1月8号KH-1线路的站点间OD.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b89d350b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#运行这个代码可以让Python不显示warnings\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import geopandas\n",
    "import geopandas as gpd\n",
    "import pyproj"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c7aed683",
   "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>grid_id</th>\n",
       "      <th>centre_lng</th>\n",
       "      <th>centre_lat</th>\n",
       "      <th>left_up_lng</th>\n",
       "      <th>left_up_lat</th>\n",
       "      <th>left_down_lng</th>\n",
       "      <th>left_down_lat</th>\n",
       "      <th>right_up_lng</th>\n",
       "      <th>right_up_lat</th>\n",
       "      <th>right_down_lng</th>\n",
       "      <th>right_down_lat</th>\n",
       "      <th>city_id</th>\n",
       "      <th>city_name</th>\n",
       "      <th>district_id</th>\n",
       "      <th>district_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ww56mus</td>\n",
       "      <td>117.329178</td>\n",
       "      <td>34.170914</td>\n",
       "      <td>117.328491</td>\n",
       "      <td>34.171600</td>\n",
       "      <td>117.328491</td>\n",
       "      <td>34.170227</td>\n",
       "      <td>117.329864</td>\n",
       "      <td>34.171600</td>\n",
       "      <td>117.329864</td>\n",
       "      <td>34.170227</td>\n",
       "      <td>1000516</td>\n",
       "      <td>徐州市</td>\n",
       "      <td>320303</td>\n",
       "      <td>云龙区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ww56gwd</td>\n",
       "      <td>117.227554</td>\n",
       "      <td>34.269791</td>\n",
       "      <td>117.226868</td>\n",
       "      <td>34.270477</td>\n",
       "      <td>117.226868</td>\n",
       "      <td>34.269104</td>\n",
       "      <td>117.228241</td>\n",
       "      <td>34.270477</td>\n",
       "      <td>117.228241</td>\n",
       "      <td>34.269104</td>\n",
       "      <td>1000516</td>\n",
       "      <td>徐州市</td>\n",
       "      <td>320303</td>\n",
       "      <td>云龙区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ww56s9g</td>\n",
       "      <td>117.272873</td>\n",
       "      <td>34.199753</td>\n",
       "      <td>117.272186</td>\n",
       "      <td>34.200439</td>\n",
       "      <td>117.272186</td>\n",
       "      <td>34.199066</td>\n",
       "      <td>117.273560</td>\n",
       "      <td>34.200439</td>\n",
       "      <td>117.273560</td>\n",
       "      <td>34.199066</td>\n",
       "      <td>1000516</td>\n",
       "      <td>徐州市</td>\n",
       "      <td>320303</td>\n",
       "      <td>云龙区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ww56g5p</td>\n",
       "      <td>117.212448</td>\n",
       "      <td>34.250565</td>\n",
       "      <td>117.211761</td>\n",
       "      <td>34.251251</td>\n",
       "      <td>117.211761</td>\n",
       "      <td>34.249878</td>\n",
       "      <td>117.213135</td>\n",
       "      <td>34.251251</td>\n",
       "      <td>117.213135</td>\n",
       "      <td>34.249878</td>\n",
       "      <td>1000516</td>\n",
       "      <td>徐州市</td>\n",
       "      <td>320303</td>\n",
       "      <td>云龙区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ww56gqz</td>\n",
       "      <td>117.223434</td>\n",
       "      <td>34.271164</td>\n",
       "      <td>117.222748</td>\n",
       "      <td>34.271851</td>\n",
       "      <td>117.222748</td>\n",
       "      <td>34.270477</td>\n",
       "      <td>117.224121</td>\n",
       "      <td>34.271851</td>\n",
       "      <td>117.224121</td>\n",
       "      <td>34.270477</td>\n",
       "      <td>1000516</td>\n",
       "      <td>徐州市</td>\n",
       "      <td>320303</td>\n",
       "      <td>云龙区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151455</th>\n",
       "      <td>ww57367</td>\n",
       "      <td>117.130051</td>\n",
       "      <td>34.334335</td>\n",
       "      <td>117.129364</td>\n",
       "      <td>34.335022</td>\n",
       "      <td>117.129364</td>\n",
       "      <td>34.333649</td>\n",
       "      <td>117.130737</td>\n",
       "      <td>34.335022</td>\n",
       "      <td>117.130737</td>\n",
       "      <td>34.333649</td>\n",
       "      <td>1000516</td>\n",
       "      <td>徐州市</td>\n",
       "      <td>320302</td>\n",
       "      <td>鼓楼区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151456</th>\n",
       "      <td>ww5739q</td>\n",
       "      <td>117.145157</td>\n",
       "      <td>34.328842</td>\n",
       "      <td>117.144470</td>\n",
       "      <td>34.329529</td>\n",
       "      <td>117.144470</td>\n",
       "      <td>34.328156</td>\n",
       "      <td>117.145843</td>\n",
       "      <td>34.329529</td>\n",
       "      <td>117.145843</td>\n",
       "      <td>34.328156</td>\n",
       "      <td>1000516</td>\n",
       "      <td>徐州市</td>\n",
       "      <td>320302</td>\n",
       "      <td>鼓楼区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151457</th>\n",
       "      <td>ww57662</td>\n",
       "      <td>117.169876</td>\n",
       "      <td>34.334335</td>\n",
       "      <td>117.169190</td>\n",
       "      <td>34.335022</td>\n",
       "      <td>117.169190</td>\n",
       "      <td>34.333649</td>\n",
       "      <td>117.170563</td>\n",
       "      <td>34.335022</td>\n",
       "      <td>117.170563</td>\n",
       "      <td>34.333649</td>\n",
       "      <td>1000516</td>\n",
       "      <td>徐州市</td>\n",
       "      <td>320302</td>\n",
       "      <td>鼓楼区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151458</th>\n",
       "      <td>ww57638</td>\n",
       "      <td>117.169876</td>\n",
       "      <td>34.330215</td>\n",
       "      <td>117.169190</td>\n",
       "      <td>34.330902</td>\n",
       "      <td>117.169190</td>\n",
       "      <td>34.329529</td>\n",
       "      <td>117.170563</td>\n",
       "      <td>34.330902</td>\n",
       "      <td>117.170563</td>\n",
       "      <td>34.329529</td>\n",
       "      <td>1000516</td>\n",
       "      <td>徐州市</td>\n",
       "      <td>320302</td>\n",
       "      <td>鼓楼区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151459</th>\n",
       "      <td>ww57397</td>\n",
       "      <td>117.141037</td>\n",
       "      <td>34.328842</td>\n",
       "      <td>117.140350</td>\n",
       "      <td>34.329529</td>\n",
       "      <td>117.140350</td>\n",
       "      <td>34.328156</td>\n",
       "      <td>117.141724</td>\n",
       "      <td>34.329529</td>\n",
       "      <td>117.141724</td>\n",
       "      <td>34.328156</td>\n",
       "      <td>1000516</td>\n",
       "      <td>徐州市</td>\n",
       "      <td>320302</td>\n",
       "      <td>鼓楼区</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>151460 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        grid_id  centre_lng  centre_lat  left_up_lng  left_up_lat  \\\n",
       "0       ww56mus  117.329178   34.170914   117.328491    34.171600   \n",
       "1       ww56gwd  117.227554   34.269791   117.226868    34.270477   \n",
       "2       ww56s9g  117.272873   34.199753   117.272186    34.200439   \n",
       "3       ww56g5p  117.212448   34.250565   117.211761    34.251251   \n",
       "4       ww56gqz  117.223434   34.271164   117.222748    34.271851   \n",
       "...         ...         ...         ...          ...          ...   \n",
       "151455  ww57367  117.130051   34.334335   117.129364    34.335022   \n",
       "151456  ww5739q  117.145157   34.328842   117.144470    34.329529   \n",
       "151457  ww57662  117.169876   34.334335   117.169190    34.335022   \n",
       "151458  ww57638  117.169876   34.330215   117.169190    34.330902   \n",
       "151459  ww57397  117.141037   34.328842   117.140350    34.329529   \n",
       "\n",
       "        left_down_lng  left_down_lat  right_up_lng  right_up_lat  \\\n",
       "0          117.328491      34.170227    117.329864     34.171600   \n",
       "1          117.226868      34.269104    117.228241     34.270477   \n",
       "2          117.272186      34.199066    117.273560     34.200439   \n",
       "3          117.211761      34.249878    117.213135     34.251251   \n",
       "4          117.222748      34.270477    117.224121     34.271851   \n",
       "...               ...            ...           ...           ...   \n",
       "151455     117.129364      34.333649    117.130737     34.335022   \n",
       "151456     117.144470      34.328156    117.145843     34.329529   \n",
       "151457     117.169190      34.333649    117.170563     34.335022   \n",
       "151458     117.169190      34.329529    117.170563     34.330902   \n",
       "151459     117.140350      34.328156    117.141724     34.329529   \n",
       "\n",
       "        right_down_lng  right_down_lat  city_id city_name  district_id  \\\n",
       "0           117.329864       34.170227  1000516       徐州市       320303   \n",
       "1           117.228241       34.269104  1000516       徐州市       320303   \n",
       "2           117.273560       34.199066  1000516       徐州市       320303   \n",
       "3           117.213135       34.249878  1000516       徐州市       320303   \n",
       "4           117.224121       34.270477  1000516       徐州市       320303   \n",
       "...                ...             ...      ...       ...          ...   \n",
       "151455      117.130737       34.333649  1000516       徐州市       320302   \n",
       "151456      117.145843       34.328156  1000516       徐州市       320302   \n",
       "151457      117.170563       34.333649  1000516       徐州市       320302   \n",
       "151458      117.170563       34.329529  1000516       徐州市       320302   \n",
       "151459      117.141724       34.328156  1000516       徐州市       320302   \n",
       "\n",
       "       district_name  \n",
       "0                云龙区  \n",
       "1                云龙区  \n",
       "2                云龙区  \n",
       "3                云龙区  \n",
       "4                云龙区  \n",
       "...              ...  \n",
       "151455           鼓楼区  \n",
       "151456           鼓楼区  \n",
       "151457           鼓楼区  \n",
       "151458           鼓楼区  \n",
       "151459           鼓楼区  \n",
       "\n",
       "[151460 rows x 15 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xinling = pd.read_csv(r'F:\\徐州\\xuzhou徐州五区县网格2.csv',encoding='gbk')\n",
    "#arrive2.columns=['日期','出发时间','D编号','到达人数','O编号','出发人数']\n",
    "xinling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "423dd573",
   "metadata": {},
   "outputs": [],
   "source": [
    "xinling['区编号']=xinling.iloc[:,0]\n",
    "xinling['经度']=xinling.iloc[:,1]\n",
    "xinling['纬度']=xinling.iloc[:,2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7e678b6a",
   "metadata": {
    "scrolled": true
   },
   "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>区编号</th>\n",
       "      <th>经度</th>\n",
       "      <th>纬度</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ww56mus</td>\n",
       "      <td>117.329178</td>\n",
       "      <td>34.170914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ww56gwd</td>\n",
       "      <td>117.227554</td>\n",
       "      <td>34.269791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ww56s9g</td>\n",
       "      <td>117.272873</td>\n",
       "      <td>34.199753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ww56g5p</td>\n",
       "      <td>117.212448</td>\n",
       "      <td>34.250565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ww56gqz</td>\n",
       "      <td>117.223434</td>\n",
       "      <td>34.271164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151455</th>\n",
       "      <td>ww57367</td>\n",
       "      <td>117.130051</td>\n",
       "      <td>34.334335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151456</th>\n",
       "      <td>ww5739q</td>\n",
       "      <td>117.145157</td>\n",
       "      <td>34.328842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151457</th>\n",
       "      <td>ww57662</td>\n",
       "      <td>117.169876</td>\n",
       "      <td>34.334335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151458</th>\n",
       "      <td>ww57638</td>\n",
       "      <td>117.169876</td>\n",
       "      <td>34.330215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151459</th>\n",
       "      <td>ww57397</td>\n",
       "      <td>117.141037</td>\n",
       "      <td>34.328842</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>151460 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            区编号          经度         纬度\n",
       "0       ww56mus  117.329178  34.170914\n",
       "1       ww56gwd  117.227554  34.269791\n",
       "2       ww56s9g  117.272873  34.199753\n",
       "3       ww56g5p  117.212448  34.250565\n",
       "4       ww56gqz  117.223434  34.271164\n",
       "...         ...         ...        ...\n",
       "151455  ww57367  117.130051  34.334335\n",
       "151456  ww5739q  117.145157  34.328842\n",
       "151457  ww57662  117.169876  34.334335\n",
       "151458  ww57638  117.169876  34.330215\n",
       "151459  ww57397  117.141037  34.328842\n",
       "\n",
       "[151460 rows x 3 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "QSY=xinling.loc[:,['区编号','经度','纬度']]\n",
    "QSY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "899e0c63",
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas\n",
    "import matplotlib.pyplot as plt\n",
    "line = geopandas.read_file(r'F:\\徐州\\线路\\线路.shp',encoding='gbk')\n",
    "stop=pd.read_excel(r'F:\\徐州\\表格\\KH-1站点.xls')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "445635c8",
   "metadata": {
    "scrolled": true
   },
   "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>FID</th>\n",
       "      <th>stopcode</th>\n",
       "      <th>stopname</th>\n",
       "      <th>经度</th>\n",
       "      <th>纬度</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>210121</td>\n",
       "      <td>九里山(北)</td>\n",
       "      <td>117.135633</td>\n",
       "      <td>34.280820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>XYRJCZ</td>\n",
       "      <td>西苑人家(场站)</td>\n",
       "      <td>117.135832</td>\n",
       "      <td>34.277209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td></td>\n",
       "      <td>中海九樾</td>\n",
