{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "# STARE-Based Joins"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "outputs": [],
   "source": [
    "import starepandas\n",
    "import geopandas\n",
    "import datetime\n",
    "import matplotlib.pyplot as plt"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Loading Some Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:10:25.661751Z",
     "iopub.status.busy": "2022-09-15T05:10:25.661537Z",
     "iopub.status.idle": "2022-09-15T05:10:25.679541Z",
     "shell.execute_reply": "2022-09-15T05:10:25.678962Z"
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "cities = ['Buenos Aires', 'Brasilia', 'Santiago', \n",
    "          'Bogota', 'Caracas', 'Sao Paulo', 'Bridgetown']\n",
    "\n",
    "latitudes = [-34.58, -15.78, -33.45, 4.60, 10.48, -23.55, 13.1]\n",
    "longitudes = [-58.66, -47.91, -70.66, -74.08, -66.86, -46.63, -59.62]\n",
    "data =  {'City': cities, \n",
    "         'Latitude': latitudes, 'Longitude': longitudes}\n",
    "\n",
    "cities = starepandas.STAREDataFrame(data)\n",
    "stare = starepandas.sids_from_xy(cities.Longitude, cities.Latitude, level=26)\n",
    "geom = geopandas.points_from_xy(cities.Longitude, cities.Latitude, crs='EPSG:4326')\n",
    "cities.set_sids(stare, inplace=True)\n",
    "cities.set_geometry(geom, inplace=True)\n",
    "cities.add_trixels(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:10:25.682096Z",
     "iopub.status.busy": "2022-09-15T05:10:25.681837Z",
     "iopub.status.idle": "2022-09-15T05:10:26.653929Z",
     "shell.execute_reply": "2022-09-15T05:10:26.653389Z"
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "countries = geopandas.read_file(geopandas.datasets.get_path('naturalearth_lowres'))#.set_crs(4326)\n",
    "samerica = countries[countries.continent=='South America']\n",
    "samerica = starepandas.STAREDataFrame(samerica, add_sids=True, level=7, add_trixels=True)\n",
    "\n",
    "brazil = samerica[samerica.name=='Brazil']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Small Join"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:10:26.656261Z",
     "iopub.status.busy": "2022-09-15T05:10:26.656044Z",
     "iopub.status.idle": "2022-09-15T05:10:26.713552Z",
     "shell.execute_reply": "2022-09-15T05:10:26.713051Z"
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_1001175/189025826.py:1: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n",
      "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n",
      "\n",
      "Left CRS: None\n",
      "Right CRS: EPSG:4326\n",
      "\n",
      "  geopandas.sjoin(samerica, cities, how='left').head()\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\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>pop_est</th>\n",
       "      <th>continent</th>\n",
       "      <th>name</th>\n",
       "      <th>iso_a3</th>\n",
       "      <th>gdp_md_est</th>\n",
       "      <th>geometry</th>\n",
       "      <th>sids_left</th>\n",
       "      <th>trixels_left</th>\n",
       "      <th>index_right</th>\n",
       "      <th>City</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>sids_right</th>\n",
       "      <th>trixels_right</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>44293293</td>\n",
       "      <td>South America</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>ARG</td>\n",
       "      <td>879400.0</td>\n",
       "      <td>MULTIPOLYGON (((-68.63401 -52.63637, -68.25000...</td>\n",
       "      <td>[1831874332805038087, 1831909517177126919, 183...</td>\n",
       "      <td>MULTIPOLYGON (((-68.10744 -55.31801, -67.97225...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Buenos Aires</td>\n",
       "      <td>-34.58</td>\n",
       "      <td>-58.66</td>\n",
       "      <td>2.663379e+18</td>\n",
       "      <td>POLYGON ((-58.66000 -34.58000, -58.66000 -34.5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>17789267</td>\n",
       "      <td>South America</td>\n",
       "      <td>Chile</td>\n",
       "      <td>CHL</td>\n",
       "      <td>436100.0</td>\n",
       "      <td>MULTIPOLYGON (((-68.63401 -52.63637, -68.63335...</td>\n",
