      <td>motorway_link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">287051498</th>\n",
       "      <th>1161617447</th>\n",
       "      <th>0</th>\n",
       "      <td>30</td>\n",
       "      <td>unclassified</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3909362365</th>\n",
       "      <th>0</th>\n",
       "      <td>60</td>\n",
       "      <td>trunk</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          maxspeed        highway\n",
       "u         v          key                         \n",
       "265835867 1583801850 0          30    residential\n",
       "287037206 6418759114 0          60       motorway\n",
       "          8687399278 0          60  motorway_link\n",
       "287051498 1161617447 0          30   unclassified\n",
       "          3909362365 0          60          trunk"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Separate rows with / without speed limit information \n",
    "mask = edges[\"maxspeed\"].isnull()\n",
    "edges_without_maxspeed = edges.loc[mask].copy()\n",
    "edges_with_maxspeed = edges.loc[~mask].copy()\n",
    "\n",
    "# Apply the function and update the maxspeed\n",
    "edges_without_maxspeed[\"maxspeed\"] = edges_without_maxspeed[\"highway\"].apply(road_class_to_kmph)\n",
    "edges_without_maxspeed.head(5).loc[:, [\"maxspeed\", \"highway\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "5248e4da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<IntegerArray>\n",
       "[30, 40, 60, 50]\n",
       "Length: 4, dtype: Int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges = edges_with_maxspeed.append(edges_without_maxspeed)\n",
    "edges[\"maxspeed\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "05083487",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['osmid', 'highway', 'oneway', 'length', 'bridge', 'lanes', 'ref',\n",
       "       'name', 'geometry', 'est_width', 'maxspeed', 'tunnel'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3453201e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "13.0m以上       4\n",
       "5.5m〜13.0m    3\n",
       "Name: est_width, dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges.est_width.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "7f605199",
   "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></th>\n",
       "      <th></th>\n",
       "      <th>osmid</th>\n",
       "      <th>highway</th>\n",
       "      <th>oneway</th>\n",
       "      <th>length</th>\n",
       "      <th>bridge</th>\n",
       "      <th>lanes</th>\n",
       "      <th>ref</th>\n",
       "      <th>name</th>\n",
       "      <th>geometry</th>\n",
       "      <th>est_width</th>\n",
       "      <th>maxspeed</th>\n",
       "      <th>tunnel</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>u</th>\n",
       "      <th>v</th>\n",
       "      <th>key</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>495060600</th>\n",
       "      <th>660711475</th>\n",
       "      <th>0</th>\n",
       "      <td>55824264</td>\n",
       "      <td>residential</td>\n",
       "      <td>False</td>\n",
       "      <td>44.513</td>\n",
       "      <td>nan</td>\n",
       "      <td>2</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>LINESTRING (136.89193 35.15705, 136.89145 35.1...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495060608</th>\n",
       "      <th>660711366</th>\n",
       "      <th>0</th>\n",
       "      <td>47119686</td>\n",
       "      <td>tertiary</td>\n",
       "      <td>False</td>\n",
       "      <td>153.752</td>\n",
       "      <td>nan</td>\n",
       "      <td>2</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>LINESTRING (136.89232 35.15392, 136.89063 35.1...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>628595857</th>\n",
       "      <th>660917848</th>\n",
       "      <th>0</th>\n",
       "      <td>49478329</td>\n",
       "      <td>tertiary</td>\n",
       "      <td>False</td>\n",
       "      <td>156.572</td>\n",
       "      <td>nan</td>\n",
       "      <td>1</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>LINESTRING (136.89463 35.14493, 136.89509 35.1...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>628595860</th>\n",
       "      <th>712559797</th>\n",
       "      <th>0</th>\n",
       "      <td>318778964</td>\n",
       "      <td>tertiary</td>\n",
       "      <td>False</td>\n",
       "      <td>185.640</td>\n",
       "      <td>nan</td>\n",
       "      <td>1</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>LINESTRING (136.89656 35.13999, 136.89691 35.1...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">628595863</th>\n",
       "      <th>1547522057</th>\n",
       "      <th>0</th>\n",
       "      <td>49478329</td>\n",
       "      <td>tertiary</td>\n",
       "      <td>False</td>\n",
       "      <td>145.366</td>\n",
       "      <td>nan</td>\n",
       "      <td>1</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>LINESTRING (136.89539 35.14256, 136.89542 35.1...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>660917860</th>\n",
       "      <th>0</th>\n",
       "      <td>49478329</td>\n",
       "      <td>tertiary</td>\n",
       "      <td>False</td>\n",
       "      <td>62.751</td>\n",
       "      <td>nan</td>\n",
       "      <td>1</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>LINESTRING (136.89539 35.14256, 136.89536 35.1...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              osmid      highway  oneway   length bridge  \\\n",
       "u         v          key                                                   \n",
       "495060600 660711475  0     55824264  residential   False   44.513    nan   \n",
       "495060608 660711366  0     47119686     tertiary   False  153.752    nan   \n",
       "628595857 660917848  0     49478329     tertiary   False  156.572    nan   \n",
       "628595860 712559797  0    318778964     tertiary   False  185.640    nan   \n",
       "628595863 1547522057 0     49478329     tertiary   False  145.366    nan   \n",
       "          660917860  0     49478329     tertiary   False   62.751    nan   \n",
       "\n",
       "                         lanes  ref name  \\\n",
       "u         v          key                   \n",
       "495060600 660711475  0       2  nan  nan   \n",
       "495060608 660711366  0       2  nan  nan   \n",
       "628595857 660917848  0       1  nan  nan   \n",