       "      <td>117.143105</td>\n",
       "      <td>34.281774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>ZWYN</td>\n",
       "      <td>徐州植物园(南)</td>\n",
       "      <td>117.154076</td>\n",
       "      <td>34.280838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>60070</td>\n",
       "      <td>诚坤钢材市场(北)</td>\n",
       "      <td>117.165993</td>\n",
       "      <td>34.283159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>6120020</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "      <td>117.178249</td>\n",
       "      <td>34.285274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>120100</td>\n",
       "      <td>建材中专(南)</td>\n",
       "      <td>117.186812</td>\n",
       "      <td>34.285349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>670121</td>\n",
       "      <td>堤北农贸市场|二环路(北)</td>\n",
       "      <td>117.195917</td>\n",
       "      <td>34.285544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>670190</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>117.213182</td>\n",
       "      <td>34.285629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>670220</td>\n",
       "      <td>杨庄(南)</td>\n",
       "      <td>117.226433</td>\n",
       "      <td>34.291450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>GLFYX</td>\n",
       "      <td>鼓楼法院(西)</td>\n",
       "      <td>117.235048</td>\n",
       "      <td>34.293996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>KFQZX2</td>\n",
       "      <td>开发区中学2</td>\n",
       "      <td>117.248011</td>\n",
       "      <td>34.288649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>30100</td>\n",
       "      <td>金山桥公交停车场(东)</td>\n",
       "      <td>117.255128</td>\n",
       "      <td>34.291032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td></td>\n",
       "      <td>宝莲寺</td>\n",
       "      <td>117.262351</td>\n",
       "      <td>34.293597</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    FID stopcode       stopname          经度         纬度\n",
       "6     6   210121         九里山(北)  117.135633  34.280820\n",
       "10   10   XYRJCZ       西苑人家(场站)  117.135832  34.277209\n",
       "12   12                    中海九樾  117.143105  34.281774\n",
       "8     8     ZWYN       徐州植物园(南)  117.154076  34.280838\n",
       "5     5    60070      诚坤钢材市场(北)  117.165993  34.283159\n",
       "1     1  6120020       九龙湖公园(南)  117.178249  34.285274\n",
       "0     0   120100        建材中专(南)  117.186812  34.285349\n",
       "4     4   670121  堤北农贸市场|二环路(北)  117.195917  34.285544\n",
       "2     2   670190        二九宿舍(南)  117.213182  34.285629\n",
       "3     3   670220          杨庄(南)  117.226433  34.291450\n",
       "9     9    GLFYX        鼓楼法院(西)  117.235048  34.293996\n",
       "11   11   KFQZX2         开发区中学2  117.248011  34.288649\n",
       "7     7    30100    金山桥公交停车场(东)  117.255128  34.291032\n",
       "13   13                     宝莲寺  117.262351  34.293597"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stop=stop.sort_values(by='经度')\n",
    "stop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e0a4525e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#-*-coding=utf-8 -*-\\n\",\n",
    "import pyproj\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "#data = pd.read_csv(\\\"test.csv\\\",sep=',',header='infer')#将第一行作为表头,\n",
    "p1 = pyproj.Proj(init=\"epsg:4326\")#wgs坐标系统的EPSG Code,\n",
    "p2 = pyproj.Proj(init=\"epsg:32651\")#UTM 51N坐标系统的EPSG Code\\n\",\n",
    "lonprj, latprj = pyproj.transform(p1, p2,stop['经度'], stop['纬度'])\n",
    "lonprj3, latprj3 = pyproj.transform(p1, p2,QSY['经度'], QSY['纬度'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cce3745f",
   "metadata": {},
   "outputs": [],
   "source": [
    "##将数组转换为PD\\n\",\n",
    "stop['lons']=pd.DataFrame(lonprj)\n",
    "stop['lats']=pd.DataFrame(latprj)\n",
    "#line['lons']=pd.DataFrame(lonprj2)\n",
    "#line['lats']=pd.DataFrame(latprj2)\n",
    "QSY['lons']=pd.DataFrame(lonprj3)\n",
    "QSY['lats']=pd.DataFrame(latprj3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8e8718f2",
   "metadata": {
    "scrolled": true
   },
   "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>FID</th>\n",
       "      <th>stopcode</th>\n",
       "      <th>stopname</th>\n",
       "      <th>经度</th>\n",
       "      <th>纬度</th>\n",
       "      <th>lons</th>\n",
       "      <th>lats</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>210121</td>\n",
       "      <td>九里山(北)</td>\n",
       "      <td>117.135633</td>\n",
       "      <td>34.280820</td>\n",
       "      <td>-35371.115984</td>\n",
       "      <td>3.809126e+06</td>\n",
       "      <td>POINT (-35371.11598390527 3809126.27149845)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>XYRJCZ</td>\n",
       "      <td>西苑人家(场站)</td>\n",
       "      <td>117.135832</td>\n",
       "      <td>34.277209</td>\n",
       "      <td>-30868.628715</td>\n",
       "      <td>3.809833e+06</td>\n",
       "      <td>POINT (-30868.62871548999 3809832.7291986453)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td></td>\n",
       "      <td>中海九樾</td>\n",
       "      <td>117.143105</td>\n",
       "      <td>34.281774</td>\n",
       "      <td>-29035.955572</td>\n",
       "      <td>3.809398e+06</td>\n",
       "      <td>POINT (-29035.95557169034 3809398.4323940463)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>ZWYN</td>\n",
       "      <td>徐州植物园(南)</td>\n",
       "      <td>117.154076</td>\n",
       "      <td>34.280838</td>\n",
       "      <td>-32937.790434</td>\n",
       "      <td>3.809018e+06</td>\n",
       "      <td>POINT (-32937.790433969116 3809018.192193212)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>60070</td>\n",
       "      <td>诚坤钢材市场(北)</td>\n",
       "      <td>117.165993</td>\n",
       "      <td>34.283159</td>\n",
       "      <td>-36161.275042</td>\n",
       "      <td>3.809163e+06</td>\n",
       "      <td>POINT (-36161.27504204004 3809163.1900935313)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>6120020</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "      <td>117.178249</td>\n",
       "      <td>34.285274</td>\n",
       "      <td>-40124.510910</td>\n",
       "      <td>3.808493e+06</td>\n",
       "      <td>POINT (-40124.510909937904 3808492.723794836)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>120100</td>\n",
       "      <td>建材中专(南)</td>\n",
       "      <td>117.186812</td>\n",
       "      <td>34.285349</td>\n",
       "      <td>-40119.598338</td>\n",
       "      <td>3.808895e+06</td>\n",
       "      <td>POINT (-40119.59833793016 3808894.9726925436)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>670121</td>\n",
       "      <td>堤北农贸市场|二环路(北)</td>\n",
       "      <td>117.195917</td>\n",
       "      <td>34.285544</td>\n",
       "      <td>-37304.952052</td>\n",
       "      <td>3.808993e+06</td>\n",
       "      <td>POINT (-37304.95205151627 3808993.2155954926)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>670190</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>117.213182</td>\n",
       "      <td>34.285629</td>\n",
       "      <td>-39424.457030</td>\n",
       "      <td>3.808961e+06</td>\n",
       "      <td>POINT (-39424.45702975185 3808961.078141681)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>670220</td>\n",
       "      <td>杨庄(南)</td>\n",
       "      <td>117.226433</td>\n",
       "      <td>34.291450</td>\n",
       "      <td>-38418.762596</td>\n",
       "      <td>3.808799e+06</td>\n",
       "      <td>POINT (-38418.7625962653 3808798.6800883734)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>GLFYX</td>\n",
       "      <td>鼓楼法院(西)</td>\n",
       "      <td>117.235048</td>\n",
       "      <td>34.293996</td>\n",
       "      <td>-31679.098141</td>\n",
       "      <td>3.809595e+06</td>\n",
       "      <td>POINT (-31679.098140898743 3809595.15839898)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>KFQZX2</td>\n",
       "      <td>开发区中学2</td>\n",
       "      <td>117.248011</td>\n",
       "      <td>34.288649</td>\n",
       "      <td>-29707.210525</td>\n",
       "      <td>3.809171e+06</td>\n",
       "      <td>POINT (-29707.210525320144 3809170.8619969385)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>30100</td>\n",
       "      <td>金山桥公交停车场(东)</td>\n",
       "      <td>117.255128</td>\n",
       "      <td>34.291032</td>\n",
       "      <td>-34530.302321</td>\n",
       "      <td>3.809100e+06</td>\n",
       "      <td>POINT (-34530.302320748335 3809099.795096339)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td></td>\n",
       "      <td>宝莲寺</td>\n",
       "      <td>117.262351</td>\n",
       "      <td>34.293597</td>\n",
       "      <td>-28353.836794</td>\n",
       "      <td>3.809646e+06</td>\n",
       "      <td>POINT (-28353.836794012925 3809645.6000315594)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    FID stopcode       stopname          经度         纬度          lons  \\\n",
       "6     6   210121         九里山(北)  117.135633  34.280820 -35371.115984   \n",
       "10   10   XYRJCZ       西苑人家(场站)  117.135832  34.277209 -30868.628715   \n",
       "12   12                    中海九樾  117.143105  34.281774 -29035.955572   \n",
       "8     8     ZWYN       徐州植物园(南)  117.154076  34.280838 -32937.790434   \n",
       "5     5    60070      诚坤钢材市场(北)  117.165993  34.283159 -36161.275042   \n",
       "1     1  6120020       九龙湖公园(南)  117.178249  34.285274 -40124.510910   \n",
       "0     0   120100        建材中专(南)  117.186812  34.285349 -40119.598338   \n",
       "4     4   670121  堤北农贸市场|二环路(北)  117.195917  34.285544 -37304.952052   \n",
       "2     2   670190        二九宿舍(南)  117.213182  34.285629 -39424.457030   \n",
       "3     3   670220          杨庄(南)  117.226433  34.291450 -38418.762596   \n",
       "9     9    GLFYX        鼓楼法院(西)  117.235048  34.293996 -31679.098141   \n",
       "11   11   KFQZX2         开发区中学2  117.248011  34.288649 -29707.210525   \n",
       "7     7    30100    金山桥公交停车场(东)  117.255128  34.291032 -34530.302321   \n",
       "13   13                     宝莲寺  117.262351  34.293597 -28353.836794   \n",
       "\n",
       "            lats                                        geometry  \n",
       "6   3.809126e+06     POINT (-35371.11598390527 3809126.27149845)  \n",
       "10  3.809833e+06   POINT (-30868.62871548999 3809832.7291986453)  \n",
       "12  3.809398e+06   POINT (-29035.95557169034 3809398.4323940463)  \n",
       "8   3.809018e+06   POINT (-32937.790433969116 3809018.192193212)  \n",
       "5   3.809163e+06   POINT (-36161.27504204004 3809163.1900935313)  \n",
       "1   3.808493e+06   POINT (-40124.510909937904 3808492.723794836)  \n",
       "0   3.808895e+06   POINT (-40119.59833793016 3808894.9726925436)  \n",
       "4   3.808993e+06   POINT (-37304.95205151627 3808993.2155954926)  \n",
       "2   3.808961e+06    POINT (-39424.45702975185 3808961.078141681)  \n",
       "3   3.808799e+06    POINT (-38418.7625962653 3808798.6800883734)  \n",
       "9   3.809595e+06    POINT (-31679.098140898743 3809595.15839898)  \n",
       "11  3.809171e+06  POINT (-29707.210525320144 3809170.8619969385)  \n",
       "7   3.809100e+06   POINT (-34530.302320748335 3809099.795096339)  \n",
       "13  3.809646e+06  POINT (-28353.836794012925 3809645.6000315594)  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "594d7390",
   "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>区编号</th>\n",
       "      <th>经度</th>\n",
       "      <th>纬度</th>\n",
       "      <th>lons</th>\n",
       "      <th>lats</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ww56mus</td>\n",
       "      <td>117.329178</td>\n",
       "      <td>34.170914</td>\n",
       "      <td>-22953.956952</td>\n",
       "      <td>3.795671e+06</td>\n",
       "      <td>POINT (-22953.956951656553 3795670.852514178)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ww56gwd</td>\n",
       "      <td>117.227554</td>\n",
       "      <td>34.269791</td>\n",
       "      <td>-31712.680638</td>\n",
       "      <td>3.807183e+06</td>\n",
       "      <td>POINT (-31712.680638363352 3807183.140981803)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ww56s9g</td>\n",
       "      <td>117.272873</td>\n",
       "      <td>34.199753</td>\n",
       "      <td>-27972.154486</td>\n",
       "      <td>3.799166e+06</td>\n",
       "      <td>POINT (-27972.15448565688 3799165.896358251)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ww56g5p</td>\n",
       "      <td>117.212448</td>\n",
       "      <td>34.250565</td>\n",
       "      <td>-33227.754585</td>\n",
       "      <td>3.805127e+06</td>\n",
       "      <td>POINT (-33227.75458505633 3805126.7115265634)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ww56gqz</td>\n",
       "      <td>117.223434</td>\n",
       "      <td>34.271164</td>\n",
       "      <td>-32083.954936</td>\n",
       "      <td>3.807357e+06</td>\n",
       "      <td>POINT (-32083.954935508664 3807357.337184346)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151455</th>\n",
       "      <td>ww57367</td>\n",
       "      <td>117.130051</td>\n",
       "      <td>34.334335</td>\n",
       "      <td>-40289.916609</td>\n",
       "      <td>3.814870e+06</td>\n",
       "      <td>POINT (-40289.91660904547 3814870.112977421)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151456</th>\n",
       "      <td>ww5739q</td>\n",
       "      <td>117.145157</td>\n",
       "      <td>34.328842</td>\n",
       "      <td>-38933.016510</td>\n",
       "      <td>3.814179e+06</td>\n",
       "      <td>POINT (-38933.01651049976 3814179.2181995884)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151457</th>\n",
       "      <td>ww57662</td>\n",
       "      <td>117.169876</td>\n",
       "      <td>34.334335</td>\n",
       "      <td>-36619.618067</td>\n",
       "      <td>3.814658e+06</td>\n",
       "      <td>POINT (-36619.61806662788 3814658.0036518783)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151458</th>\n",
       "      <td>ww57638</td>\n",
       "      <td>117.169876</td>\n",
       "      <td>34.330215</td>\n",
       "      <td>-36645.976475</td>\n",
       "      <td>3.814200e+06</td>\n",
       "      <td>POINT (-36645.97647538001 3814200.309984983)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151459</th>\n",