       "      <td>[1822268999224786951, 1822339367968964615, 182...</td>\n",
       "      <td>MULTIPOLYGON (((-70.49911 -54.87622, -70.66819...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Santiago</td>\n",
       "      <td>-33.45</td>\n",
       "      <td>-70.66</td>\n",
       "      <td>2.723775e+18</td>\n",
       "      <td>POLYGON ((-70.66000 -33.45000, -70.66000 -33.4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2931</td>\n",
       "      <td>South America</td>\n",
       "      <td>Falkland Is.</td>\n",
       "      <td>FLK</td>\n",
       "      <td>281.8</td>\n",
       "      <td>POLYGON ((-61.20000 -51.85000, -60.00000 -51.2...</td>\n",
       "      <td>[1807104534854500359, 1807245272342855687, 180...</td>\n",
       "      <td>MULTIPOLYGON (((-60.67409 -51.68503, -59.57634...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>3360148</td>\n",
       "      <td>South America</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>URY</td>\n",
       "      <td>73250.0</td>\n",
       "      <td>POLYGON ((-57.62513 -30.21629, -56.97603 -30.1...</td>\n",
       "      <td>[2632353982198054918, 2661627379775963142, 266...</td>\n",
       "      <td>MULTIPOLYGON (((-55.17662 -32.24790, -55.77960...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>207353391</td>\n",
       "      <td>South America</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>BRA</td>\n",
       "      <td>3081000.0</td>\n",
       "      <td>POLYGON ((-53.37366 -33.76838, -53.65054 -33.2...</td>\n",
       "      <td>[2749447572509687812, 2796735368597078020, 286...</td>\n",
       "      <td>MULTIPOLYGON (((-53.69934 -4.63080, -61.44765 ...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Brasilia</td>\n",
       "      <td>-15.78</td>\n",
       "      <td>-47.91</td>\n",
       "      <td>2.867415e+18</td>\n",
       "      <td>POLYGON ((-47.91000 -15.78000, -47.91000 -15.7...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      pop_est      continent          name iso_a3  gdp_md_est  \\\n",
       "9    44293293  South America     Argentina    ARG    879400.0   \n",
       "10   17789267  South America         Chile    CHL    436100.0   \n",
       "20       2931  South America  Falkland Is.    FLK       281.8   \n",
       "28    3360148  South America       Uruguay    URY     73250.0   \n",
       "29  207353391  South America        Brazil    BRA   3081000.0   \n",
       "\n",
       "                                             geometry  \\\n",
       "9   MULTIPOLYGON (((-68.63401 -52.63637, -68.25000...   \n",
       "10  MULTIPOLYGON (((-68.63401 -52.63637, -68.63335...   \n",
       "20  POLYGON ((-61.20000 -51.85000, -60.00000 -51.2...   \n",
       "28  POLYGON ((-57.62513 -30.21629, -56.97603 -30.1...   \n",
       "29  POLYGON ((-53.37366 -33.76838, -53.65054 -33.2...   \n",
       "\n",
       "                                            sids_left  \\\n",
       "9   [1831874332805038087, 1831909517177126919, 183...   \n",
       "10  [1822268999224786951, 1822339367968964615, 182...   \n",
       "20  [1807104534854500359, 1807245272342855687, 180...   \n",
       "28  [2632353982198054918, 2661627379775963142, 266...   \n",
       "29  [2749447572509687812, 2796735368597078020, 286...   \n",
       "\n",
       "                                         trixels_left  index_right  \\\n",
       "9   MULTIPOLYGON (((-68.10744 -55.31801, -67.97225...          0.0   \n",
       "10  MULTIPOLYGON (((-70.49911 -54.87622, -70.66819...          2.0   \n",
       "20  MULTIPOLYGON (((-60.67409 -51.68503, -59.57634...          NaN   \n",
       "28  MULTIPOLYGON (((-55.17662 -32.24790, -55.77960...          NaN   \n",
       "29  MULTIPOLYGON (((-53.69934 -4.63080, -61.44765 ...          1.0   \n",
       "\n",
       "            City  Latitude  Longitude    sids_right  \\\n",
       "9   Buenos Aires    -34.58     -58.66  2.663379e+18   \n",
       "10      Santiago    -33.45     -70.66  2.723775e+18   \n",
       "20           NaN       NaN        NaN           NaN   \n",
       "28           NaN       NaN        NaN           NaN   \n",