       "628595860 712559797  0       1  nan  nan   \n",
       "628595863 1547522057 0       1  nan  nan   \n",
       "          660917860  0       1  nan  nan   \n",
       "\n",
       "                                                                   geometry  \\\n",
       "u         v          key                                                      \n",
       "495060600 660711475  0    LINESTRING (136.89193 35.15705, 136.89145 35.1...   \n",
       "495060608 660711366  0    LINESTRING (136.89232 35.15392, 136.89063 35.1...   \n",
       "628595857 660917848  0    LINESTRING (136.89463 35.14493, 136.89509 35.1...   \n",
       "628595860 712559797  0    LINESTRING (136.89656 35.13999, 136.89691 35.1...   \n",
       "628595863 1547522057 0    LINESTRING (136.89539 35.14256, 136.89542 35.1...   \n",
       "          660917860  0    LINESTRING (136.89539 35.14256, 136.89536 35.1...   \n",
       "\n",
       "                         est_width  maxspeed tunnel  \n",
       "u         v          key                             \n",
       "495060600 660711475  0         NaN        30    NaN  \n",
       "495060608 660711366  0         NaN        40    NaN  \n",
       "628595857 660917848  0         NaN        40    NaN  \n",
       "628595860 712559797  0         NaN        40    NaN  \n",
       "628595863 1547522057 0         NaN        40    NaN  \n",
       "          660917860  0         NaN        40    NaN  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges.head(6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "06f8fc98",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "edges[\"maxspeed\"] = edges[\"maxspeed\"].astype(int)\n",
    "edges.plot(column=\"maxspeed\", figsize=(10,10), legend=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "65a01d64",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "22520"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(edges)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "1bcfa24d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Distance risk\n",
    "graph_distance = nx.read_gpickle(\"data/nakagawa_graph_distance_risk_added.pickle\")\n",
    "_,edges_distance = ox.graph_to_gdfs(graph_distance)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "546f4947",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "30694"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(edges_distance)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "c603d29b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Building risk\n",
    "graph_building = nx.read_gpickle(\"data/nakagawa_graph_building_density_risk_addded.pickle\")\n",
    "_,edges_building = ox.graph_to_gdfs(graph_building)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "7bd26d94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "30694"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(edges_building)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b6bdf92b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Earthquake risk\n",
    "graph_earthquake = nx.read_gpickle(\"data/nakagawa_graph_earthquake_risk_addded.pickle\")\n",
    "_,edges_earthquake = ox.graph_to_gdfs(graph_earthquake)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "503cc126",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "41756"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(edges_earthquake)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "f7eba406",
   "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></th>\n",
       "      <th></th>\n",
       "      <th>osmid</th>\n",
       "      <th>bridge</th>\n",
       "      <th>oneway</th>\n",
       "      <th>lanes</th>\n",
       "      <th>ref</th>\n",
       "      <th>name</th>\n",
       "      <th>highway</th>\n",
       "      <th>length</th>\n",
       "      <th>geometry</th>\n",
       "      <th>sampling_counts</th>\n",
       "      <th>...</th>\n",
       "      <th>median_scaled</th>\n",
       "      <th>mean_scaled_inversed</th>\n",
       "      <th>median_scaled_inversed</th>\n",
       "      <th>distance_risk_score</th>\n",
       "      <th>edge_color</th>\n",
       "      <th>est_width</th>\n",
       "      <th>tunnel</th>\n",
       "      <th>service</th>\n",
       "      <th>maxspeed</th>\n",
       "      <th>width</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>u</th>\n",
       "      <th>v</th>\n",
       "      <th>key</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">287037206</th>\n",
       "      <th>6418759114</th>\n",
       "      <th>0</th>\n",
       "      <td>[235402848, 940877736]</td>\n",
       "      <td>[viaduct, yes]</td>\n",
       "      <td>True</td>\n",
       "      <td>2</td>\n",
       "      <td>[5, E23]</td>\n",
       "      <td>[名古屋高速5号万場線, 東名阪自動車道]</td>\n",
       "      <td>motorway</td>\n",
       "      <td>549.217</td>\n",
       "      <td>LINESTRING (136.81737 35.15822, 136.81780 35.1...</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>1.648721</td>\n",
       "      <td>146.747868</td>\n",
       "      <td>146.764438</td>\n",
       "      <td>8.0</td>\n",
       "      <td>red</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8687399278</th>\n",
       "      <th>0</th>\n",
       "      <td>[937718833, 940585691, 766866772, 766866773]</td>\n",
       "      <td>yes</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>名古屋第二環状自動車道</td>\n",
       "      <td>motorway_link</td>\n",
       "      <td>717.481</td>\n",
       "      <td>LINESTRING (136.81737 35.15822, 136.81817 35.1...</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>1.648721</td>\n",
       "      <td>146.697152</td>\n",
       "      <td>146.764438</td>\n",
       "      <td>6.0</td>\n",
       "      <td>yellow</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8687399278</th>\n",
       "      <th>7162166992</th>\n",
       "      <th>0</th>\n",
       "      <td>766866776</td>\n",
       "      <td>yes</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>名古屋第二環状自動車道</td>\n",
       "      <td>motorway_link</td>\n",
       "      <td>211.954</td>\n",
       "      <td>LINESTRING (136.81880 35.15551, 136.81879 35.1...</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>2.718282</td>\n",
       "      <td>145.775215</td>\n",
       "      <td>145.694877</td>\n",
       "      <td>8.0</td>\n",
       "      <td>red</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">287051498</th>\n",