       "      <td>ww57397</td>\n",
       "      <td>117.141037</td>\n",
       "      <td>34.328842</td>\n",
       "      <td>-39312.732220</td>\n",
       "      <td>3.814201e+06</td>\n",
       "      <td>POINT (-39312.7322198333 3814201.185110974)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>151460 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            区编号          经度         纬度          lons          lats  \\\n",
       "0       ww56mus  117.329178  34.170914 -22953.956952  3.795671e+06   \n",
       "1       ww56gwd  117.227554  34.269791 -31712.680638  3.807183e+06   \n",
       "2       ww56s9g  117.272873  34.199753 -27972.154486  3.799166e+06   \n",
       "3       ww56g5p  117.212448  34.250565 -33227.754585  3.805127e+06   \n",
       "4       ww56gqz  117.223434  34.271164 -32083.954936  3.807357e+06   \n",
       "...         ...         ...        ...           ...           ...   \n",
       "151455  ww57367  117.130051  34.334335 -40289.916609  3.814870e+06   \n",
       "151456  ww5739q  117.145157  34.328842 -38933.016510  3.814179e+06   \n",
       "151457  ww57662  117.169876  34.334335 -36619.618067  3.814658e+06   \n",
       "151458  ww57638  117.169876  34.330215 -36645.976475  3.814200e+06   \n",
       "151459  ww57397  117.141037  34.328842 -39312.732220  3.814201e+06   \n",
       "\n",
       "                                             geometry  \n",
       "0       POINT (-22953.956951656553 3795670.852514178)  \n",
       "1       POINT (-31712.680638363352 3807183.140981803)  \n",
       "2        POINT (-27972.15448565688 3799165.896358251)  \n",
       "3       POINT (-33227.75458505633 3805126.7115265634)  \n",
       "4       POINT (-32083.954935508664 3807357.337184346)  \n",
       "...                                               ...  \n",
       "151455   POINT (-40289.91660904547 3814870.112977421)  \n",
       "151456  POINT (-38933.01651049976 3814179.2181995884)  \n",
       "151457  POINT (-36619.61806662788 3814658.0036518783)  \n",
       "151458   POINT (-36645.97647538001 3814200.309984983)  \n",
       "151459    POINT (-39312.7322198333 3814201.185110974)  \n",
       "\n",
       "[151460 rows x 6 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "QSY"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ac1f4ca",
   "metadata": {
    "scrolled": true
   },
   "source": [
    "#生成线路的线要素\n",
    "from shapely.geometry import LineString\n",
    "dianlon=line['lons']\n",
    "dianlat=line['lats']\n",
    "dianlist=[]\n",
    "for i in range(0,len(line)):\n",
    "    g=(dianlon[i],dianlat[i])\n",
    "    dianlist.append(g)\n",
    "    pass\n",
    "dianlist\n",
    "linestr = LineString(dianlist)\n",
    "line['geometry']=linestr\n",
    "line['geometry']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "b2d5a7d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "###将所有小区匹配到最近的站点上\n",
    "#for k in range(0,len(lineQSY)):\n",
    "match=[]\n",
    "nearestd=[]\n",
    "for k in range(0,len(QSY)):###range写法要求索引连续完整\n",
    "    distance=[]\n",
    "    for i in range(0,len(stop)):        \n",
    "        x1 = stop.loc[i,'lons']\n",
    "        y1 = stop.loc[i,'lats']\n",
    "        x2 = QSY.loc[k,'lons']\n",
    "        y2 = QSY.loc[k,'lats']\n",
    "        #print(math.sqrt((x2-x1)**2+(y2-y1)**2))\n",
    "        distance.append(math.sqrt((x2-x1)**2+(y2-y1)**2))\n",
    "    #print(distance)\n",
    "    #print(len(distance))\n",
    "    # 求列表最小值及索引\n",
    "    min_value = min(distance) # 求列表最小值\n",
    "    min_idx = distance.index(min_value) # 求最小值对应索引\n",
    "    #print(min_value)\n",
    "    #print(min_idx )\n",
    "    nearestd.append(min_value)\n",
    "    match.append(min_idx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b5f370f3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "###最近站点整理\n",
    "QSY['最近站名索引']=match\n",
    "QSY['最近站距离']=nearestd\n",
    "QSY['最近站名']=None\n",
    "QSY['最近站编号']=None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "44fb697f",
   "metadata": {
    "scrolled": true
   },
   "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>区编号</th>\n",
       "      <th>经度</th>\n",
       "      <th>纬度</th>\n",
       "      <th>lons</th>\n",
       "      <th>lats</th>\n",
       "      <th>geometry</th>\n",
       "      <th>最近站名索引</th>\n",
       "      <th>最近站距离</th>\n",
       "      <th>最近站名</th>\n",
       "      <th>最近站编号</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ww56mus</td>\n",
       "      <td>117.329178</td>\n",
       "      <td>34.170914</td>\n",
       "      <td>-22953.956952</td>\n",
       "      <td>3.795671e+06</td>\n",
       "      <td>POINT (-22953.956951656553 3795670.852514178)</td>\n",
       "      <td>13</td>\n",
       "      <td>14981.731225</td>\n",
       "      <td>宝莲寺</td>\n",
       "      <td>宝莲寺</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ww56gwd</td>\n",
       "      <td>117.227554</td>\n",
       "      <td>34.269791</td>\n",
       "      <td>-31712.680638</td>\n",
       "      <td>3.807183e+06</td>\n",
       "      <td>POINT (-31712.680638363352 3807183.140981803)</td>\n",
       "      <td>8</td>\n",
       "      <td>2206.424021</td>\n",
       "      <td>徐州植物园(南)</td>\n",
       "      <td>徐州植物园(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ww56s9g</td>\n",
       "      <td>117.272873</td>\n",
       "      <td>34.199753</td>\n",
       "      <td>-27972.154486</td>\n",
       "      <td>3.799166e+06</td>\n",
       "      <td>POINT (-27972.15448565688 3799165.896358251)</td>\n",
       "      <td>11</td>\n",
       "      <td>10154.297459</td>\n",
       "      <td>开发区中学2</td>\n",
       "      <td>开发区中学2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ww56g5p</td>\n",
       "      <td>117.212448</td>\n",
       "      <td>34.250565</td>\n",
       "      <td>-33227.754585</td>\n",
       "      <td>3.805127e+06</td>\n",
       "      <td>POINT (-33227.75458505633 3805126.7115265634)</td>\n",
       "      <td>8</td>\n",
       "      <td>3902.268698</td>\n",
       "      <td>徐州植物园(南)</td>\n",
       "      <td>徐州植物园(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ww56gqz</td>\n",
       "      <td>117.223434</td>\n",
       "      <td>34.271164</td>\n",
       "      <td>-32083.954936</td>\n",
       "      <td>3.807357e+06</td>\n",
       "      <td>POINT (-32083.954935508664 3807357.337184346)</td>\n",
       "      <td>8</td>\n",
       "      <td>1867.478091</td>\n",
       "      <td>徐州植物园(南)</td>\n",
       "      <td>徐州植物园(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151455</th>\n",
       "      <td>ww57367</td>\n",
       "      <td>117.130051</td>\n",
       "      <td>34.334335</td>\n",
       "      <td>-40289.916609</td>\n",
       "      <td>3.814870e+06</td>\n",
       "      <td>POINT (-40289.91660904547 3814870.112977421)</td>\n",
       "      <td>2</td>\n",
       "      <td>5972.077777</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151456</th>\n",
       "      <td>ww5739q</td>\n",
       "      <td>117.145157</td>\n",
       "      <td>34.328842</td>\n",
       "      <td>-38933.016510</td>\n",
       "      <td>3.814179e+06</td>\n",
       "      <td>POINT (-38933.01651049976 3814179.2181995884)</td>\n",
       "      <td>2</td>\n",
       "      <td>5241.230719</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151457</th>\n",
       "      <td>ww57662</td>\n",
       "      <td>117.169876</td>\n",
       "      <td>34.334335</td>\n",
       "      <td>-36619.618067</td>\n",
       "      <td>3.814658e+06</td>\n",
       "      <td>POINT (-36619.61806662788 3814658.0036518783)</td>\n",
       "      <td>5</td>\n",
       "      <td>5513.896478</td>\n",
       "      <td>诚坤钢材市场(北)</td>\n",
       "      <td>诚坤钢材市场(北)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151458</th>\n",
       "      <td>ww57638</td>\n",
       "      <td>117.169876</td>\n",
       "      <td>34.330215</td>\n",
       "      <td>-36645.976475</td>\n",
       "      <td>3.814200e+06</td>\n",
       "      <td>POINT (-36645.97647538001 3814200.309984983)</td>\n",
       "      <td>5</td>\n",
       "      <td>5060.386574</td>\n",
       "      <td>诚坤钢材市场(北)</td>\n",
       "      <td>诚坤钢材市场(北)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151459</th>\n",
       "      <td>ww57397</td>\n",
       "      <td>117.141037</td>\n",
       "      <td>34.328842</td>\n",
       "      <td>-39312.732220</td>\n",
       "      <td>3.814201e+06</td>\n",
       "      <td>POINT (-39312.7322198333 3814201.185110974)</td>\n",
       "      <td>2</td>\n",
       "      <td>5241.297882</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>151460 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            区编号          经度         纬度          lons          lats  \\\n",
       "0       ww56mus  117.329178  34.170914 -22953.956952  3.795671e+06   \n",
       "1       ww56gwd  117.227554  34.269791 -31712.680638  3.807183e+06   \n",
       "2       ww56s9g  117.272873  34.199753 -27972.154486  3.799166e+06   \n",
       "3       ww56g5p  117.212448  34.250565 -33227.754585  3.805127e+06   \n",
       "4       ww56gqz  117.223434  34.271164 -32083.954936  3.807357e+06   \n",
       "...         ...         ...        ...           ...           ...   \n",
       "151455  ww57367  117.130051  34.334335 -40289.916609  3.814870e+06   \n",
       "151456  ww5739q  117.145157  34.328842 -38933.016510  3.814179e+06   \n",
       "151457  ww57662  117.169876  34.334335 -36619.618067  3.814658e+06   \n",
       "151458  ww57638  117.169876  34.330215 -36645.976475  3.814200e+06   \n",
       "151459  ww57397  117.141037  34.328842 -39312.732220  3.814201e+06   \n",
       "\n",
       "                                             geometry  最近站名索引         最近站距离  \\\n",
       "0       POINT (-22953.956951656553 3795670.852514178)      13  14981.731225   \n",
       "1       POINT (-31712.680638363352 3807183.140981803)       8   2206.424021   \n",
       "2        POINT (-27972.15448565688 3799165.896358251)      11  10154.297459   \n",
       "3       POINT (-33227.75458505633 3805126.7115265634)       8   3902.268698   \n",
       "4       POINT (-32083.954935508664 3807357.337184346)       8   1867.478091   \n",
       "...                                               ...     ...           ...   \n",
       "151455   POINT (-40289.91660904547 3814870.112977421)       2   5972.077777   \n",
       "151456  POINT (-38933.01651049976 3814179.2181995884)       2   5241.230719   \n",
       "151457  POINT (-36619.61806662788 3814658.0036518783)       5   5513.896478   \n",
       "151458   POINT (-36645.97647538001 3814200.309984983)       5   5060.386574   \n",
       "151459    POINT (-39312.7322198333 3814201.185110974)       2   5241.297882   \n",
       "\n",
       "             最近站名      最近站编号  \n",
       "0             宝莲寺        宝莲寺  \n",
       "1        徐州植物园(南)   徐州植物园(南)  \n",
       "2          开发区中学2     开发区中学2  \n",
       "3        徐州植物园(南)   徐州植物园(南)  \n",
       "4        徐州植物园(南)   徐州植物园(南)  \n",
       "...           ...        ...  \n",
       "151455    二九宿舍(南)    二九宿舍(南)  \n",
       "151456    二九宿舍(南)    二九宿舍(南)  \n",
       "151457  诚坤钢材市场(北)  诚坤钢材市场(北)  \n",
       "151458  诚坤钢材市场(北)  诚坤钢材市场(北)  \n",
       "151459    二九宿舍(南)    二九宿舍(南)  \n",
       "\n",
       "[151460 rows x 10 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for k in range(0,len(QSY)):\n",
    "    sy=QSY['最近站名索引'].loc[k]\n",
    "    QSY['最近站名'].loc[k]=stop['stopname'].loc[sy]\n",
    "    QSY['最近站编号'].loc[k]=stop['stopname'].loc[sy]\n",
    "QSY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "4bc2a7fa",
   "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>区编号</th>\n",
       "      <th>经度</th>\n",
       "      <th>纬度</th>\n",
       "      <th>lons</th>\n",
       "      <th>lats</th>\n",
       "      <th>geometry</th>\n",
       "      <th>最近站名索引</th>\n",
       "      <th>最近站距离</th>\n",
       "      <th>最近站名</th>\n",
       "      <th>最近站编号</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ww56mus</td>\n",
       "      <td>117.329178</td>\n",
       "      <td>34.170914</td>\n",
       "      <td>-22953.956952</td>\n",
       "      <td>3.795671e+06</td>\n",
       "      <td>POINT (-22953.956951656553 3795670.852514178)</td>\n",
       "      <td>13</td>\n",
       "      <td>14981.731225</td>\n",
       "      <td>宝莲寺</td>\n",
       "      <td>宝莲寺</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ww56gwd</td>\n",
       "      <td>117.227554</td>\n",
       "      <td>34.269791</td>\n",
       "      <td>-31712.680638</td>\n",
       "      <td>3.807183e+06</td>\n",
       "      <td>POINT (-31712.680638363352 3807183.140981803)</td>\n",
       "      <td>8</td>\n",
       "      <td>2206.424021</td>\n",
       "      <td>徐州植物园(南)</td>\n",
       "      <td>徐州植物园(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ww56s9g</td>\n",
       "      <td>117.272873</td>\n",
       "      <td>34.199753</td>\n",
       "      <td>-27972.154486</td>\n",
       "      <td>3.799166e+06</td>\n",
       "      <td>POINT (-27972.15448565688 3799165.896358251)</td>\n",
       "      <td>11</td>\n",
       "      <td>10154.297459</td>\n",
       "      <td>开发区中学2</td>\n",
       "      <td>开发区中学2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ww56g5p</td>\n",
       "      <td>117.212448</td>\n",
       "      <td>34.250565</td>\n",
       "      <td>-33227.754585</td>\n",
       "      <td>3.805127e+06</td>\n",
       "      <td>POINT (-33227.75458505633 3805126.7115265634)</td>\n",
       "      <td>8</td>\n",
       "      <td>3902.268698</td>\n",
       "      <td>徐州植物园(南)</td>\n",
       "      <td>徐州植物园(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ww56gqz</td>\n",
       "      <td>117.223434</td>\n",
       "      <td>34.271164</td>\n",
       "      <td>-32083.954936</td>\n",
       "      <td>3.807357e+06</td>\n",
       "      <td>POINT (-32083.954935508664 3807357.337184346)</td>\n",
       "      <td>8</td>\n",
       "      <td>1867.478091</td>\n",
       "      <td>徐州植物园(南)</td>\n",
       "      <td>徐州植物园(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151455</th>\n",
       "      <td>ww57367</td>\n",
       "      <td>117.130051</td>\n",
       "      <td>34.334335</td>\n",
       "      <td>-40289.916609</td>\n",