       "29      Brasilia    -15.78     -47.91  2.867415e+18   \n",
       "\n",
       "                                        trixels_right  \n",
       "9   POLYGON ((-58.66000 -34.58000, -58.66000 -34.5...  \n",
       "10  POLYGON ((-70.66000 -33.45000, -70.66000 -33.4...  \n",
       "20                                               None  \n",
       "28                                               None  \n",
       "29  POLYGON ((-47.91000 -15.78000, -47.91000 -15.7...  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geopandas.sjoin(samerica, cities, how='left').head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:10:26.715539Z",
     "iopub.status.busy": "2022-09-15T05:10:26.715357Z",
     "iopub.status.idle": "2022-09-15T05:10:26.764969Z",
     "shell.execute_reply": "2022-09-15T05:10:26.764446Z"
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pop_est</th>\n",
       "      <th>continent</th>\n",
       "      <th>name</th>\n",
       "      <th>iso_a3</th>\n",
       "      <th>gdp_md_est</th>\n",
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       "      <th>sids_left</th>\n",
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       "      <th>City</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>sids_right</th>\n",
       "      <th>geometry_right</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>44293293</td>\n",
       "      <td>South America</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>ARG</td>\n",
       "      <td>879400.0</td>\n",
       "      <td>MULTIPOLYGON (((-68.63401 -52.63637, -68.25000...</td>\n",
       "      <td>[1811572950109782022, 1811713687598137351, 181...</td>\n",
       "      <td>MULTIPOLYGON (((-68.10744 -55.31801, -67.97225...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Buenos Aires</td>\n",
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       "      <td>2.663379e+18</td>\n",
       "      <td>POINT (-58.66000 -34.58000)</td>\n",
       "      <td>POLYGON ((-58.66000 -34.58000, -58.66000 -34.5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>17789267</td>\n",
       "      <td>South America</td>\n",
       "      <td>Chile</td>\n",
       "      <td>CHL</td>\n",
       "      <td>436100.0</td>\n",
       "      <td>MULTIPOLYGON (((-68.63401 -52.63637, -68.63335...</td>\n",
       "      <td>[1810517418947117063, 1810622972063383559, 181...</td>\n",
       "      <td>MULTIPOLYGON (((-70.49911 -54.87622, -70.66819...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Santiago</td>\n",
       "      <td>-33.45</td>\n",
       "      <td>-70.66</td>\n",
       "      <td>2.723775e+18</td>\n",
       "      <td>POINT (-70.66000 -33.45000)</td>\n",
       "      <td>POLYGON ((-70.66000 -33.45000, -70.66000 -33.4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2931</td>\n",
       "      <td>South America</td>\n",
       "      <td>Falkland Is.</td>\n",
       "      <td>FLK</td>\n",
       "      <td>281.8</td>\n",
       "      <td>POLYGON ((-61.20000 -51.85000, -60.00000 -51.2...</td>\n",
       "      <td>[1807104534854500359, 1807245272342855687, 180...</td>\n",
       "      <td>MULTIPOLYGON (((-60.67409 -51.68503, -59.57634...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>3360148</td>\n",
       "      <td>South America</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>URY</td>\n",
       "      <td>73250.0</td>\n",
       "      <td>POLYGON ((-57.62513 -30.21629, -56.97603 -30.1...</td>\n",
       "      <td>[2632353982198054918, 2632494719686410247, 263...</td>\n",
       "      <td>MULTIPOLYGON (((-55.17662 -32.24790, -55.77960...</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>207353391</td>\n",
       "      <td>South America</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>BRA</td>\n",
       "      <td>3081000.0</td>\n",
       "      <td>POLYGON ((-53.37366 -33.76838, -53.65054 -33.2...</td>\n",
       "      <td>[2643648165638569991, 2643753718754836487, 264...</td>\n",
       "      <td>MULTIPOLYGON (((-53.69934 -4.63080, -61.44765 ...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Brasilia</td>\n",
       "      <td>-15.78</td>\n",