       "      <th>1161617447</th>\n",
       "      <th>0</th>\n",
       "      <td>140501318</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>unclassified</td>\n",
       "      <td>12.298</td>\n",
       "      <td>LINESTRING (136.84672 35.12402, 136.84672 35.1...</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>1.648721</td>\n",
       "      <td>146.764438</td>\n",
       "      <td>146.764438</td>\n",
       "      <td>9.0</td>\n",
       "      <td>red</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3909362365</th>\n",
       "      <th>0</th>\n",
       "      <td>311076737</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>国道1号</td>\n",
       "      <td>trunk</td>\n",
       "      <td>106.927</td>\n",
       "      <td>LINESTRING (136.84672 35.12402, 136.84555 35.1...</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>1.648721</td>\n",
       "      <td>146.714227</td>\n",
       "      <td>146.764438</td>\n",
       "      <td>8.0</td>\n",
       "      <td>red</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                  osmid  \\\n",
       "u          v          key                                                 \n",
       "287037206  6418759114 0                          [235402848, 940877736]   \n",
       "           8687399278 0    [937718833, 940585691, 766866772, 766866773]   \n",
       "8687399278 7162166992 0                                       766866776   \n",
       "287051498  1161617447 0                                       140501318   \n",
       "           3909362365 0                                       311076737   \n",
       "\n",
       "                                   bridge  oneway lanes       ref  \\\n",
       "u          v          key                                           \n",
       "287037206  6418759114 0    [viaduct, yes]    True     2  [5, E23]   \n",
       "           8687399278 0               yes    True   NaN       NaN   \n",
       "8687399278 7162166992 0               yes    True   NaN       NaN   \n",
       "287051498  1161617447 0               NaN   False   NaN       NaN   \n",
       "           3909362365 0               NaN    True     2         1   \n",
       "\n",
       "                                            name        highway   length  \\\n",
       "u          v          key                                                  \n",
       "287037206  6418759114 0    [名古屋高速5号万場線, 東名阪自動車道]       motorway  549.217   \n",
       "           8687399278 0              名古屋第二環状自動車道  motorway_link  717.481   \n",
       "8687399278 7162166992 0              名古屋第二環状自動車道  motorway_link  211.954   \n",
       "287051498  1161617447 0                      NaN   unclassified   12.298   \n",
       "           3909362365 0                     国道1号          trunk  106.927   \n",
       "\n",
       "                                                                    geometry  \\\n",
       "u          v          key                                                      \n",
       "287037206  6418759114 0    LINESTRING (136.81737 35.15822, 136.81780 35.1...   \n",
       "           8687399278 0    LINESTRING (136.81737 35.15822, 136.81817 35.1...   \n",
       "8687399278 7162166992 0    LINESTRING (136.81880 35.15551, 136.81879 35.1...   \n",
       "287051498  1161617447 0    LINESTRING (136.84672 35.12402, 136.84672 35.1...   \n",
       "           3909362365 0    LINESTRING (136.84672 35.12402, 136.84555 35.1...   \n",
       "\n",
       "                           sampling_counts  ...  median_scaled  \\\n",
       "u          v          key                   ...                  \n",
       "287037206  6418759114 0                 50  ...       1.648721   \n",
       "           8687399278 0                 50  ...       1.648721   \n",
       "8687399278 7162166992 0                 50  ...       2.718282   \n",
       "287051498  1161617447 0                 50  ...       1.648721   \n",
       "           3909362365 0                 50  ...       1.648721   \n",
       "\n",
       "                           mean_scaled_inversed  median_scaled_inversed  \\\n",
       "u          v          key                                                 \n",
       "287037206  6418759114 0              146.747868              146.764438   \n",
       "           8687399278 0              146.697152              146.764438   \n",
       "8687399278 7162166992 0              145.775215              145.694877   \n",
       "287051498  1161617447 0              146.764438              146.764438   \n",
       "           3909362365 0              146.714227              146.764438   \n",
       "\n",
       "                           distance_risk_score edge_color est_width  tunnel  \\\n",
       "u          v          key                                                     \n",
       "287037206  6418759114 0                    8.0        red       NaN     NaN   \n",
       "           8687399278 0                    6.0     yellow       NaN     NaN   \n",
       "8687399278 7162166992 0                    8.0        red       NaN     NaN   \n",
       "287051498  1161617447 0                    9.0        red       NaN     NaN   \n",
       "           3909362365 0                    8.0        red       NaN     NaN   \n",
       "\n",
       "                           service  maxspeed  width  \n",
       "u          v          key                            \n",
       "287037206  6418759114 0        NaN       NaN    NaN  \n",
       "           8687399278 0        NaN       NaN    NaN  \n",
       "8687399278 7162166992 0        NaN       NaN    NaN  \n",
       "287051498  1161617447 0        NaN       NaN    NaN  \n",
       "           3909362365 0        NaN       NaN    NaN  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges_distance.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "16869ddf",
   "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></th>\n",
       "      <th></th>\n",
       "      <th>osmid</th>\n",
       "      <th>bridge</th>\n",
       "      <th>oneway</th>\n",
       "      <th>lanes</th>\n",
       "      <th>ref</th>\n",
       "      <th>name</th>\n",
       "      <th>highway</th>\n",
       "      <th>length</th>\n",
       "      <th>geometry</th>\n",
       "      <th>building_count</th>\n",
       "      <th>est_width</th>\n",
       "      <th>tunnel</th>\n",
       "      <th>service</th>\n",
