odleglosc_geo.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "forbidden-mitchell",
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas as gpd\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "overall-professor",
   "metadata": {},
   "outputs": [],
   "source": [
    "# dane mapowe z https://www.naturalearthdata.com/downloads/110m-cultural-vectors/\n",
    "world = gpd.read_file('/home/lemur/Work/data/mapy_shp/world/ne_110m_admin_0_countries.shp')\n",
    "\n",
    "# żeby liczyć odległość w metrach\n",
    "world.to_crs(epsg=3310,inplace=True)\n",
    "\n",
    "# środki państw\n",
    "world['center_point'] = world.centroid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "intense-steering",
   "metadata": {},
   "outputs": [],
   "source": [
    "distance_df = pd.DataFrame()\n",
    "\n",
    "for _, row in world.iterrows():\n",
    "    d = world.center_point.distance(row['center_point']) / 1000 # odległość w km\n",
    "    d_df = pd.DataFrame({'from': row['ISO_A2'],\n",
    "                        'to': world.ISO_A2,\n",
    "                        'distance': d})\n",
    "    distance_df = distance_df.append(d_df)\n",
    "\n",
    "distance_df = distance_df[distance_df['distance'] != 0]\n",
    "distance_df.reset_index(inplace=True, drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "israeli-style",
   "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>from</th>\n",
       "      <th>to</th>\n",
       "      <th>distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FJ</td>\n",
       "      <td>TZ</td>\n",
       "      <td>24281.133313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FJ</td>\n",
       "      <td>EH</td>\n",
       "      <td>18594.589359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>FJ</td>\n",
       "      <td>CA</td>\n",
       "      <td>11104.667608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>FJ</td>\n",
       "      <td>US</td>\n",
       "      <td>10194.345005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FJ</td>\n",
       "      <td>KZ</td>\n",
       "      <td>14220.484828</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  from  to      distance\n",
       "0   FJ  TZ  24281.133313\n",
       "1   FJ  EH  18594.589359\n",
       "2   FJ  CA  11104.667608\n",
       "3   FJ  US  10194.345005\n",
       "4   FJ  KZ  14220.484828"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "distance_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "acknowledged-dictionary",
   "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>from</th>\n",
       "      <th>to</th>\n",
       "      <th>distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20039</th>\n",
       "      <td>PL</td>\n",
       "      <td>SK</td>\n",
       "      <td>366.084206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20040</th>\n",
       "      <td>PL</td>\n",
       "      <td>CZ</td>\n",
       "      <td>384.740711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20005</th>\n",
       "      <td>PL</td>\n",
       "      <td>LT</td>\n",
       "      <td>459.598910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20002</th>\n",
       "      <td>PL</td>\n",
       "      <td>HU</td>\n",
       "      <td>532.896891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20006</th>\n",
       "      <td>PL</td>\n",
       "      <td>LV</td>\n",
       "      <td>620.502991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20021</th>\n",
       "      <td>PL</td>\n",
       "      <td>NC</td>\n",
       "      <td>19152.511560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19912</th>\n",
       "      <td>PL</td>\n",
       "      <td>TL</td>\n",
       "      <td>19389.924139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20023</th>\n",
       "      <td>PL</td>\n",
       "      <td>NZ</td>\n",
       "      <td>20135.171462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20024</th>\n",
       "      <td>PL</td>\n",
       "      <td>AU</td>\n",
       "      <td>20407.590593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19911</th>\n",
       "      <td>PL</td>\n",
       "      <td>TF</td>\n",
       "      <td>22639.744261</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>176 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      from  to      distance\n",
       "20039   PL  SK    366.084206\n",
       "20040   PL  CZ    384.740711\n",
       "20005   PL  LT    459.598910\n",
       "20002   PL  HU    532.896891\n",
       "20006   PL  LV    620.502991\n",
       "...    ...  ..           ...\n",
       "20021   PL  NC  19152.511560\n",
       "19912   PL  TL  19389.924139\n",
       "20023   PL  NZ  20135.171462\n",
       "20024   PL  AU  20407.590593\n",
       "19911   PL  TF  22639.744261\n",
       "\n",
       "[176 rows x 3 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "distance_df[distance_df['from'] == 'PL'].sort_values('distance')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "pursuant-fence",
   "metadata": {},
   "outputs": [],
   "source": [
    "distance_df.to_csv('country_distances.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "domestic-queue",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}