       "      <td>-47.91</td>\n",
       "      <td>2.867415e+18</td>\n",
       "      <td>POINT (-47.91000 -15.78000)</td>\n",
       "      <td>POLYGON ((-47.91000 -15.78000, -47.91000 -15.7...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      pop_est      continent          name iso_a3  gdp_md_est  \\\n",
       "9    44293293  South America     Argentina    ARG    879400.0   \n",
       "10   17789267  South America         Chile    CHL    436100.0   \n",
       "20       2931  South America  Falkland Is.    FLK       281.8   \n",
       "28    3360148  South America       Uruguay    URY     73250.0   \n",
       "29  207353391  South America        Brazil    BRA   3081000.0   \n",
       "\n",
       "                                        geometry_left  \\\n",
       "9   MULTIPOLYGON (((-68.63401 -52.63637, -68.25000...   \n",
       "10  MULTIPOLYGON (((-68.63401 -52.63637, -68.63335...   \n",
       "20  POLYGON ((-61.20000 -51.85000, -60.00000 -51.2...   \n",
       "28  POLYGON ((-57.62513 -30.21629, -56.97603 -30.1...   \n",
       "29  POLYGON ((-53.37366 -33.76838, -53.65054 -33.2...   \n",
       "\n",
       "                                            sids_left  \\\n",
       "9   [1811572950109782022, 1811713687598137351, 181...   \n",
       "10  [1810517418947117063, 1810622972063383559, 181...   \n",
       "20  [1807104534854500359, 1807245272342855687, 180...   \n",
       "28  [2632353982198054918, 2632494719686410247, 263...   \n",
       "29  [2643648165638569991, 2643753718754836487, 264...   \n",
       "\n",
       "                                         trixels_left  key_right  \\\n",
       "9   MULTIPOLYGON (((-68.10744 -55.31801, -67.97225...        0.0   \n",
       "10  MULTIPOLYGON (((-70.49911 -54.87622, -70.66819...        2.0   \n",
       "20  MULTIPOLYGON (((-60.67409 -51.68503, -59.57634...        NaN   \n",
       "28  MULTIPOLYGON (((-55.17662 -32.24790, -55.77960...        NaN   \n",
       "29  MULTIPOLYGON (((-53.69934 -4.63080, -61.44765 ...        1.0   \n",
       "\n",
       "            City  Latitude  Longitude    sids_right  \\\n",
       "9   Buenos Aires    -34.58     -58.66  2.663379e+18   \n",
       "10      Santiago    -33.45     -70.66  2.723775e+18   \n",
       "20           NaN       NaN        NaN           NaN   \n",
       "28           NaN       NaN        NaN           NaN   \n",
       "29      Brasilia    -15.78     -47.91  2.867415e+18   \n",
       "\n",
       "                 geometry_right  \\\n",
       "9   POINT (-58.66000 -34.58000)   \n",
       "10  POINT (-70.66000 -33.45000)   \n",
       "20                         None   \n",
       "28                         None   \n",
       "29  POINT (-47.91000 -15.78000)   \n",
       "\n",
       "                                        trixels_right  \n",
       "9   POLYGON ((-58.66000 -34.58000, -58.66000 -34.5...  \n",
       "10  POLYGON ((-70.66000 -33.45000, -70.66000 -33.4...  \n",
       "20                                               None  \n",
       "28                                               None  \n",
       "29  POLYGON ((-47.91000 -15.78000, -47.91000 -15.7...  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "starepandas.stare_join(samerica, cities, how='left').head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Granule Intersect"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:10:26.767348Z",
     "iopub.status.busy": "2022-09-15T05:10:26.766901Z",
     "iopub.status.idle": "2022-09-15T05:10:26.769760Z",
     "shell.execute_reply": "2022-09-15T05:10:26.769330Z"
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "fname = '../tests/data/granules/MYD05_L2.A2020060.1635.061.2020061153519.hdf'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:10:26.771596Z",
     "iopub.status.busy": "2022-09-15T05:10:26.771416Z",
     "iopub.status.idle": "2022-09-15T05:10:50.352699Z",
     "shell.execute_reply": "2022-09-15T05:10:50.352149Z"
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "modis = starepandas.read_granule(fname, add_sids=True, adapt_resolution=True, track_first=False)\n",
    "\n",