       "      <th>maxspeed</th>\n",
       "      <th>width</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>u</th>\n",
       "      <th>v</th>\n",
       "      <th>key</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">287037206</th>\n",
       "      <th>6418759114</th>\n",
       "      <th>0</th>\n",
       "      <td>[235402848, 940877736]</td>\n",
       "      <td>[viaduct, yes]</td>\n",
       "      <td>True</td>\n",
       "      <td>2</td>\n",
       "      <td>[5, E23]</td>\n",
       "      <td>[東名阪自動車道, 名古屋高速5号万場線]</td>\n",
       "      <td>motorway</td>\n",
       "      <td>549.217</td>\n",
       "      <td>LINESTRING (136.81737 35.15822, 136.81780 35.1...</td>\n",
       "      <td>215</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8687399278</th>\n",
       "      <th>0</th>\n",
       "      <td>[937718833, 940585691, 766866772, 766866773]</td>\n",
       "      <td>yes</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>名古屋第二環状自動車道</td>\n",
       "      <td>motorway_link</td>\n",
       "      <td>717.481</td>\n",
       "      <td>LINESTRING (136.81737 35.15822, 136.81817 35.1...</td>\n",
       "      <td>215</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8687399278</th>\n",
       "      <th>7162166992</th>\n",
       "      <th>0</th>\n",
       "      <td>766866776</td>\n",
       "      <td>yes</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>名古屋第二環状自動車道</td>\n",
       "      <td>motorway_link</td>\n",
       "      <td>211.954</td>\n",
       "      <td>LINESTRING (136.81880 35.15551, 136.81879 35.1...</td>\n",
       "      <td>467</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">287051498</th>\n",
       "      <th>1161617447</th>\n",
       "      <th>0</th>\n",
       "      <td>140501318</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>unclassified</td>\n",
       "      <td>12.298</td>\n",
       "      <td>LINESTRING (136.84672 35.12402, 136.84672 35.1...</td>\n",
       "      <td>311</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3909362365</th>\n",
       "      <th>0</th>\n",
       "      <td>311076737</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>国道1号</td>\n",
       "      <td>trunk</td>\n",
       "      <td>106.927</td>\n",
       "      <td>LINESTRING (136.84672 35.12402, 136.84555 35.1...</td>\n",
       "      <td>311</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                  osmid  \\\n",
       "u          v          key                                                 \n",
       "287037206  6418759114 0                          [235402848, 940877736]   \n",
       "           8687399278 0    [937718833, 940585691, 766866772, 766866773]   \n",
       "8687399278 7162166992 0                                       766866776   \n",
       "287051498  1161617447 0                                       140501318   \n",
       "           3909362365 0                                       311076737   \n",
       "\n",
       "                                   bridge  oneway lanes       ref  \\\n",
       "u          v          key                                           \n",
       "287037206  6418759114 0    [viaduct, yes]    True     2  [5, E23]   \n",
       "           8687399278 0               yes    True   NaN       NaN   \n",
       "8687399278 7162166992 0               yes    True   NaN       NaN   \n",
       "287051498  1161617447 0               NaN   False   NaN       NaN   \n",
       "           3909362365 0               NaN    True     2         1   \n",
       "\n",
       "                                            name        highway   length  \\\n",
       "u          v          key                                                  \n",
       "287037206  6418759114 0    [東名阪自動車道, 名古屋高速5号万場線]       motorway  549.217   \n",
       "           8687399278 0              名古屋第二環状自動車道  motorway_link  717.481   \n",
       "8687399278 7162166992 0              名古屋第二環状自動車道  motorway_link  211.954   \n",
       "287051498  1161617447 0                      NaN   unclassified   12.298   \n",
       "           3909362365 0                     国道1号          trunk  106.927   \n",
       "\n",
       "                                                                    geometry  \\\n",
       "u          v          key                                                      \n",
       "287037206  6418759114 0    LINESTRING (136.81737 35.15822, 136.81780 35.1...   \n",
       "           8687399278 0    LINESTRING (136.81737 35.15822, 136.81817 35.1...   \n",
       "8687399278 7162166992 0    LINESTRING (136.81880 35.15551, 136.81879 35.1...   \n",
       "287051498  1161617447 0    LINESTRING (136.84672 35.12402, 136.84672 35.1...   \n",
       "           3909362365 0    LINESTRING (136.84672 35.12402, 136.84555 35.1...   \n",
       "\n",
       "                           building_count est_width tunnel service maxspeed  \\\n",
       "u          v          key                                                     \n",
       "287037206  6418759114 0               215       NaN    NaN     NaN      NaN   \n",
       "           8687399278 0               215       NaN    NaN     NaN      NaN   \n",
       "8687399278 7162166992 0               467       NaN    NaN     NaN      NaN   \n",
       "287051498  1161617447 0               311       NaN    NaN     NaN      NaN   \n",
       "           3909362365 0               311       NaN    NaN     NaN      NaN   \n",
       "\n",
       "                          width  \n",
       "u          v          key        \n",
       "287037206  6418759114 0     NaN  \n",
       "           8687399278 0     NaN  \n",
       "8687399278 7162166992 0     NaN  \n",
       "287051498  1161617447 0     NaN  \n",
       "           3909362365 0     NaN  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges_building.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a8ba69d3",
   "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></th>\n",
       "      <th></th>\n",
       "      <th>osmid</th>\n",
       "      <th>highway</th>\n",
       "      <th>oneway</th>\n",
       "      <th>length</th>\n",
       "      <th>geometry</th>\n",
       "      <th>earthquake_risk</th>\n",
       "      <th>bridge</th>\n",
       "      <th>lanes</th>\n",
       "      <th>ref</th>\n",
       "      <th>name</th>\n",
       "      <th>width</th>\n",
       "      <th>maxspeed</th>\n",