       "      <td>3.814870e+06</td>\n",
       "      <td>POINT (-40289.91660904547 3814870.112977421)</td>\n",
       "      <td>2</td>\n",
       "      <td>5972.077777</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151456</th>\n",
       "      <td>ww5739q</td>\n",
       "      <td>117.145157</td>\n",
       "      <td>34.328842</td>\n",
       "      <td>-38933.016510</td>\n",
       "      <td>3.814179e+06</td>\n",
       "      <td>POINT (-38933.01651049976 3814179.2181995884)</td>\n",
       "      <td>2</td>\n",
       "      <td>5241.230719</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151457</th>\n",
       "      <td>ww57662</td>\n",
       "      <td>117.169876</td>\n",
       "      <td>34.334335</td>\n",
       "      <td>-36619.618067</td>\n",
       "      <td>3.814658e+06</td>\n",
       "      <td>POINT (-36619.61806662788 3814658.0036518783)</td>\n",
       "      <td>5</td>\n",
       "      <td>5513.896478</td>\n",
       "      <td>诚坤钢材市场(北)</td>\n",
       "      <td>诚坤钢材市场(北)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151458</th>\n",
       "      <td>ww57638</td>\n",
       "      <td>117.169876</td>\n",
       "      <td>34.330215</td>\n",
       "      <td>-36645.976475</td>\n",
       "      <td>3.814200e+06</td>\n",
       "      <td>POINT (-36645.97647538001 3814200.309984983)</td>\n",
       "      <td>5</td>\n",
       "      <td>5060.386574</td>\n",
       "      <td>诚坤钢材市场(北)</td>\n",
       "      <td>诚坤钢材市场(北)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151459</th>\n",
       "      <td>ww57397</td>\n",
       "      <td>117.141037</td>\n",
       "      <td>34.328842</td>\n",
       "      <td>-39312.732220</td>\n",
       "      <td>3.814201e+06</td>\n",
       "      <td>POINT (-39312.7322198333 3814201.185110974)</td>\n",
       "      <td>2</td>\n",
       "      <td>5241.297882</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>151460 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            区编号          经度         纬度          lons          lats  \\\n",
       "0       ww56mus  117.329178  34.170914 -22953.956952  3.795671e+06   \n",
       "1       ww56gwd  117.227554  34.269791 -31712.680638  3.807183e+06   \n",
       "2       ww56s9g  117.272873  34.199753 -27972.154486  3.799166e+06   \n",
       "3       ww56g5p  117.212448  34.250565 -33227.754585  3.805127e+06   \n",
       "4       ww56gqz  117.223434  34.271164 -32083.954936  3.807357e+06   \n",
       "...         ...         ...        ...           ...           ...   \n",
       "151455  ww57367  117.130051  34.334335 -40289.916609  3.814870e+06   \n",
       "151456  ww5739q  117.145157  34.328842 -38933.016510  3.814179e+06   \n",
       "151457  ww57662  117.169876  34.334335 -36619.618067  3.814658e+06   \n",
       "151458  ww57638  117.169876  34.330215 -36645.976475  3.814200e+06   \n",
       "151459  ww57397  117.141037  34.328842 -39312.732220  3.814201e+06   \n",
       "\n",
       "                                             geometry  最近站名索引         最近站距离  \\\n",
       "0       POINT (-22953.956951656553 3795670.852514178)      13  14981.731225   \n",
       "1       POINT (-31712.680638363352 3807183.140981803)       8   2206.424021   \n",
       "2        POINT (-27972.15448565688 3799165.896358251)      11  10154.297459   \n",
       "3       POINT (-33227.75458505633 3805126.7115265634)       8   3902.268698   \n",
       "4       POINT (-32083.954935508664 3807357.337184346)       8   1867.478091   \n",
       "...                                               ...     ...           ...   \n",
       "151455   POINT (-40289.91660904547 3814870.112977421)       2   5972.077777   \n",
       "151456  POINT (-38933.01651049976 3814179.2181995884)       2   5241.230719   \n",
       "151457  POINT (-36619.61806662788 3814658.0036518783)       5   5513.896478   \n",
       "151458   POINT (-36645.97647538001 3814200.309984983)       5   5060.386574   \n",
       "151459    POINT (-39312.7322198333 3814201.185110974)       2   5241.297882   \n",
       "\n",
       "             最近站名      最近站编号  \n",
       "0             宝莲寺        宝莲寺  \n",
       "1        徐州植物园(南)   徐州植物园(南)  \n",
       "2          开发区中学2     开发区中学2  \n",
       "3        徐州植物园(南)   徐州植物园(南)  \n",
       "4        徐州植物园(南)   徐州植物园(南)  \n",
       "...           ...        ...  \n",
       "151455    二九宿舍(南)    二九宿舍(南)  \n",
       "151456    二九宿舍(南)    二九宿舍(南)  \n",
       "151457  诚坤钢材市场(北)  诚坤钢材市场(北)  \n",
       "151458  诚坤钢材市场(北)  诚坤钢材市场(北)  \n",
       "151459    二九宿舍(南)    二九宿舍(南)  \n",
       "\n",
       "[151460 rows x 10 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#QSY=QSY.drop(QSY['最近站距离']>300)\n",
    "QSY.drop(index=QSY[QSY['最近站距离']>300].index[0])\n",
    "QSY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "id": "ef359a90",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1750x1000 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#绘制栅格到最近的站点的距离密度分布\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.sans-serif']=['SimHei']\n",
    "plt.rcParams['font.serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus']=False\n",
    "import seaborn as sns\n",
    "fig     = plt.figure(1,(7,4),dpi = 250)   \n",
    "ax1      = plt.subplot(111)\n",
    "sns.kdeplot(QSY[QSY['最近站距离']<1000]['最近站距离'])\n",
    "plt.xticks(range(0,2000,500),range(0,2000,500))##实际范围和标志，最后是步长\n",
    "plt.show()\n",
    "###沿线一公里内的栅格，距离最近的站点的距离大部分在在1500米以内"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "id": "9c00f2df",
   "metadata": {},
   "outputs": [],
   "source": [
    "d_time = datetime.datetime.strptime('6:30:00', '%H:%M:%S')##!!!!\n",
    "d_time1 = datetime.datetime.strptime('18:30:00', '%H:%M:%S')###!!!!注意区分白天和晚班车"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "id": "35b8dbd1",
   "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>日期</th>\n",
       "      <th>出发时间</th>\n",
       "      <th>O编号</th>\n",
       "      <th>出发人数</th>\n",
       "      <th>D编号</th>\n",
       "      <th>到达人数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20211008</td>\n",
       "      <td>12:00-12:30</td>\n",
       "      <td>ww56ftw</td>\n",
       "      <td>237</td>\n",
       "      <td>ww57jb2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20211008</td>\n",
       "      <td>22:00-22:30</td>\n",
       "      <td>ww56c0b</td>\n",
       "      <td>12</td>\n",
       "      <td>ww56ft5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20211008</td>\n",
       "      <td>06:00-06:30</td>\n",
       "      <td>ww56fps</td>\n",
       "      <td>13</td>\n",
       "      <td>ww56fwe</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20211008</td>\n",
       "      <td>07:00-07:30</td>\n",
       "      <td>ww5e54k</td>\n",
       "      <td>81</td>\n",
       "      <td>ww5e51z</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20211008</td>\n",
       "      <td>06:30-07:00</td>\n",
       "      <td>ww56by2</td>\n",
       "      <td>191</td>\n",
       "      <td>ww56cv0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3254767</th>\n",
       "      <td>20211008</td>\n",
       "      <td>21:30-22:00</td>\n",
       "      <td>ww56d8q</td>\n",
       "      <td>17</td>\n",
       "      <td>ww56ggw</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3254768</th>\n",
       "      <td>20211008</td>\n",
       "      <td>14:30-15:00</td>\n",
       "      <td>ww56t46</td>\n",
       "      <td>26</td>\n",
       "      <td>ww56u78</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3254769</th>\n",
       "      <td>20211008</td>\n",
       "      <td>15:30-16:00</td>\n",
       "      <td>ww5eh0e</td>\n",
       "      <td>13</td>\n",
       "      <td>ww5e5cb</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3254770</th>\n",
       "      <td>20211008</td>\n",
       "      <td>18:30-19:00</td>\n",
       "      <td>ww56df5</td>\n",
       "      <td>106</td>\n",
       "      <td>ww563xs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3254771</th>\n",
       "      <td>20211008</td>\n",
       "      <td>06:00-06:30</td>\n",
       "      <td>ww56fv4</td>\n",
       "      <td>16</td>\n",
       "      <td>ww56cg8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3254772 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               日期         出发时间      O编号  出发人数      D编号  到达人数\n",
       "0        20211008  12:00-12:30  ww56ftw   237  ww57jb2     1\n",
       "1        20211008  22:00-22:30  ww56c0b    12  ww56ft5     1\n",
       "2        20211008  06:00-06:30  ww56fps    13  ww56fwe     1\n",
       "3        20211008  07:00-07:30  ww5e54k    81  ww5e51z     6\n",
       "4        20211008  06:30-07:00  ww56by2   191  ww56cv0     3\n",
       "...           ...          ...      ...   ...      ...   ...\n",
       "3254767  20211008  21:30-22:00  ww56d8q    17  ww56ggw     1\n",
       "3254768  20211008  14:30-15:00  ww56t46    26  ww56u78     2\n",
       "3254769  20211008  15:30-16:00  ww5eh0e    13  ww5e5cb     1\n",
       "3254770  20211008  18:30-19:00  ww56df5   106  ww563xs     1\n",
       "3254771  20211008  06:00-06:30  ww56fv4    16  ww56cg8     1\n",
       "\n",
       "[3254772 rows x 6 columns]"
      ]
     },
     "execution_count": 223,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arrive2 = pd.read_csv(r'F:\\徐州\\xuzhou_res\\xuzhou_res\\setOutRes\\20211008.csv',encoding='utf-8')\n",
    "arrive2.columns=['日期','出发时间','O编号','出发人数','D编号','到达人数']\n",
    "arrive2 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "id": "4d592c8e",
   "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>日期</th>\n",
       "      <th>出发时间</th>\n",
       "      <th>O编号</th>\n",
       "      <th>出发人数</th>\n",
       "      <th>D编号</th>\n",
       "      <th>到达人数</th>\n",
       "      <th>出发起始时间</th>\n",
       "      <th>出发结束时间</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20211008</td>\n",
       "      <td>12:00-12:30</td>\n",
       "      <td>ww56ftw</td>\n",
       "      <td>237</td>\n",
       "      <td>ww57jb2</td>\n",
       "      <td>1</td>\n",
       "      <td>12:00</td>\n",
       "      <td>12:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20211008</td>\n",
       "      <td>22:00-22:30</td>\n",
       "      <td>ww56c0b</td>\n",
       "      <td>12</td>\n",
       "      <td>ww56ft5</td>\n",
       "      <td>1</td>\n",
       "      <td>22:00</td>\n",
       "      <td>22:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20211008</td>\n",
       "      <td>06:00-06:30</td>\n",
       "      <td>ww56fps</td>\n",
       "      <td>13</td>\n",
       "      <td>ww56fwe</td>\n",
       "      <td>1</td>\n",
       "      <td>06:00</td>\n",
       "      <td>06:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20211008</td>\n",
       "      <td>07:00-07:30</td>\n",
       "      <td>ww5e54k</td>\n",
       "      <td>81</td>\n",
       "      <td>ww5e51z</td>\n",
       "      <td>6</td>\n",
       "      <td>07:00</td>\n",
       "      <td>07:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20211008</td>\n",
       "      <td>06:30-07:00</td>\n",
       "      <td>ww56by2</td>\n",
       "      <td>191</td>\n",
       "      <td>ww56cv0</td>\n",
       "      <td>3</td>\n",
       "      <td>06:30</td>\n",
       "      <td>07:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3254767</th>\n",
       "      <td>20211008</td>\n",
       "      <td>21:30-22:00</td>\n",
       "      <td>ww56d8q</td>\n",
       "      <td>17</td>\n",
       "      <td>ww56ggw</td>\n",
       "      <td>1</td>\n",
       "      <td>21:30</td>\n",
       "      <td>22:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3254768</th>\n",
       "      <td>20211008</td>\n",
       "      <td>14:30-15:00</td>\n",
       "      <td>ww56t46</td>\n",
       "      <td>26</td>\n",
       "      <td>ww56u78</td>\n",
       "      <td>2</td>\n",
       "      <td>14:30</td>\n",
       "      <td>15:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3254769</th>\n",
       "      <td>20211008</td>\n",
       "      <td>15:30-16:00</td>\n",
       "      <td>ww5eh0e</td>\n",
       "      <td>13</td>\n",
       "      <td>ww5e5cb</td>\n",
       "      <td>1</td>\n",
       "      <td>15:30</td>\n",
       "      <td>16:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3254770</th>\n",
       "      <td>20211008</td>\n",
       "      <td>18:30-19:00</td>\n",
       "      <td>ww56df5</td>\n",
       "      <td>106</td>\n",
       "      <td>ww563xs</td>\n",
       "      <td>1</td>\n",
       "      <td>18:30</td>\n",
       "      <td>19:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3254771</th>\n",
       "      <td>20211008</td>\n",
       "      <td>06:00-06:30</td>\n",
       "      <td>ww56fv4</td>\n",
       "      <td>16</td>\n",
       "      <td>ww56cg8</td>\n",
       "      <td>1</td>\n",
       "      <td>06:00</td>\n",
       "      <td>06:30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3254772 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               日期         出发时间      O编号  出发人数      D编号  到达人数 出发起始时间 出发结束时间\n",
       "0        20211008  12:00-12:30  ww56ftw   237  ww57jb2     1  12:00  12:30\n",
       "1        20211008  22:00-22:30  ww56c0b    12  ww56ft5     1  22:00  22:30\n",
       "2        20211008  06:00-06:30  ww56fps    13  ww56fwe     1  06:00  06:30\n",
       "3        20211008  07:00-07:30  ww5e54k    81  ww5e51z     6  07:00  07:30\n",
       "4        20211008  06:30-07:00  ww56by2   191  ww56cv0     3  06:30  07:00\n",
       "...           ...          ...      ...   ...      ...   ...    ...    ...\n",
       "3254767  20211008  21:30-22:00  ww56d8q    17  ww56ggw     1  21:30  22:00\n",
       "3254768  20211008  14:30-15:00  ww56t46    26  ww56u78     2  14:30  15:00\n",
       "3254769  20211008  15:30-16:00  ww5eh0e    13  ww5e5cb     1  15:30  16:00\n",
       "3254770  20211008  18:30-19:00  ww56df5   106  ww563xs     1  18:30  19:00\n",
       "3254771  20211008  06:00-06:30  ww56fv4    16  ww56cg8     1  06:00  06:30\n",
       "\n",
       "[3254772 rows x 8 columns]"
      ]
     },
     "execution_count": 224,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "###切分时间字段\n",
    "###筛选出这段时间内到达的栅格人群，线路\n",
    "o=arrive2['出发时间'].str.split('-',expand=True)\n",
    "o['起始时间']=o.loc[:,[0]]\n",