       "      <th>est_width</th>\n",
       "      <th>tunnel</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>u</th>\n",
       "      <th>v</th>\n",
       "      <th>key</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>265835867</th>\n",
       "      <th>1583801850</th>\n",
       "      <th>0</th>\n",
       "      <td>891546719</td>\n",
       "      <td>residential</td>\n",
       "      <td>False</td>\n",
       "      <td>123.257</td>\n",
       "      <td>LINESTRING (136.80442 35.14114, 136.80578 35.1...</td>\n",
       "      <td>6.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">1583801850</th>\n",
       "      <th>1583801736</th>\n",
       "      <th>0</th>\n",
       "      <td>144896104</td>\n",
       "      <td>unclassified</td>\n",
       "      <td>False</td>\n",
       "      <td>60.260</td>\n",
       "      <td>LINESTRING (136.80578 35.14108, 136.80574 35.1...</td>\n",
       "      <td>6.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1583801938</th>\n",
       "      <th>0</th>\n",
       "      <td>144898376</td>\n",
       "      <td>unclassified</td>\n",
       "      <td>False</td>\n",
       "      <td>57.588</td>\n",
       "      <td>LINESTRING (136.80578 35.14108, 136.80581 35.1...</td>\n",
       "      <td>6.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>265835867</th>\n",
       "      <th>0</th>\n",
       "      <td>891546719</td>\n",
       "      <td>residential</td>\n",
       "      <td>False</td>\n",
       "      <td>123.257</td>\n",
       "      <td>LINESTRING (136.80578 35.14108, 136.80442 35.1...</td>\n",
       "      <td>6.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1583801828</th>\n",
       "      <th>0</th>\n",
       "      <td>144898782</td>\n",
       "      <td>unclassified</td>\n",
       "      <td>False</td>\n",
       "      <td>116.876</td>\n",
       "      <td>LINESTRING (136.80578 35.14108, 136.80701 35.1...</td>\n",
       "      <td>6.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               osmid       highway  oneway   length  \\\n",
       "u          v          key                                             \n",
       "265835867  1583801850 0    891546719   residential   False  123.257   \n",
       "1583801850 1583801736 0    144896104  unclassified   False   60.260   \n",
       "           1583801938 0    144898376  unclassified   False   57.588   \n",
       "           265835867  0    891546719   residential   False  123.257   \n",
       "           1583801828 0    144898782  unclassified   False  116.876   \n",
       "\n",
       "                                                                    geometry  \\\n",
       "u          v          key                                                      \n",
       "265835867  1583801850 0    LINESTRING (136.80442 35.14114, 136.80578 35.1...   \n",
       "1583801850 1583801736 0    LINESTRING (136.80578 35.14108, 136.80574 35.1...   \n",
       "           1583801938 0    LINESTRING (136.80578 35.14108, 136.80581 35.1...   \n",
       "           265835867  0    LINESTRING (136.80578 35.14108, 136.80442 35.1...   \n",
       "           1583801828 0    LINESTRING (136.80578 35.14108, 136.80701 35.1...   \n",
       "\n",
       "                           earthquake_risk bridge lanes  ref name width  \\\n",
       "u          v          key                                                 \n",
       "265835867  1583801850 0                6.5    NaN   NaN  NaN  NaN   NaN   \n",
       "1583801850 1583801736 0                6.5    NaN   NaN  NaN  NaN   NaN   \n",
       "           1583801938 0                6.5    NaN   NaN  NaN  NaN   NaN   \n",
       "           265835867  0                6.5    NaN   NaN  NaN  NaN   NaN   \n",
       "           1583801828 0                6.5    NaN   NaN  NaN  NaN   NaN   \n",
       "\n",
       "                          maxspeed est_width tunnel  \n",
       "u          v          key                            \n",
       "265835867  1583801850 0        NaN       NaN    NaN  \n",
       "1583801850 1583801736 0        NaN       NaN    NaN  \n",
       "           1583801938 0        NaN       NaN    NaN  \n",
       "           265835867  0        NaN       NaN    NaN  \n",
       "           1583801828 0        NaN       NaN    NaN  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges_earthquake.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "c8dc2bc8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Geographic 2D CRS: EPSG:4326>\n",
       "Name: WGS 84\n",
       "Axis Info [ellipsoidal]:\n",
       "- Lat[north]: Geodetic latitude (degree)\n",
       "- Lon[east]: Geodetic longitude (degree)\n",
       "Area of Use:\n",
       "- name: World.\n",
       "- bounds: (-180.0, -90.0, 180.0, 90.0)\n",
       "Datum: World Geodetic System 1984\n",
       "- Ellipsoid: WGS 84\n",
       "- Prime Meridian: Greenwich"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "1bae8eb9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Geographic 2D CRS: EPSG:4326>\n",
       "Name: WGS 84\n",
       "Axis Info [ellipsoidal]:\n",
       "- Lat[north]: Geodetic latitude (degree)\n",
       "- Lon[east]: Geodetic longitude (degree)\n",
       "Area of Use:\n",
       "- name: World.\n",
       "- bounds: (-180.0, -90.0, 180.0, 90.0)\n",
       "Datum: World Geodetic System 1984\n",
       "- Ellipsoid: WGS 84\n",
       "- Prime Meridian: Greenwich"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges_distance.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "926777db",
   "metadata": {},
   "outputs": [],
   "source": [
    "edges['uv']=edges.index.to_numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "28c72577",
   "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></th>\n",
       "      <th></th>\n",
       "      <th>osmid</th>\n",
       "      <th>highway</th>\n",
       "      <th>oneway</th>\n",
       "      <th>length</th>\n",
       "      <th>bridge</th>\n",
       "      <th>lanes</th>\n",
       "      <th>ref</th>\n",
       "      <th>name</th>\n",
       "      <th>geometry</th>\n",
       "      <th>est_width</th>\n",
       "      <th>maxspeed</th>\n",
       "      <th>tunnel</th>\n",
       "      <th>uv</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>u</th>\n",
       "      <th>v</th>\n",
       "      <th>key</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>495060600</th>\n",
       "      <th>660711475</th>\n",
       "      <th>0</th>\n",
       "      <td>55824264</td>\n",
       "      <td>residential</td>\n",
       "      <td>False</td>\n",
       "      <td>44.513</td>\n",
       "      <td>nan</td>\n",
       "      <td>2</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>LINESTRING (136.89193 35.15705, 136.89145 35.1...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(495060600, 660711475, 0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495060608</th>\n",
       "      <th>660711366</th>\n",
       "      <th>0</th>\n",
       "      <td>47119686</td>\n",
       "      <td>tertiary</td>\n",
       "      <td>False</td>\n",
       "      <td>153.752</td>\n",
       "      <td>nan</td>\n",
       "      <td>2</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>LINESTRING (136.89232 35.15392, 136.89063 35.1...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(495060608, 660711366, 0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>628595857</th>\n",
       "      <th>660917848</th>\n",
       "      <th>0</th>\n",
       "      <td>49478329</td>\n",
       "      <td>tertiary</td>\n",
       "      <td>False</td>\n",
       "      <td>156.572</td>\n",
       "      <td>nan</td>\n",
       "      <td>1</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>LINESTRING (136.89463 35.14493, 136.89509 35.1...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(628595857, 660917848, 0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>628595860</th>\n",
       "      <th>712559797</th>\n",
       "      <th>0</th>\n",
       "      <td>318778964</td>\n",
       "      <td>tertiary</td>\n",
       "      <td>False</td>\n",
       "      <td>185.640</td>\n",
       "      <td>nan</td>\n",
       "      <td>1</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>LINESTRING (136.89656 35.13999, 136.89691 35.1...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(628595860, 712559797, 0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>628595863</th>\n",
       "      <th>1547522057</th>\n",
       "      <th>0</th>\n",
       "      <td>49478329</td>\n",
       "      <td>tertiary</td>\n",
       "      <td>False</td>\n",
       "      <td>145.366</td>\n",
       "      <td>nan</td>\n",
       "      <td>1</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>LINESTRING (136.89539 35.14256, 136.89542 35.1...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(628595863, 1547522057, 0)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              osmid      highway  oneway   length bridge  \\\n",
       "u         v          key                                                   \n",
       "495060600 660711475  0     55824264  residential   False   44.513    nan   \n",
       "495060608 660711366  0     47119686     tertiary   False  153.752    nan   \n",
       "628595857 660917848  0     49478329     tertiary   False  156.572    nan   \n",
       "628595860 712559797  0    318778964     tertiary   False  185.640    nan   \n",
       "628595863 1547522057 0     49478329     tertiary   False  145.366    nan   \n",
       "\n",
       "                         lanes  ref name  \\\n",
       "u         v          key                   \n",
       "495060600 660711475  0       2  nan  nan   \n",
       "495060608 660711366  0       2  nan  nan   \n",
       "628595857 660917848  0       1  nan  nan   \n",
       "628595860 712559797  0       1  nan  nan   \n",
       "628595863 1547522057 0       1  nan  nan   \n",
       "\n",
       "                                                                   geometry  \\\n",
       "u         v          key                                                      \n",
       "495060600 660711475  0    LINESTRING (136.89193 35.15705, 136.89145 35.1...   \n",
       "495060608 660711366  0    LINESTRING (136.89232 35.15392, 136.89063 35.1...   \n",
       "628595857 660917848  0    LINESTRING (136.89463 35.14493, 136.89509 35.1...   \n",
       "628595860 712559797  0    LINESTRING (136.89656 35.13999, 136.89691 35.1...   \n",
       "628595863 1547522057 0    LINESTRING (136.89539 35.14256, 136.89542 35.1...   \n",
       "\n",
       "                         est_width  maxspeed tunnel  \\\n",
       "u         v          key                              \n",
       "495060600 660711475  0         NaN        30    NaN   \n",
       "495060608 660711366  0         NaN        40    NaN   \n",
       "628595857 660917848  0         NaN        40    NaN   \n",
       "628595860 712559797  0         NaN        40    NaN   \n",
       "628595863 1547522057 0         NaN        40    NaN   \n",
       "\n",
       "                                                  uv  \n",
       "u         v          key                              \n",
       "495060600 660711475  0     (495060600, 660711475, 0)  \n",
       "495060608 660711366  0     (495060608, 660711366, 0)  \n",
       "628595857 660917848  0     (628595857, 660917848, 0)  \n",
       "628595860 712559797  0     (628595860, 712559797, 0)  \n",
       "628595863 1547522057 0    (628595863, 1547522057, 0)  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "472c7520",
   "metadata": {},
   "outputs": [],
   "source": [
    "combine_score=pd.merge(edges_distance,edges_building,how=\"inner\",on='geometry')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "0cec9407",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "30718"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(combine_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "5a1d9c1c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['osmid_x', 'bridge_x', 'oneway_x', 'lanes_x', 'ref_x', 'name_x',\n",
       "       'highway_x', 'length_x', 'geometry', 'sampling_counts', 'max', 'min',\n",
       "       'mean', 'median', 'x_y', 'lon_lat', 'mean_scaled', 'median_scaled',\n",
       "       'mean_scaled_inversed', 'median_scaled_inversed', 'distance_risk_score',\n",
       "       'edge_color', 'est_width_x', 'tunnel_x', 'service_x', 'maxspeed_x',\n",
       "       'width_x', 'osmid_y', 'bridge_y', 'oneway_y', 'lanes_y', 'ref_y',\n",
       "       'name_y', 'highway_y', 'length_y', 'building_count', 'est_width_y',\n",
       "       'tunnel_y', 'service_y', 'maxspeed_y', 'width_y'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combine_score.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "91e77cc0",
   "metadata": {},
   "outputs": [],