    "o['结束时间']=o.loc[:,[1]]\n",
    "arrive2['出发起始时间']=o['起始时间']\n",
    "arrive2['出发结束时间']=o['结束时间']\n",
    "arrive2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "id": "47718713",
   "metadata": {},
   "outputs": [],
   "source": [
    "#根据时间筛选栅格数据\n",
    "import datetime\n",
    "list=[] \n",
    "n=len(arrive2)###!!!!!这个参数记得改\\n\",\n",
    "for i in range(0, n):    \n",
    "    # 当前时间\\n\",\n",
    "    s_time = datetime.datetime.strptime(arrive2.loc[i,'出发起始时间'], '%H:%M')\n",
    "    e_time = datetime.datetime.strptime(arrive2.loc[i,'出发结束时间'], '%H:%M')\n",
    "    # 当前时间\\n\",\n",
    "    #n_time = datetime.datetime.now()\\n\",\"    #判断时间\\n\",\"    #n_time =BUS_GPS.loc[1,'RECDATETIME']\\n\",\n",
    "    # 判断当前时间是否在范围时间内\\n\",\n",
    "    if s_time > d_time and e_time<d_time1:\n",
    "        k=i\n",
    "        list.append(k)##要用圆括号,且不要写成list=list.append(k)的赋值形式\\n\",\n",
    "        #读取经纬度\n",
    "        pass\n",
    "DSY=arrive2.loc[list,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "id": "8ae1e710",
   "metadata": {
    "scrolled": true
   },
   "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>日期</th>\n",
       "      <th>出发时间</th>\n",
       "      <th>O编号</th>\n",
       "      <th>出发人数</th>\n",
       "      <th>D编号</th>\n",
       "      <th>到达人数</th>\n",
       "      <th>出发起始时间</th>\n",
       "      <th>出发结束时间</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20211008</td>\n",
       "      <td>12:00-12:30</td>\n",
       "      <td>ww56ftw</td>\n",
       "      <td>237</td>\n",
       "      <td>ww57jb2</td>\n",
       "      <td>1</td>\n",
       "      <td>12:00</td>\n",
       "      <td>12:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20211008</td>\n",
       "      <td>07:00-07:30</td>\n",
       "      <td>ww5e54k</td>\n",
       "      <td>81</td>\n",
       "      <td>ww5e51z</td>\n",
       "      <td>6</td>\n",
       "      <td>07:00</td>\n",
       "      <td>07:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>20211008</td>\n",
       "      <td>11:00-11:30</td>\n",
       "      <td>ww5754y</td>\n",
       "      <td>96</td>\n",
       "      <td>ww57557</td>\n",
       "      <td>1</td>\n",
       "      <td>11:00</td>\n",
       "      <td>11:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>20211008</td>\n",
       "      <td>14:00-14:30</td>\n",
       "      <td>ww56ujt</td>\n",
       "      <td>173</td>\n",
       "      <td>ww56gsr</td>\n",
       "      <td>1</td>\n",
       "      <td>14:00</td>\n",
       "      <td>14:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>20211008</td>\n",
       "      <td>13:00-13:30</td>\n",
       "      <td>ww571z9</td>\n",
       "      <td>51</td>\n",
       "      <td>ww574h4</td>\n",
       "      <td>1</td>\n",
       "      <td>13:00</td>\n",
       "      <td>13:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3254759</th>\n",
       "      <td>20211008</td>\n",
       "      <td>10:00-10:30</td>\n",
       "      <td>ww57734</td>\n",
       "      <td>86</td>\n",
       "      <td>ww574g8</td>\n",
       "      <td>3</td>\n",
       "      <td>10:00</td>\n",
       "      <td>10:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3254763</th>\n",
       "      <td>20211008</td>\n",
       "      <td>10:30-11:00</td>\n",
       "      <td>ww574cp</td>\n",
       "      <td>104</td>\n",
       "      <td>ww57578</td>\n",
       "      <td>1</td>\n",
       "      <td>10:30</td>\n",
       "      <td>11:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3254766</th>\n",
       "      <td>20211008</td>\n",
       "      <td>15:30-16:00</td>\n",
       "      <td>ww567m9</td>\n",
       "      <td>63</td>\n",
       "      <td>ww567m9</td>\n",
       "      <td>15</td>\n",
       "      <td>15:30</td>\n",
       "      <td>16:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3254768</th>\n",
       "      <td>20211008</td>\n",
       "      <td>14:30-15:00</td>\n",
       "      <td>ww56t46</td>\n",
       "      <td>26</td>\n",
       "      <td>ww56u78</td>\n",
       "      <td>2</td>\n",
       "      <td>14:30</td>\n",
       "      <td>15:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3254769</th>\n",
       "      <td>20211008</td>\n",
       "      <td>15:30-16:00</td>\n",
       "      <td>ww5eh0e</td>\n",
       "      <td>13</td>\n",
       "      <td>ww5e5cb</td>\n",
       "      <td>1</td>\n",
       "      <td>15:30</td>\n",
       "      <td>16:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2271628 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               日期         出发时间      O编号  出发人数      D编号  到达人数 出发起始时间 出发结束时间\n",
       "0        20211008  12:00-12:30  ww56ftw   237  ww57jb2     1  12:00  12:30\n",
       "3        20211008  07:00-07:30  ww5e54k    81  ww5e51z     6  07:00  07:30\n",
       "5        20211008  11:00-11:30  ww5754y    96  ww57557     1  11:00  11:30\n",
       "8        20211008  14:00-14:30  ww56ujt   173  ww56gsr     1  14:00  14:30\n",
       "9        20211008  13:00-13:30  ww571z9    51  ww574h4     1  13:00  13:30\n",
       "...           ...          ...      ...   ...      ...   ...    ...    ...\n",
       "3254759  20211008  10:00-10:30  ww57734    86  ww574g8     3  10:00  10:30\n",
       "3254763  20211008  10:30-11:00  ww574cp   104  ww57578     1  10:30  11:00\n",
       "3254766  20211008  15:30-16:00  ww567m9    63  ww567m9    15  15:30  16:00\n",
       "3254768  20211008  14:30-15:00  ww56t46    26  ww56u78     2  14:30  15:00\n",
       "3254769  20211008  15:30-16:00  ww5eh0e    13  ww5e5cb     1  15:30  16:00\n",
       "\n",
       "[2271628 rows x 8 columns]"
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DSY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "id": "4dc3b60a",
   "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>区编号</th>\n",
       "      <th>经度</th>\n",
       "      <th>纬度</th>\n",
       "      <th>lons</th>\n",
       "      <th>lats</th>\n",
       "      <th>geometry</th>\n",
       "      <th>project</th>\n",
       "      <th>geometry_orgin</th>\n",
       "      <th>diff</th>\n",
       "      <th>最近站名索引</th>\n",
       "      <th>最近站距离</th>\n",
       "      <th>最近站名</th>\n",
       "      <th>最近站编号</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ww5713p</td>\n",
       "      <td>117.135544</td>\n",
       "      <td>34.283524</td>\n",
       "      <td>-40110.494903</td>\n",
       "      <td>3.809196e+06</td>\n",
       "      <td>POINT (-39965.107295379945 3809024.1875716033)</td>\n",
       "      <td>1046.006179</td>\n",
       "      <td>POINT (-40110.494903228944 3809195.7641564626)</td>\n",
       "      <td>224.891265</td>\n",
       "      <td>0</td>\n",
       "      <td>300.929190</td>\n",
       "      <td>建材中专(南)</td>\n",
       "      <td>建材中专(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ww56cxc</td>\n",
       "      <td>117.138290</td>\n",
       "      <td>34.276657</td>\n",
       "      <td>-39901.324405</td>\n",
       "      <td>3.808418e+06</td>\n",
       "      <td>POINT (-40067.91193592001 3808497.6339962855)</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>POINT (-39901.32440537622 3808418.2749732556)</td>\n",
       "      <td>184.524415</td>\n",
       "      <td>1</td>\n",
       "      <td>235.276099</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ww56crt</td>\n",
       "      <td>117.132797</td>\n",
       "      <td>34.275284</td>\n",
       "      <td>-40416.762168</td>\n",
       "      <td>3.808295e+06</td>\n",
       "      <td>POINT (-40372.336605769815 3808471.371154026)</td>\n",
       "      <td>305.555423</td>\n",
       "      <td>POINT (-40416.76216800348 3808295.0137090506)</td>\n",
       "      <td>181.866927</td>\n",
       "      <td>1</td>\n",
       "      <td>352.845683</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ww57125</td>\n",
       "      <td>117.130051</td>\n",
       "      <td>34.278030</td>\n",
       "      <td>-40652.393259</td>\n",
       "      <td>3.808615e+06</td>\n",
       "      <td>POINT (-40357.333195892315 3808569.870717806)</td>\n",
       "      <td>405.191091</td>\n",
       "      <td>POINT (-40652.39325876965 3808614.8141357456)</td>\n",
       "      <td>298.463317</td>\n",
       "      <td>1</td>\n",
       "      <td>541.817151</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ww56cx8</td>\n",
       "      <td>117.136917</td>\n",
       "      <td>34.275284</td>\n",
       "      <td>-40036.799817</td>\n",
       "      <td>3.808273e+06</td>\n",
       "      <td>POINT (-40067.91193592001 3808497.6339962855)</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>POINT (-40036.7998166366 3808273.031525016)</td>\n",
       "      <td>226.747071</td>\n",
       "      <td>1</td>\n",
       "      <td>236.554284</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>ww57190</td>\n",
       "      <td>117.136917</td>\n",
       "      <td>34.283524</td>\n",
       "      <td>-39983.853437</td>\n",
       "      <td>3.809188e+06</td>\n",
       "      <td>POINT (-39913.373638120574 3809059.857881236)</td>\n",
       "      <td>1109.165559</td>\n",
       "      <td>POINT (-39983.853436529054 3809188.437675828)</td>\n",
       "      <td>146.629348</td>\n",
       "      <td>0</td>\n",
       "      <td>323.339411</td>\n",
       "      <td>建材中专(南)</td>\n",
       "      <td>建材中专(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>ww5719n</td>\n",
       "      <td>117.145157</td>\n",
       "      <td>34.283524</td>\n",
       "      <td>-39224.007018</td>\n",
       "      <td>3.809145e+06</td>\n",
       "      <td>POINT (-39289.056116667874 3808921.571691153)</td>\n",
       "      <td>1772.387042</td>\n",
       "      <td>POINT (-39224.00701761572 3809144.5152177247)</td>\n",
       "      <td>232.239534</td>\n",
       "      <td>2</td>\n",
       "      <td>271.715602</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>ww5718s</td>\n",
       "      <td>117.142410</td>\n",
       "      <td>34.280777</td>\n",
       "      <td>-39494.922000</td>\n",
       "      <td>3.808854e+06</td>\n",
       "      <td>POINT (-39435.61760311102 3808966.9393417495)</td>\n",
       "      <td>1618.734326</td>\n",
       "      <td>POINT (-39494.921999888844 3808854.0151853287)</td>\n",
       "      <td>127.549506</td>\n",
       "      <td>2</td>\n",
       "      <td>128.170935</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>ww5718w</td>\n",
       "      <td>117.145157</td>\n",
       "      <td>34.280777</td>\n",
       "      <td>-39241.631956</td>\n",
       "      <td>3.808839e+06</td>\n",
       "      <td>POINT (-39231.773645709814 3808905.162539506)</td>\n",
       "      <td>1831.992521</td>\n",
       "      <td>POINT (-39241.63195552677 3808839.3818501807)</td>\n",
       "      <td>66.515302</td>\n",
       "      <td>2</td>\n",
       "      <td>219.624669</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>ww5712r</td>\n",
       "      <td>117.135544</td>\n",
       "      <td>34.279404</td>\n",
       "      <td>-40136.975726</td>\n",
       "      <td>3.808738e+06</td>\n",
       "      <td>POINT (-40212.70080255813 3808840.8497851477)</td>\n",
       "      <td>737.141307</td>\n",
       "      <td>POINT (-40136.9757257147 3808738.061234022)</td>\n",
       "      <td>127.670566</td>\n",
       "      <td>0</td>\n",
       "      <td>157.870768</td>\n",
       "      <td>建材中专(南)</td>\n",
       "      <td>建材中专(南)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>66 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        区编号          经度         纬度          lons          lats  \\\n",
       "0   ww5713p  117.135544  34.283524 -40110.494903  3.809196e+06   \n",
       "1   ww56cxc  117.138290  34.276657 -39901.324405  3.808418e+06   \n",
       "2   ww56crt  117.132797  34.275284 -40416.762168  3.808295e+06   \n",
       "3   ww57125  117.130051  34.278030 -40652.393259  3.808615e+06   \n",
       "4   ww56cx8  117.136917  34.275284 -40036.799817  3.808273e+06   \n",
       "..      ...         ...        ...           ...           ...   \n",
       "61  ww57190  117.136917  34.283524 -39983.853437  3.809188e+06   \n",
       "62  ww5719n  117.145157  34.283524 -39224.007018  3.809145e+06   \n",
       "63  ww5718s  117.142410  34.280777 -39494.922000  3.808854e+06   \n",
       "64  ww5718w  117.145157  34.280777 -39241.631956  3.808839e+06   \n",
       "65  ww5712r  117.135544  34.279404 -40136.975726  3.808738e+06   \n",
       "\n",
       "                                          geometry      project  \\\n",
       "0   POINT (-39965.107295379945 3809024.1875716033)  1046.006179   \n",
       "1    POINT (-40067.91193592001 3808497.6339962855)     0.000000   \n",
       "2    POINT (-40372.336605769815 3808471.371154026)   305.555423   \n",
       "3    POINT (-40357.333195892315 3808569.870717806)   405.191091   \n",
       "4    POINT (-40067.91193592001 3808497.6339962855)     0.000000   \n",
       "..                                             ...          ...   \n",
       "61   POINT (-39913.373638120574 3809059.857881236)  1109.165559   \n",
       "62   POINT (-39289.056116667874 3808921.571691153)  1772.387042   \n",
       "63   POINT (-39435.61760311102 3808966.9393417495)  1618.734326   \n",
       "64   POINT (-39231.773645709814 3808905.162539506)  1831.992521   \n",
       "65   POINT (-40212.70080255813 3808840.8497851477)   737.141307   \n",
       "\n",
       "                                    geometry_orgin        diff  最近站名索引  \\\n",
       "0   POINT (-40110.494903228944 3809195.7641564626)  224.891265       0   \n",
       "1    POINT (-39901.32440537622 3808418.2749732556)  184.524415       1   \n",
       "2    POINT (-40416.76216800348 3808295.0137090506)  181.866927       1   \n",
       "3    POINT (-40652.39325876965 3808614.8141357456)  298.463317       1   \n",
       "4      POINT (-40036.7998166366 3808273.031525016)  226.747071       1   \n",
       "..                                             ...         ...     ...   \n",
       "61   POINT (-39983.853436529054 3809188.437675828)  146.629348       0   \n",
       "62   POINT (-39224.00701761572 3809144.5152177247)  232.239534       2   \n",
       "63  POINT (-39494.921999888844 3808854.0151853287)  127.549506       2   \n",
       "64   POINT (-39241.63195552677 3808839.3818501807)   66.515302       2   \n",
       "65     POINT (-40136.9757257147 3808738.061234022)  127.670566       0   \n",
       "\n",
       "         最近站距离      最近站名     最近站编号  \n",
       "0   300.929190   建材中专(南)   建材中专(南)  \n",
       "1   235.276099  九龙湖公园(南)  九龙湖公园(南)  \n",
       "2   352.845683  九龙湖公园(南)  九龙湖公园(南)  \n",
       "3   541.817151  九龙湖公园(南)  九龙湖公园(南)  \n",
       "4   236.554284  九龙湖公园(南)  九龙湖公园(南)  \n",
       "..         ...       ...       ...  \n",
       "61  323.339411   建材中专(南)   建材中专(南)  \n",
       "62  271.715602   二九宿舍(南)   二九宿舍(南)  \n",
       "63  128.170935   二九宿舍(南)   二九宿舍(南)  \n",
       "64  219.624669   二九宿舍(南)   二九宿舍(南)  \n",
       "65  157.870768   建材中专(南)   建材中专(南)  \n",
       "\n",
       "[66 rows x 13 columns]"
      ]
     },
     "execution_count": 227,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lineQSY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "id": "a7a92587",
   "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>日期</th>\n",
       "      <th>出发时间</th>\n",
       "      <th>O编号</th>\n",
       "      <th>出发人数</th>\n",
       "      <th>D编号</th>\n",
       "      <th>到达人数</th>\n",
       "      <th>出发起始时间</th>\n",
       "      <th>出发结束时间</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20211008</td>\n",
       "      <td>08:00-08:30</td>\n",
       "      <td>ww56cgy</td>\n",
       "      <td>246</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>1</td>\n",
       "      <td>08:00</td>\n",
       "      <td>08:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20211008</td>\n",
       "      <td>10:00-10:30</td>\n",
       "      <td>ww56bt7</td>\n",
       "      <td>131</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>1</td>\n",
       "      <td>10:00</td>\n",
       "      <td>10:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20211008</td>\n",
       "      <td>07:30-08:00</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>32</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>7</td>\n",
       "      <td>07:30</td>\n",
       "      <td>08:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20211008</td>\n",
       "      <td>08:30-09:00</td>\n",
       "      <td>ww570t8</td>\n",
       "      <td>25</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>1</td>\n",
       "      <td>08:30</td>\n",
       "      <td>09:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20211008</td>\n",
       "      <td>09:00-09:30</td>\n",
       "      <td>ww5731k</td>\n",
       "      <td>94</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>1</td>\n",
       "      <td>09:00</td>\n",
       "      <td>09:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2185</th>\n",
       "      <td>20211008</td>\n",
       "      <td>07:00-07:30</td>\n",
       "      <td>ww571xt</td>\n",
       "      <td>158</td>\n",
       "      <td>ww5718z</td>\n",
       "      <td>1</td>\n",
       "      <td>07:00</td>\n",
       "      <td>07:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2186</th>\n",
       "      <td>20211008</td>\n",
       "      <td>13:30-14:00</td>\n",
       "      <td>ww5718z</td>\n",
       "      <td>5</td>\n",
       "      <td>ww5718z</td>\n",
       "      <td>1</td>\n",
       "      <td>13:30</td>\n",
       "      <td>14:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2187</th>\n",
       "      <td>20211008</td>\n",
       "      <td>15:30-16:00</td>\n",
       "      <td>ww56eqm</td>\n",
       "      <td>97</td>\n",
       "      <td>ww5718z</td>\n",
       "      <td>1</td>\n",
       "      <td>15:30</td>\n",
       "      <td>16:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2188</th>\n",
       "      <td>20211008</td>\n",
       "      <td>17:30-18:00</td>\n",
       "      <td>ww5717f</td>\n",
       "      <td>37</td>\n",
       "      <td>ww5718z</td>\n",
       "      <td>1</td>\n",
       "      <td>17:30</td>\n",
       "      <td>18:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2189</th>\n",
       "      <td>20211008</td>\n",
       "      <td>15:30-16:00</td>\n",
       "      <td>ww5k2qq</td>\n",
       "      <td>95</td>\n",
       "      <td>ww5718z</td>\n",
       "      <td>1</td>\n",
       "      <td>15:30</td>\n",
       "      <td>16:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2190 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            日期         出发时间      O编号  出发人数      D编号  到达人数 出发起始时间 出发结束时间\n",
       "0     20211008  08:00-08:30  ww56cgy   246  ww5713p     1  08:00  08:30\n",
       "1     20211008  10:00-10:30  ww56bt7   131  ww5713p     1  10:00  10:30\n",
       "2     20211008  07:30-08:00  ww5713p    32  ww5713p     7  07:30  08:00\n",
       "3     20211008  08:30-09:00  ww570t8    25  ww5713p     1  08:30  09:00\n",
       "4     20211008  09:00-09:30  ww5731k    94  ww5713p     1  09:00  09:30\n",
       "...        ...          ...      ...   ...      ...   ...    ...    ...\n",
       "2185  20211008  07:00-07:30  ww571xt   158  ww5718z     1  07:00  07:30\n",
       "2186  20211008  13:30-14:00  ww5718z     5  ww5718z     1  13:30  14:00\n",
       "2187  20211008  15:30-16:00  ww56eqm    97  ww5718z     1  15:30  16:00\n",
       "2188  20211008  17:30-18:00  ww5717f    37  ww5718z     1  17:30  18:00\n",
       "2189  20211008  15:30-16:00  ww5k2qq    95  ww5718z     1  15:30  16:00\n",
       "\n",
       "[2190 rows x 8 columns]"
      ]
     },
     "execution_count": 228,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.DataFrame()\n",
    "for i in range(0,len(lineQSY)):\n",
    "    sg=DSY.loc[DSY['D编号'].str.contains(lineQSY['区编号'].iloc[i])]  \n",
    "    df1 = df1.append(sg,ignore_index = True)\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "id": "8d30c2ff",
   "metadata": {
    "scrolled": true
   },
   "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>日期</th>\n",
       "      <th>出发时间</th>\n",
       "      <th>O编号</th>\n",
       "      <th>出发人数</th>\n",
       "      <th>D编号</th>\n",
       "      <th>到达人数</th>\n",
       "      <th>出发起始时间</th>\n",
       "      <th>出发结束时间</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20211008</td>\n",
       "      <td>07:30-08:00</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>32</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>7</td>\n",
       "      <td>07:30</td>\n",
       "      <td>08:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20211008</td>\n",
       "      <td>08:00-08:30</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>31</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>4</td>\n",
       "      <td>08:00</td>\n",
       "      <td>08:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20211008</td>\n",
       "      <td>10:30-11:00</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>12</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>2</td>\n",
       "      <td>10:30</td>\n",
       "      <td>11:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20211008</td>\n",
       "      <td>11:30-12:00</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>17</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>4</td>\n",
       "      <td>11:30</td>\n",
       "      <td>12:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20211008</td>\n",
       "      <td>07:00-07:30</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>21</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>3</td>\n",
       "      <td>07:00</td>\n",
       "      <td>07:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>20211008</td>\n",
       "      <td>10:30-11:00</td>\n",
       "      <td>ww5718z</td>\n",
       "      <td>3</td>\n",
       "      <td>ww5718q</td>\n",
       "      <td>1</td>\n",
       "      <td>10:30</td>\n",
       "      <td>11:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>20211008</td>\n",
       "      <td>11:30-12:00</td>\n",
       "      <td>ww5718z</td>\n",
       "      <td>5</td>\n",
       "      <td>ww5718z</td>\n",
       "      <td>1</td>\n",
       "      <td>11:30</td>\n",
       "      <td>12:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>20211008</td>\n",
       "      <td>14:00-14:30</td>\n",
       "      <td>ww5718z</td>\n",
       "      <td>2</td>\n",
       "      <td>ww5718z</td>\n",
       "      <td>1</td>\n",
       "      <td>14:00</td>\n",
       "      <td>14:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>20211008</td>\n",
       "      <td>09:00-09:30</td>\n",
       "      <td>ww5718z</td>\n",
       "      <td>2</td>\n",
       "      <td>ww5718z</td>\n",
       "      <td>2</td>\n",
       "      <td>09:00</td>\n",
       "      <td>09:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>20211008</td>\n",
       "      <td>13:30-14:00</td>\n",
       "      <td>ww5718z</td>\n",
       "      <td>5</td>\n",
       "      <td>ww5718z</td>\n",
       "      <td>1</td>\n",
       "      <td>13:30</td>\n",
       "      <td>14:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>141 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           日期         出发时间      O编号  出发人数      D编号  到达人数 出发起始时间 出发结束时间\n",
       "0    20211008  07:30-08:00  ww5713p    32  ww5713p     7  07:30  08:00\n",
       "1    20211008  08:00-08:30  ww5713p    31  ww5713p     4  08:00  08:30\n",
       "2    20211008  10:30-11:00  ww5713p    12  ww5713p     2  10:30  11:00\n",
       "3    20211008  11:30-12:00  ww5713p    17  ww5713p     4  11:30  12:00\n",
       "4    20211008  07:00-07:30  ww5713p    21  ww5713p     3  07:00  07:30\n",
       "..        ...          ...      ...   ...      ...   ...    ...    ...\n",
       "136  20211008  10:30-11:00  ww5718z     3  ww5718q     1  10:30  11:00\n",
       "137  20211008  11:30-12:00  ww5718z     5  ww5718z     1  11:30  12:00\n",
       "138  20211008  14:00-14:30  ww5718z     2  ww5718z     1  14:00  14:30\n",
       "139  20211008  09:00-09:30  ww5718z     2  ww5718z     2  09:00  09:30\n",
       "140  20211008  13:30-14:00  ww5718z     5  ww5718z     1  13:30  14:00\n",
       "\n",
       "[141 rows x 8 columns]"
      ]
     },
     "execution_count": 229,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3 = pd.DataFrame()\n",
    "for i in range(0,len(lineQSY)):\n",
    "    sg=df1.loc[df1['O编号'].str.contains(lineQSY['区编号'].iloc[i])]  \n",
    "    df3 = df3.append(sg,ignore_index = True)\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "id": "78f6db06",
   "metadata": {
    "scrolled": true
   },
   "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>FID</th>\n",
       "      <th>stopcode</th>\n",
       "      <th>stopname</th>\n",
       "      <th>经度</th>\n",
       "      <th>纬度</th>\n",
       "      <th>lons</th>\n",
       "      <th>lats</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>210121</td>\n",
       "      <td>九里山(北)</td>\n",
       "      <td>117.135633</td>\n",
       "      <td>34.280820</td>\n",
       "      <td>-35371.115984</td>\n",
       "      <td>3.809126e+06</td>\n",
       "      <td>POINT (-35371.11598390527 3809126.27149845)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>XYRJCZ</td>\n",
       "      <td>西苑人家(场站)</td>\n",
       "      <td>117.135832</td>\n",
       "      <td>34.277209</td>\n",
       "      <td>-30868.628715</td>\n",
       "      <td>3.809833e+06</td>\n",
       "      <td>POINT (-30868.62871548999 3809832.7291986453)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td></td>\n",
       "      <td>中海九樾</td>\n",
       "      <td>117.143105</td>\n",
       "      <td>34.281774</td>\n",
       "      <td>-29035.955572</td>\n",
       "      <td>3.809398e+06</td>\n",
       "      <td>POINT (-29035.95557169034 3809398.4323940463)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>ZWYN</td>\n",
       "      <td>徐州植物园(南)</td>\n",
       "      <td>117.154076</td>\n",
       "      <td>34.280838</td>\n",
       "      <td>-32937.790434</td>\n",
       "      <td>3.809018e+06</td>\n",
       "      <td>POINT (-32937.790433969116 3809018.192193212)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>60070</td>\n",
       "      <td>诚坤钢材市场(北)</td>\n",
       "      <td>117.165993</td>\n",
       "      <td>34.283159</td>\n",
       "      <td>-36161.275042</td>\n",
       "      <td>3.809163e+06</td>\n",
       "      <td>POINT (-36161.27504204004 3809163.1900935313)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>6120020</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "      <td>117.178249</td>\n",
       "      <td>34.285274</td>\n",
       "      <td>-40124.510910</td>\n",
       "      <td>3.808493e+06</td>\n",
       "      <td>POINT (-40124.510909937904 3808492.723794836)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>120100</td>\n",
       "      <td>建材中专(南)</td>\n",
       "      <td>117.186812</td>\n",
       "      <td>34.285349</td>\n",
       "      <td>-40119.598338</td>\n",
       "      <td>3.808895e+06</td>\n",
       "      <td>POINT (-40119.59833793016 3808894.9726925436)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>670121</td>\n",
       "      <td>堤北农贸市场|二环路(北)</td>\n",
       "      <td>117.195917</td>\n",
       "      <td>34.285544</td>\n",
       "      <td>-37304.952052</td>\n",
       "      <td>3.808993e+06</td>\n",
       "      <td>POINT (-37304.95205151627 3808993.2155954926)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>670190</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>117.213182</td>\n",
       "      <td>34.285629</td>\n",
       "      <td>-39424.457030</td>\n",
       "      <td>3.808961e+06</td>\n",
       "      <td>POINT (-39424.45702975185 3808961.078141681)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>670220</td>\n",
       "      <td>杨庄(南)</td>\n",
       "      <td>117.226433</td>\n",
       "      <td>34.291450</td>\n",
       "      <td>-38418.762596</td>\n",
       "      <td>3.808799e+06</td>\n",
       "      <td>POINT (-38418.7625962653 3808798.6800883734)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>GLFYX</td>\n",
       "      <td>鼓楼法院(西)</td>\n",
       "      <td>117.235048</td>\n",
       "      <td>34.293996</td>\n",
       "      <td>-31679.098141</td>\n",
       "      <td>3.809595e+06</td>\n",
       "      <td>POINT (-31679.098140898743 3809595.15839898)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>KFQZX2</td>\n",
       "      <td>开发区中学2</td>\n",