   "source": [
    "combine_score=combine_score.loc[:,['osmid_x', 'bridge_x', 'oneway_x', 'lanes_x', 'ref_x', 'name_x',\n",
    "       'highway_x', 'length_x', 'geometry','distance_risk_score','building_count']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "5b7aaf6a",
   "metadata": {},
   "outputs": [],
   "source": [
    "combine_score=pd.merge(combine_score,edges_earthquake,how=\"inner\",on='geometry')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "dc2bd0a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20040"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(combine_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "795c2883",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['osmid_x', 'bridge_x', 'oneway_x', 'lanes_x', 'ref_x', 'name_x',\n",
       "       'highway_x', 'length_x', 'geometry', 'distance_risk_score',\n",
       "       'building_count', 'osmid', 'highway', 'oneway', 'length',\n",
       "       'earthquake_risk', 'bridge', 'lanes', 'ref', 'name', 'width',\n",
       "       'maxspeed', 'est_width', 'tunnel'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combine_score.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "6b9ccd4c",
   "metadata": {},
   "outputs": [],
   "source": [
    "combine_score=combine_score.loc[:,['osmid_x', 'bridge_x', 'oneway_x', 'lanes_x', 'ref_x', 'name_x',\n",
    "       'highway_x', 'length_x', 'geometry', 'distance_risk_score',\n",
    "       'building_count', 'earthquake_risk']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "d1390c9f",
   "metadata": {},
   "outputs": [],
   "source": [
    "combine_score=pd.merge(combine_score,edges,how=\"inner\",on='geometry')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "20ee0810",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20092"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(combine_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "16073158",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['osmid_x', 'bridge_x', 'oneway_x', 'lanes_x', 'ref_x', 'name_x',\n",
       "       'highway_x', 'length_x', 'geometry', 'distance_risk_score',\n",
       "       'building_count', 'earthquake_risk', 'osmid', 'highway', 'oneway',\n",
       "       'length', 'bridge', 'lanes', 'ref', 'name', 'est_width', 'maxspeed',\n",
       "       'tunnel', 'uv'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combine_score.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "4e781c75",
   "metadata": {},
   "outputs": [],
   "source": [
    "combine_score.index=pd.MultiIndex.from_tuples(combine_score.uv, names=('u', 'v','key'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "1c909b86",
   "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></th>\n",
       "      <th></th>\n",
       "      <th>osmid_x</th>\n",
       "      <th>bridge_x</th>\n",
       "      <th>oneway_x</th>\n",
       "      <th>lanes_x</th>\n",
       "      <th>ref_x</th>\n",
       "      <th>name_x</th>\n",
       "      <th>highway_x</th>\n",
       "      <th>length_x</th>\n",
       "      <th>geometry</th>\n",
       "      <th>distance_risk_score</th>\n",
       "      <th>...</th>\n",
       "      <th>oneway</th>\n",
       "      <th>length</th>\n",
       "      <th>bridge</th>\n",
       "      <th>lanes</th>\n",
       "      <th>ref</th>\n",
       "      <th>name</th>\n",
       "      <th>est_width</th>\n",
       "      <th>maxspeed</th>\n",
       "      <th>tunnel</th>\n",
       "      <th>uv</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>u</th>\n",
       "      <th>v</th>\n",
       "      <th>key</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">287037206</th>\n",
       "      <th>6418759114</th>\n",
       "      <th>0</th>\n",
       "      <td>[235402848, 940877736]</td>\n",
       "      <td>[viaduct, yes]</td>\n",
       "      <td>True</td>\n",
       "      <td>2</td>\n",
       "      <td>[5, E23]</td>\n",
       "      <td>[名古屋高速5号万場線, 東名阪自動車道]</td>\n",
       "      <td>motorway</td>\n",
       "      <td>549.217</td>\n",
       "      <td>LINESTRING (136.81737 35.15822, 136.81780 35.1...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>549.217</td>\n",
       "      <td>['yes', 'viaduct']</td>\n",
       "      <td>2</td>\n",
       "      <td>['E23', '5']</td>\n",
       "      <td>['東名阪自動車道', '名古屋高速5号万場線']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(287037206, 6418759114, 0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8687399278</th>\n",
       "      <th>0</th>\n",
       "      <td>[937718833, 940585691, 766866772, 766866773]</td>\n",
       "      <td>yes</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>名古屋第二環状自動車道</td>\n",
       "      <td>motorway_link</td>\n",
       "      <td>717.481</td>\n",
       "      <td>LINESTRING (136.81737 35.15822, 136.81817 35.1...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>717.481</td>\n",
       "      <td>yes</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>名古屋第二環状自動車道</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(287037206, 8687399278, 0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8687399278</th>\n",
       "      <th>7162166992</th>\n",
       "      <th>0</th>\n",
       "      <td>766866776</td>\n",
       "      <td>yes</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>名古屋第二環状自動車道</td>\n",
       "      <td>motorway_link</td>\n",
       "      <td>211.954</td>\n",
       "      <td>LINESTRING (136.81880 35.15551, 136.81879 35.1...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>211.954</td>\n",
       "      <td>yes</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>名古屋第二環状自動車道</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(8687399278, 7162166992, 0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">287051498</th>\n",
       "      <th>1161617447</th>\n",
       "      <th>0</th>\n",
       "      <td>140501318</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>unclassified</td>\n",
       "      <td>12.298</td>\n",
       "      <td>LINESTRING (136.84672 35.12402, 136.84672 35.1...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>12.298</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(287051498, 1161617447, 0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3909362365</th>\n",
       "      <th>0</th>\n",
       "      <td>311076737</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>国道1号</td>\n",
       "      <td>trunk</td>\n",