       "      <td>117.248011</td>\n",
       "      <td>34.288649</td>\n",
       "      <td>-29707.210525</td>\n",
       "      <td>3.809171e+06</td>\n",
       "      <td>POINT (-29707.210525320144 3809170.8619969385)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>30100</td>\n",
       "      <td>金山桥公交停车场(东)</td>\n",
       "      <td>117.255128</td>\n",
       "      <td>34.291032</td>\n",
       "      <td>-34530.302321</td>\n",
       "      <td>3.809100e+06</td>\n",
       "      <td>POINT (-34530.302320748335 3809099.795096339)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td></td>\n",
       "      <td>宝莲寺</td>\n",
       "      <td>117.262351</td>\n",
       "      <td>34.293597</td>\n",
       "      <td>-28353.836794</td>\n",
       "      <td>3.809646e+06</td>\n",
       "      <td>POINT (-28353.836794012925 3809645.6000315594)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    FID stopcode       stopname          经度         纬度          lons  \\\n",
       "6     6   210121         九里山(北)  117.135633  34.280820 -35371.115984   \n",
       "10   10   XYRJCZ       西苑人家(场站)  117.135832  34.277209 -30868.628715   \n",
       "12   12                    中海九樾  117.143105  34.281774 -29035.955572   \n",
       "8     8     ZWYN       徐州植物园(南)  117.154076  34.280838 -32937.790434   \n",
       "5     5    60070      诚坤钢材市场(北)  117.165993  34.283159 -36161.275042   \n",
       "1     1  6120020       九龙湖公园(南)  117.178249  34.285274 -40124.510910   \n",
       "0     0   120100        建材中专(南)  117.186812  34.285349 -40119.598338   \n",
       "4     4   670121  堤北农贸市场|二环路(北)  117.195917  34.285544 -37304.952052   \n",
       "2     2   670190        二九宿舍(南)  117.213182  34.285629 -39424.457030   \n",
       "3     3   670220          杨庄(南)  117.226433  34.291450 -38418.762596   \n",
       "9     9    GLFYX        鼓楼法院(西)  117.235048  34.293996 -31679.098141   \n",
       "11   11   KFQZX2         开发区中学2  117.248011  34.288649 -29707.210525   \n",
       "7     7    30100    金山桥公交停车场(东)  117.255128  34.291032 -34530.302321   \n",
       "13   13                     宝莲寺  117.262351  34.293597 -28353.836794   \n",
       "\n",
       "            lats                                        geometry  \n",
       "6   3.809126e+06     POINT (-35371.11598390527 3809126.27149845)  \n",
       "10  3.809833e+06   POINT (-30868.62871548999 3809832.7291986453)  \n",
       "12  3.809398e+06   POINT (-29035.95557169034 3809398.4323940463)  \n",
       "8   3.809018e+06   POINT (-32937.790433969116 3809018.192193212)  \n",
       "5   3.809163e+06   POINT (-36161.27504204004 3809163.1900935313)  \n",
       "1   3.808493e+06   POINT (-40124.510909937904 3808492.723794836)  \n",
       "0   3.808895e+06   POINT (-40119.59833793016 3808894.9726925436)  \n",
       "4   3.808993e+06   POINT (-37304.95205151627 3808993.2155954926)  \n",
       "2   3.808961e+06    POINT (-39424.45702975185 3808961.078141681)  \n",
       "3   3.808799e+06    POINT (-38418.7625962653 3808798.6800883734)  \n",
       "9   3.809595e+06    POINT (-31679.098140898743 3809595.15839898)  \n",
       "11  3.809171e+06  POINT (-29707.210525320144 3809170.8619969385)  \n",
       "7   3.809100e+06   POINT (-34530.302320748335 3809099.795096339)  \n",
       "13  3.809646e+06  POINT (-28353.836794012925 3809645.6000315594)  "
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "id": "73e142a8",
   "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>区编号</th>\n",
       "      <th>经度</th>\n",
       "      <th>纬度</th>\n",
       "      <th>lons</th>\n",
       "      <th>lats</th>\n",
       "      <th>geometry</th>\n",
       "      <th>project</th>\n",
       "      <th>geometry_orgin</th>\n",
       "      <th>diff</th>\n",
       "      <th>最近站名索引</th>\n",
       "      <th>最近站距离</th>\n",
       "      <th>最近站名</th>\n",
       "      <th>最近站编号</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ww5713p</td>\n",
       "      <td>117.135544</td>\n",
       "      <td>34.283524</td>\n",
       "      <td>-40110.494903</td>\n",
       "      <td>3.809196e+06</td>\n",
       "      <td>POINT (-39965.107295379945 3809024.1875716033)</td>\n",
       "      <td>1046.006179</td>\n",
       "      <td>POINT (-40110.494903228944 3809195.7641564626)</td>\n",
       "      <td>224.891265</td>\n",
       "      <td>0</td>\n",
       "      <td>300.929190</td>\n",
       "      <td>建材中专(南)</td>\n",
       "      <td>120100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ww56cxc</td>\n",
       "      <td>117.138290</td>\n",
       "      <td>34.276657</td>\n",
       "      <td>-39901.324405</td>\n",
       "      <td>3.808418e+06</td>\n",
       "      <td>POINT (-40067.91193592001 3808497.6339962855)</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>POINT (-39901.32440537622 3808418.2749732556)</td>\n",
       "      <td>184.524415</td>\n",
       "      <td>1</td>\n",
       "      <td>235.276099</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "      <td>6120020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ww56crt</td>\n",
       "      <td>117.132797</td>\n",
       "      <td>34.275284</td>\n",
       "      <td>-40416.762168</td>\n",
       "      <td>3.808295e+06</td>\n",
       "      <td>POINT (-40372.336605769815 3808471.371154026)</td>\n",
       "      <td>305.555423</td>\n",
       "      <td>POINT (-40416.76216800348 3808295.0137090506)</td>\n",
       "      <td>181.866927</td>\n",
       "      <td>1</td>\n",
       "      <td>352.845683</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "      <td>6120020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ww57125</td>\n",
       "      <td>117.130051</td>\n",
       "      <td>34.278030</td>\n",
       "      <td>-40652.393259</td>\n",
       "      <td>3.808615e+06</td>\n",
       "      <td>POINT (-40357.333195892315 3808569.870717806)</td>\n",
       "      <td>405.191091</td>\n",
       "      <td>POINT (-40652.39325876965 3808614.8141357456)</td>\n",
       "      <td>298.463317</td>\n",
       "      <td>1</td>\n",
       "      <td>541.817151</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "      <td>6120020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ww56cx8</td>\n",
       "      <td>117.136917</td>\n",
       "      <td>34.275284</td>\n",
       "      <td>-40036.799817</td>\n",
       "      <td>3.808273e+06</td>\n",
       "      <td>POINT (-40067.91193592001 3808497.6339962855)</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>POINT (-40036.7998166366 3808273.031525016)</td>\n",
       "      <td>226.747071</td>\n",
       "      <td>1</td>\n",
       "      <td>236.554284</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "      <td>6120020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>ww57190</td>\n",
       "      <td>117.136917</td>\n",
       "      <td>34.283524</td>\n",
       "      <td>-39983.853437</td>\n",
       "      <td>3.809188e+06</td>\n",
       "      <td>POINT (-39913.373638120574 3809059.857881236)</td>\n",
       "      <td>1109.165559</td>\n",
       "      <td>POINT (-39983.853436529054 3809188.437675828)</td>\n",
       "      <td>146.629348</td>\n",
       "      <td>0</td>\n",
       "      <td>323.339411</td>\n",
       "      <td>建材中专(南)</td>\n",
       "      <td>120100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>ww5719n</td>\n",
       "      <td>117.145157</td>\n",
       "      <td>34.283524</td>\n",
       "      <td>-39224.007018</td>\n",
       "      <td>3.809145e+06</td>\n",
       "      <td>POINT (-39289.056116667874 3808921.571691153)</td>\n",
       "      <td>1772.387042</td>\n",
       "      <td>POINT (-39224.00701761572 3809144.5152177247)</td>\n",
       "      <td>232.239534</td>\n",
       "      <td>2</td>\n",
       "      <td>271.715602</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>670190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>ww5718s</td>\n",
       "      <td>117.142410</td>\n",
       "      <td>34.280777</td>\n",
       "      <td>-39494.922000</td>\n",
       "      <td>3.808854e+06</td>\n",
       "      <td>POINT (-39435.61760311102 3808966.9393417495)</td>\n",
       "      <td>1618.734326</td>\n",
       "      <td>POINT (-39494.921999888844 3808854.0151853287)</td>\n",
       "      <td>127.549506</td>\n",
       "      <td>2</td>\n",
       "      <td>128.170935</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>670190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>ww5718w</td>\n",
       "      <td>117.145157</td>\n",
       "      <td>34.280777</td>\n",
       "      <td>-39241.631956</td>\n",
       "      <td>3.808839e+06</td>\n",
       "      <td>POINT (-39231.773645709814 3808905.162539506)</td>\n",
       "      <td>1831.992521</td>\n",
       "      <td>POINT (-39241.63195552677 3808839.3818501807)</td>\n",
       "      <td>66.515302</td>\n",
       "      <td>2</td>\n",
       "      <td>219.624669</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>670190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>ww5712r</td>\n",
       "      <td>117.135544</td>\n",
       "      <td>34.279404</td>\n",
       "      <td>-40136.975726</td>\n",
       "      <td>3.808738e+06</td>\n",
       "      <td>POINT (-40212.70080255813 3808840.8497851477)</td>\n",
       "      <td>737.141307</td>\n",
       "      <td>POINT (-40136.9757257147 3808738.061234022)</td>\n",
       "      <td>127.670566</td>\n",
       "      <td>0</td>\n",
       "      <td>157.870768</td>\n",
       "      <td>建材中专(南)</td>\n",
       "      <td>120100</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>66 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        区编号          经度         纬度          lons          lats  \\\n",
       "0   ww5713p  117.135544  34.283524 -40110.494903  3.809196e+06   \n",
       "1   ww56cxc  117.138290  34.276657 -39901.324405  3.808418e+06   \n",
       "2   ww56crt  117.132797  34.275284 -40416.762168  3.808295e+06   \n",
       "3   ww57125  117.130051  34.278030 -40652.393259  3.808615e+06   \n",
       "4   ww56cx8  117.136917  34.275284 -40036.799817  3.808273e+06   \n",
       "..      ...         ...        ...           ...           ...   \n",
       "61  ww57190  117.136917  34.283524 -39983.853437  3.809188e+06   \n",
       "62  ww5719n  117.145157  34.283524 -39224.007018  3.809145e+06   \n",
       "63  ww5718s  117.142410  34.280777 -39494.922000  3.808854e+06   \n",
       "64  ww5718w  117.145157  34.280777 -39241.631956  3.808839e+06   \n",
       "65  ww5712r  117.135544  34.279404 -40136.975726  3.808738e+06   \n",
       "\n",
       "                                          geometry      project  \\\n",
       "0   POINT (-39965.107295379945 3809024.1875716033)  1046.006179   \n",
       "1    POINT (-40067.91193592001 3808497.6339962855)     0.000000   \n",
       "2    POINT (-40372.336605769815 3808471.371154026)   305.555423   \n",
       "3    POINT (-40357.333195892315 3808569.870717806)   405.191091   \n",
       "4    POINT (-40067.91193592001 3808497.6339962855)     0.000000   \n",
       "..                                             ...          ...   \n",
       "61   POINT (-39913.373638120574 3809059.857881236)  1109.165559   \n",
       "62   POINT (-39289.056116667874 3808921.571691153)  1772.387042   \n",
       "63   POINT (-39435.61760311102 3808966.9393417495)  1618.734326   \n",
       "64   POINT (-39231.773645709814 3808905.162539506)  1831.992521   \n",
       "65   POINT (-40212.70080255813 3808840.8497851477)   737.141307   \n",
       "\n",
       "                                    geometry_orgin        diff  最近站名索引  \\\n",
       "0   POINT (-40110.494903228944 3809195.7641564626)  224.891265       0   \n",
       "1    POINT (-39901.32440537622 3808418.2749732556)  184.524415       1   \n",
       "2    POINT (-40416.76216800348 3808295.0137090506)  181.866927       1   \n",
       "3    POINT (-40652.39325876965 3808614.8141357456)  298.463317       1   \n",
       "4      POINT (-40036.7998166366 3808273.031525016)  226.747071       1   \n",
       "..                                             ...         ...     ...   \n",
       "61   POINT (-39983.853436529054 3809188.437675828)  146.629348       0   \n",
       "62   POINT (-39224.00701761572 3809144.5152177247)  232.239534       2   \n",
       "63  POINT (-39494.921999888844 3808854.0151853287)  127.549506       2   \n",
       "64   POINT (-39241.63195552677 3808839.3818501807)   66.515302       2   \n",
       "65     POINT (-40136.9757257147 3808738.061234022)  127.670566       0   \n",
       "\n",
       "         最近站距离      最近站名    最近站编号  \n",
       "0   300.929190   建材中专(南)   120100  \n",
       "1   235.276099  九龙湖公园(南)  6120020  \n",
       "2   352.845683  九龙湖公园(南)  6120020  \n",
       "3   541.817151  九龙湖公园(南)  6120020  \n",
       "4   236.554284  九龙湖公园(南)  6120020  \n",
       "..         ...       ...      ...  \n",
       "61  323.339411   建材中专(南)   120100  \n",
       "62  271.715602   二九宿舍(南)   670190  \n",
       "63  128.170935   二九宿舍(南)   670190  \n",
       "64  219.624669   二九宿舍(南)   670190  \n",
       "65  157.870768   建材中专(南)   120100  \n",
       "\n",
       "[66 rows x 13 columns]"
      ]
     },
     "execution_count": 231,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import math\n",
    "###将所有小区匹配到最近的站点上\n",
    "#for k in range(0,len(lineQSY)):\n",
    "match=[]\n",
    "nearestd=[]\n",
    "for k in range(0,len(lineQSY)):###range写法要求索引连续完整\n",
    "    distance=[]\n",
    "    for i in range(0,len(stop)):        \n",
    "        x1 = stop.loc[i,'lons']\n",
    "        y1 = stop.loc[i,'lats']\n",
    "        x2 = lineQSY.loc[k,'lons']\n",
    "        y2 = lineQSY.loc[k,'lats']\n",
    "        #print(math.sqrt((x2-x1)**2+(y2-y1)**2))\n",
    "        distance.append(math.sqrt((x2-x1)**2+(y2-y1)**2))\n",
    "    #print(distance)\n",
    "    #print(len(distance))\n",
    "    # 求列表最小值及索引\n",
    "    min_value = min(distance) # 求列表最小值\n",
    "    min_idx = distance.index(min_value) # 求最小值对应索引\n",
    "    #print(min_value)\n",
    "    #print(min_idx )\n",
    "    nearestd.append(min_value)\n",
    "    match.append(min_idx)\n",
    "###最近站点整理\n",
    "lineQSY['最近站名索引']=match\n",
    "lineQSY['最近站距离']=nearestd\n",
    "lineQSY['最近站名']=None\n",
    "lineQSY['最近站编号']=None\n",
    "for k in range(0,len(lineQSY)):\n",
    "    sy=lineQSY['最近站名索引'].loc[k]\n",
    "    lineQSY['最近站名'].loc[k]=stop['stopname'].loc[sy]\n",
    "    lineQSY['最近站编号'].loc[k]=stop['stopcode'].loc[sy]\n",
    "lineQSY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "id": "5ea3595e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "stod\n",
      "           日期         出发时间      O编号  出发人数      D编号  到达人数 出发起始时间 出发结束时间  \\\n",
      "0    20211008  07:30-08:00  ww5713p    32  ww5713p     7  07:30  08:00   \n",
      "1    20211008  08:00-08:30  ww5713p    31  ww5713p     4  08:00  08:30   \n",
      "2    20211008  10:30-11:00  ww5713p    12  ww5713p     2  10:30  11:00   \n",
      "3    20211008  11:30-12:00  ww5713p    17  ww5713p     4  11:30  12:00   \n",
      "4    20211008  07:00-07:30  ww5713p    21  ww5713p     3  07:00  07:30   \n",
      "..        ...          ...      ...   ...      ...   ...    ...    ...   \n",
      "136  20211008  10:30-11:00  ww5718z     3  ww5718q     1  10:30  11:00   \n",
      "137  20211008  11:30-12:00  ww5718z     5  ww5718z     1  11:30  12:00   \n",
      "138  20211008  14:00-14:30  ww5718z     2  ww5718z     1  14:00  14:30   \n",
      "139  20211008  09:00-09:30  ww5718z     2  ww5718z     2  09:00  09:30   \n",
      "140  20211008  13:30-14:00  ww5718z     5  ww5718z     1  13:30  14:00   \n",
      "\n",
      "         出发站      到达站   出发站编号   到达站编号  \n",
      "0    建材中专(南)  建材中专(南)  120100  120100  \n",
      "1    建材中专(南)  建材中专(南)  120100  120100  \n",
      "2    建材中专(南)  建材中专(南)  120100  120100  \n",
      "3    建材中专(南)  建材中专(南)  120100  120100  \n",
      "4    建材中专(南)  建材中专(南)  120100  120100  \n",
      "..       ...      ...     ...     ...  \n",
      "136  二九宿舍(南)  二九宿舍(南)  670190  670190  \n",
      "137  二九宿舍(南)  二九宿舍(南)  670190  670190  \n",
      "138  二九宿舍(南)  二九宿舍(南)  670190  670190  \n",
      "139  二九宿舍(南)  二九宿舍(南)  670190  670190  \n",
      "140  二九宿舍(南)  二九宿舍(南)  670190  670190  \n",
      "\n",
      "[141 rows x 12 columns]\n",
      "           日期         出发时间      O编号  出发人数      D编号  到达人数 出发起始时间 出发结束时间  \\\n",
      "0    20211008  07:30-08:00  ww5713p    32  ww5713p     7  07:30  08:00   \n",
      "1    20211008  08:00-08:30  ww5713p    31  ww5713p     4  08:00  08:30   \n",
      "2    20211008  10:30-11:00  ww5713p    12  ww5713p     2  10:30  11:00   \n",
      "3    20211008  11:30-12:00  ww5713p    17  ww5713p     4  11:30  12:00   \n",
      "4    20211008  07:00-07:30  ww5713p    21  ww5713p     3  07:00  07:30   \n",
      "..        ...          ...      ...   ...      ...   ...    ...    ...   \n",
      "136  20211008  10:30-11:00  ww5718z     3  ww5718q     1  10:30  11:00   \n",
      "137  20211008  11:30-12:00  ww5718z     5  ww5718z     1  11:30  12:00   \n",
      "138  20211008  14:00-14:30  ww5718z     2  ww5718z     1  14:00  14:30   \n",
      "139  20211008  09:00-09:30  ww5718z     2  ww5718z     2  09:00  09:30   \n",
      "140  20211008  13:30-14:00  ww5718z     5  ww5718z     1  13:30  14:00   \n",
      "\n",
      "         出发站      到达站   出发站编号   到达站编号  \n",
      "0    建材中专(南)  建材中专(南)  120100  120100  \n",
      "1    建材中专(南)  建材中专(南)  120100  120100  \n",
      "2    建材中专(南)  建材中专(南)  120100  120100  \n",
      "3    建材中专(南)  建材中专(南)  120100  120100  \n",
      "4    建材中专(南)  建材中专(南)  120100  120100  \n",
      "..       ...      ...     ...     ...  \n",
      "136  二九宿舍(南)  二九宿舍(南)  670190  670190  \n",
      "137  二九宿舍(南)  二九宿舍(南)  670190  670190  \n",
      "138  二九宿舍(南)  二九宿舍(南)  670190  670190  \n",
      "139  二九宿舍(南)  二九宿舍(南)  670190  670190  \n",
      "140  二九宿舍(南)  二九宿舍(南)  670190  670190  \n",
      "\n",
      "[141 rows x 12 columns]\n"
     ]
    }
   ],
   "source": [
    "##将栅格关联到站点\n",
    "spaceod=df3\n",
    "spaceod['出发站']=None\n",
    "spaceod['到达站']=None\n",
    "spaceod['出发站编号']=0\n",
    "spaceod['到达站编号']=0\n",
    "for i in range(0,len(lineQSY)):\n",
    "    sg=spaceod.loc[spaceod['O编号'].str.contains(lineQSY['区编号'].iloc[i])] \n",
    "    #print(sg)\n",
    "    k=sg.index\n",
    "    spaceod['出发站'].loc[k]=lineQSY['最近站名'].iloc[i]\n",
    "    spaceod['出发站编号'].loc[k]=lineQSY['最近站编号'].iloc[i]\n",
    "for i in range(0,len(lineQSY)):\n",
    "    sg=spaceod.loc[spaceod['D编号'].str.contains(lineQSY['区编号'].iloc[i])] \n",
    "    #print(sg)\n",
    "    k=sg.index\n",
    "    spaceod['到达站'].loc[k]=lineQSY['最近站名'].iloc[i]\n",
    "    spaceod['到达站编号'].loc[k]=lineQSY['最近站编号'].iloc[i]\n",
    "\n",
    "#获取站点的时间戳\n",
    "stod=spaceod\n",
    "print('stod')\n",
    "print(stod)\n",
    "#去除空值\n",
    "stod.dropna()\n",
    "print(stod)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "id": "500127ff",
   "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>日期</th>\n",
       "      <th>出发时间</th>\n",
       "      <th>O编号</th>\n",
       "      <th>出发人数</th>\n",
       "      <th>D编号</th>\n",
       "      <th>到达人数</th>\n",
       "      <th>出发起始时间</th>\n",
       "      <th>出发结束时间</th>\n",
       "      <th>出发站</th>\n",
       "      <th>到达站</th>\n",
       "      <th>出发站编号</th>\n",
       "      <th>到达站编号</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>20211008</td>\n",
       "      <td>15:00-15:30</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>16</td>\n",
       "      <td>ww56cx9</td>\n",
       "      <td>1</td>\n",
       "      <td>15:00</td>\n",
       "      <td>15:30</td>\n",
       "      <td>建材中专(南)</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "      <td>120100</td>\n",
       "      <td>6120020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>20211008</td>\n",
       "      <td>07:30-08:00</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>32</td>\n",
       "      <td>ww5718q</td>\n",
       "      <td>1</td>\n",
       "      <td>07:30</td>\n",
       "      <td>08:00</td>\n",
       "      <td>建材中专(南)</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>120100</td>\n",
       "      <td>670190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>20211008</td>\n",
       "      <td>11:30-12:00</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>17</td>\n",
       "      <td>ww5718v</td>\n",
       "      <td>1</td>\n",
       "      <td>11:30</td>\n",
       "      <td>12:00</td>\n",
       "      <td>建材中专(南)</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>120100</td>\n",
       "      <td>670190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>20211008</td>\n",
       "      <td>14:30-15:00</td>\n",
       "      <td>ww56cx9</td>\n",
       "      <td>18</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>1</td>\n",
       "      <td>14:30</td>\n",
       "      <td>15:00</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "      <td>建材中专(南)</td>\n",
       "      <td>6120020</td>\n",
       "      <td>120100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>20211008</td>\n",
       "      <td>11:30-12:00</td>\n",
       "      <td>ww56cx9</td>\n",
       "      <td>21</td>\n",
       "      <td>ww5712t</td>\n",
       "      <td>1</td>\n",
       "      <td>11:30</td>\n",
       "      <td>12:00</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "      <td>建材中专(南)</td>\n",
       "      <td>6120020</td>\n",
       "      <td>120100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>20211008</td>\n",
       "      <td>08:30-09:00</td>\n",
       "      <td>ww56cx9</td>\n",
       "      <td>45</td>\n",
       "      <td>ww5718v</td>\n",
       "      <td>1</td>\n",
       "      <td>08:30</td>\n",
       "      <td>09:00</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>6120020</td>\n",
       "      <td>670190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>20211008</td>\n",
       "      <td>14:30-15:00</td>\n",
       "      <td>ww56cx9</td>\n",
       "      <td>18</td>\n",
       "      <td>ww5718v</td>\n",
       "      <td>1</td>\n",
       "      <td>14:30</td>\n",
       "      <td>15:00</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>6120020</td>\n",
       "      <td>670190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>20211008</td>\n",
       "      <td>13:00-13:30</td>\n",
       "      <td>ww5712t</td>\n",
       "      <td>10</td>\n",
       "      <td>ww5718v</td>\n",
       "      <td>1</td>\n",
       "      <td>13:00</td>\n",
       "      <td>13:30</td>\n",
       "      <td>建材中专(南)</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>120100</td>\n",
       "      <td>670190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>20211008</td>\n",
       "      <td>13:00-13:30</td>\n",
       "      <td>ww5718v</td>\n",
       "      <td>19</td>\n",
       "      <td>ww5713p</td>\n",
       "      <td>1</td>\n",
       "      <td>13:00</td>\n",
       "      <td>13:30</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>建材中专(南)</td>\n",
       "      <td>670190</td>\n",
       "      <td>120100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>20211008</td>\n",
       "      <td>09:30-10:00</td>\n",
       "      <td>ww5718v</td>\n",
       "      <td>19</td>\n",
       "      <td>ww56cx9</td>\n",
       "      <td>1</td>\n",
       "      <td>09:30</td>\n",
       "      <td>10:00</td>\n",
       "      <td>二九宿舍(南)</td>\n",
       "      <td>九龙湖公园(南)</td>\n",
       "      <td>670190</td>\n",
       "      <td>6120020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           日期         出发时间      O编号  出发人数      D编号  到达人数 出发起始时间 出发结束时间  \\\n",
       "21   20211008  15:00-15:30  ww5713p    16  ww56cx9     1  15:00  15:30   \n",
       "22   20211008  07:30-08:00  ww5713p    32  ww5718q     1  07:30  08:00   \n",
       "23   20211008  11:30-12:00  ww5713p    17  ww5718v     1  11:30  12:00   \n",
       "25   20211008  14:30-15:00  ww56cx9    18  ww5713p     1  14:30  15:00   \n",
       "49   20211008  11:30-12:00  ww56cx9    21  ww5712t     1  11:30  12:00   \n",
       "50   20211008  08:30-09:00  ww56cx9    45  ww5718v     1  08:30  09:00   \n",
       "51   20211008  14:30-15:00  ww56cx9    18  ww5718v     1  14:30  15:00   \n",
       "67   20211008  13:00-13:30  ww5712t    10  ww5718v     1  13:00  13:30   \n",
       "99   20211008  13:00-13:30  ww5718v    19  ww5713p     1  13:00  13:30   \n",
       "100  20211008  09:30-10:00  ww5718v    19  ww56cx9     1  09:30  10:00   \n",
       "\n",
       "          出发站       到达站    出发站编号    到达站编号  \n",
       "21    建材中专(南)  九龙湖公园(南)   120100  6120020  \n",
       "22    建材中专(南)   二九宿舍(南)   120100   670190  \n",
       "23    建材中专(南)   二九宿舍(南)   120100   670190  \n",
       "25   九龙湖公园(南)   建材中专(南)  6120020   120100  \n",
       "49   九龙湖公园(南)   建材中专(南)  6120020   120100  \n",
       "50   九龙湖公园(南)   二九宿舍(南)  6120020   670190  \n",
       "51   九龙湖公园(南)   二九宿舍(南)  6120020   670190  \n",
       "67    建材中专(南)   二九宿舍(南)   120100   670190  \n",
       "99    二九宿舍(南)   建材中专(南)   670190   120100  \n",
       "100   二九宿舍(南)  九龙湖公园(南)   670190  6120020  "
      ]
     },
     "execution_count": 233,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list=[]\n",
    "r=stod.index\n",
    "for i in r:\n",
    "    if stod['出发站'].loc[i]==stod['到达站'].loc[i]:\n",
    "        list.append(i)\n",
    "stod=stod.drop(list,axis=0)\n",
    "stod\n",
    "list=[]\n",
    "r=stod.index\n",
    "for i in r:\n",
    "    if stod['D编号'].loc[i]==stod['O编号'].loc[i]:\n",
    "        list.append(i)\n",
    "stod=stod.drop(list,axis=0)\n",
    "stod"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "id": "70a09d49",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OD计算完毕\n"
     ]
    }
   ],
   "source": [
    "path=r'F:\\徐州\\\\'+'KH-1'+'\\\\'+'OD'+'.csv'\n",
    "stod.to_csv(path)\n",
    "data = pd.read_csv(path)\n",
    "data.to_excel(r'F:\\徐州\\\\'+'KH-1'+'\\\\'+'流量'+'.xlsx')\n",
    "print('OD计算完毕')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "id": "a35a749e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Unnamed: 0        日期         出发时间      O编号  出发人数      D编号  到达人数 出发起始时间  \\\n",
      "0          21  20211008  15:00-15:30  ww5713p    16  ww56cx9     1  15:00   \n",
      "1          22  20211008  07:30-08:00  ww5713p    32  ww5718q     1  07:30   \n",
      "3          25  20211008  14:30-15:00  ww56cx9    18  ww5713p     1  14:30   \n",
      "5          50  20211008  08:30-09:00  ww56cx9    45  ww5718v     1  08:30   \n",
      "8          99  20211008  13:00-13:30  ww5718v    19  ww5713p     1  13:00   \n",
      "9         100  20211008  09:30-10:00  ww5718v    19  ww56cx9     1  09:30   \n",
      "\n",
      "  出发结束时间       出发站       到达站    出发站编号    到达站编号  到达人数OD  出发人数OD  \n",
      "0  15:30   建材中专(南)  九龙湖公园(南)   120100  6120020       4      75  \n",
      "1  08:00   建材中专(南)   二九宿舍(南)   120100   670190       4      75  \n",
      "3  15:00  九龙湖公园(南)   建材中专(南)  6120020   120100       4     102  \n",
      "5  09:00  九龙湖公园(南)   二九宿舍(南)  6120020   670190       4     102  \n",
      "8  13:30   二九宿舍(南)   建材中专(南)   670190   120100       2      38  \n",
      "9  10:00   二九宿舍(南)  九龙湖公园(南)   670190  6120020       2      38  \n",
      "430\n",
      "20\n"
     ]
    }
   ],
   "source": [
    "data2 = data.drop_duplicates(subset=['出发站','到达站'],keep='first')\n",
    "data2['到达人数OD']=0\n",
    "data2['出发人数OD']=0\n",
    "sum=0\n",
    "sum1=0\n",
    "sumdata=pd.DataFrame()\n",
    "for i in range(0,len(data2)):\n",
    "    p=0\n",
    "    pm=0\n",
    "    for j in range(0,len(data)):\n",
    "        if data['出发站'].iloc[j]==data2['出发站'].iloc[i]:\n",
    "            p1=data['到达人数'].iloc[j]\n",
    "            p2=data['出发人数'].iloc[j]\n",
    "            p=p+p1\n",
    "            pm=pm+p2\n",
    "    data2['到达人数OD'].iloc[i]=p\n",
    "    data2['出发人数OD'].iloc[i]=pm\n",
    "    sum=sum+pm\n",
    "    sum1=sum1+p\n",
    "print(data2)\n",
    "sumdata = sumdata.append(data, ignore_index = True)\n",
    "print(sum)\n",
    "print(sum1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "id": "9569b186",
   "metadata": {},
   "outputs": [],
   "source": [
    "data2.to_csv(r'F:\\徐州\\KH-1\\站点OD.csv')\n",
    "data2.to_excel(r'F:\\徐州\\KH-1\\站点OD.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f45affe7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "292d2b4d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "708ae236",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "48ee26ea",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "14adeae3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}