       "      <td>106.927</td>\n",
       "      <td>LINESTRING (136.84672 35.12402, 136.84555 35.1...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>106.927</td>\n",
       "      <td>nan</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>国道1号</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(287051498, 3909362365, 0)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                osmid_x  \\\n",
       "u          v          key                                                 \n",
       "287037206  6418759114 0                          [235402848, 940877736]   \n",
       "           8687399278 0    [937718833, 940585691, 766866772, 766866773]   \n",
       "8687399278 7162166992 0                                       766866776   \n",
       "287051498  1161617447 0                                       140501318   \n",
       "           3909362365 0                                       311076737   \n",
       "\n",
       "                                 bridge_x  oneway_x lanes_x     ref_x  \\\n",
       "u          v          key                                               \n",
       "287037206  6418759114 0    [viaduct, yes]      True       2  [5, E23]   \n",
       "           8687399278 0               yes      True     NaN       NaN   \n",
       "8687399278 7162166992 0               yes      True     NaN       NaN   \n",
       "287051498  1161617447 0               NaN     False     NaN       NaN   \n",
       "           3909362365 0               NaN      True       2         1   \n",
       "\n",
       "                                          name_x      highway_x  length_x  \\\n",
       "u          v          key                                                   \n",
       "287037206  6418759114 0    [名古屋高速5号万場線, 東名阪自動車道]       motorway   549.217   \n",
       "           8687399278 0              名古屋第二環状自動車道  motorway_link   717.481   \n",
       "8687399278 7162166992 0              名古屋第二環状自動車道  motorway_link   211.954   \n",
       "287051498  1161617447 0                      NaN   unclassified    12.298   \n",
       "           3909362365 0                     国道1号          trunk   106.927   \n",
       "\n",
       "                                                                    geometry  \\\n",
       "u          v          key                                                      \n",
       "287037206  6418759114 0    LINESTRING (136.81737 35.15822, 136.81780 35.1...   \n",
       "           8687399278 0    LINESTRING (136.81737 35.15822, 136.81817 35.1...   \n",
       "8687399278 7162166992 0    LINESTRING (136.81880 35.15551, 136.81879 35.1...   \n",
       "287051498  1161617447 0    LINESTRING (136.84672 35.12402, 136.84672 35.1...   \n",
       "           3909362365 0    LINESTRING (136.84672 35.12402, 136.84555 35.1...   \n",
       "\n",
       "                           distance_risk_score  ...  oneway   length  \\\n",
       "u          v          key                       ...                    \n",
       "287037206  6418759114 0                    8.0  ...    True  549.217   \n",
       "           8687399278 0                    6.0  ...    True  717.481   \n",
       "8687399278 7162166992 0                    8.0  ...    True  211.954   \n",
       "287051498  1161617447 0                    9.0  ...   False   12.298   \n",
       "           3909362365 0                    8.0  ...    True  106.927   \n",
       "\n",
       "                                       bridge lanes           ref  \\\n",
       "u          v          key                                           \n",
       "287037206  6418759114 0    ['yes', 'viaduct']     2  ['E23', '5']   \n",
       "           8687399278 0                   yes   nan           nan   \n",
       "8687399278 7162166992 0                   yes   nan           nan   \n",
       "287051498  1161617447 0                   nan   nan           nan   \n",
       "           3909362365 0                   nan     2             1   \n",
       "\n",
       "                                                name est_width maxspeed  \\\n",
       "u          v          key                                                 \n",
       "287037206  6418759114 0    ['東名阪自動車道', '名古屋高速5号万場線']       NaN       60   \n",
       "           8687399278 0                  名古屋第二環状自動車道       NaN       60   \n",
       "8687399278 7162166992 0                  名古屋第二環状自動車道       NaN       60   \n",
       "287051498  1161617447 0                          nan       NaN       30   \n",
       "           3909362365 0                         国道1号       NaN       60   \n",
       "\n",
       "                          tunnel                           uv  \n",
       "u          v          key                                      \n",
       "287037206  6418759114 0      NaN   (287037206, 6418759114, 0)  \n",
       "           8687399278 0      NaN   (287037206, 8687399278, 0)  \n",
       "8687399278 7162166992 0      NaN  (8687399278, 7162166992, 0)  \n",
       "287051498  1161617447 0      NaN   (287051498, 1161617447, 0)  \n",
       "           3909362365 0      NaN   (287051498, 3909362365, 0)  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combine_score.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "bea19429",
   "metadata": {},
   "outputs": [],
   "source": [
    "combine_score=combine_score.loc[:,['osmid', 'highway', 'oneway',\n",
    "         'length', 'bridge', 'lanes', 'ref', 'name', 'est_width', 'maxspeed',\n",
    "          'tunnel', 'distance_risk_score',\n",
    "         'building_count', 'earthquake_risk','geometry']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "d434d9c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20092"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(combine_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "1f60f65f",
   "metadata": {},
   "outputs": [],
   "source": [
    "combineG=ox.utils_graph.graph_from_gdfs(nodes,combine_score, graph_attrs=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "0bd76ff5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 576x576 with 1 Axes>, <AxesSubplot:>)"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ox.plot_graph(combineG)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "6a2be6a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "nx.write_gpickle(combineG, \"data/combined_score_addded.pickle\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}