    "trixels = modis.make_trixels()\n",
    "modis.set_trixels(trixels, inplace=True)\n",
    "\n",
    "geom = geopandas.points_from_xy(modis.lon, modis.lat, crs='EPSG:4326')\n",
    "modis.set_geometry(geom, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Geos based intersects test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:10:50.355515Z",
     "iopub.status.busy": "2022-09-15T05:10:50.355207Z",
     "iopub.status.idle": "2022-09-15T05:10:52.411338Z",
     "shell.execute_reply": "2022-09-15T05:10:52.410712Z"
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0:00:02.052549\n"
     ]
    }
   ],
   "source": [
    "start = datetime.datetime.now()\n",
    "b = modis.intersects(brazil.iloc[0].geometry)\n",
    "print(datetime.datetime.now() - start)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## STARE based intersects test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:10:52.413679Z",
     "iopub.status.busy": "2022-09-15T05:10:52.413410Z",
     "iopub.status.idle": "2022-09-15T05:10:52.558815Z",
     "shell.execute_reply": "2022-09-15T05:10:52.558250Z"
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0:00:00.141935\n"
     ]
    }
   ],
   "source": [
    "start = datetime.datetime.now()\n",
    "a = modis.stare_intersects(brazil['sids'].iloc[0])\n",
    "print(datetime.datetime.now() - start)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:10:52.560987Z",
     "iopub.status.busy": "2022-09-15T05:10:52.560748Z",
     "iopub.status.idle": "2022-09-15T05:11:17.038269Z",
     "shell.execute_reply": "2022-09-15T05:11:17.037761Z"
    },
    "scrolled": true,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.grid(True)\n",
    "\n",
    "brazil.plot(ax=ax, trixels=True, boundary=True, color='y', zorder=0)\n",
    "#brazil.plot(ax=ax, trixels=False, facecolor=\"none\", edgecolor='blue', zorder=1)\n",
    "modis.plot(ax=ax, color='green', zorder=2)\n",
    "modis[a].plot(ax=ax, color='red', trixels=True, zorder=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Now doing Join"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:11:17.040488Z",
     "iopub.status.busy": "2022-09-15T05:11:17.040255Z",
     "iopub.status.idle": "2022-09-15T05:11:18.506809Z",
     "shell.execute_reply": "2022-09-15T05:11:18.506256Z"
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "joined = starepandas.stare_join(modis, samerica, how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:11:18.509280Z",
     "iopub.status.busy": "2022-09-15T05:11:18.509095Z",
     "iopub.status.idle": "2022-09-15T05:11:18.524010Z",
     "shell.execute_reply": "2022-09-15T05:11:18.523477Z"
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "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>lat</th>\n",
       "      <th>lon</th>\n",
       "      <th>sids_left</th>\n",
       "      <th>Scan_Start_Time</th>\n",
       "      <th>Solar_Zenith</th>\n",
       "      <th>Solar_Azimuth</th>\n",
       "      <th>Sensor_Zenith</th>\n",
       "      <th>Sensor_Azimuth</th>\n",
       "      <th>Water_Vapor_Infrared</th>\n",
       "      <th>trixels_left</th>\n",
       "      <th>geometry_left</th>\n",
       "      <th>key_right</th>\n",
       "      <th>pop_est</th>\n",
       "      <th>continent</th>\n",
       "      <th>name</th>\n",
       "      <th>iso_a3</th>\n",
       "      <th>gdp_md_est</th>\n",
       "      <th>geometry_right</th>\n",
       "      <th>sids_right</th>\n",
       "      <th>trixels_right</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-4.923621</td>\n",
       "      <td>-33.579193</td>\n",
       "      <td>2833105768974759241</td>\n",
       "      <td>8.571477e+08</td>\n",
       "      <td>31.989999</td>\n",
       "      <td>-96.479998</td>\n",
       "      <td>65.169999</td>\n",
       "      <td>-99.029998</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POLYGON ((-33.74330 -4.97737, -33.50112 -4.989...</td>\n",
       "      <td>POINT (-33.57919 -4.92362)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-4.956750</td>\n",
       "      <td>-33.786446</td>\n",
       "      <td>2833110603003551593</td>\n",
       "      <td>8.571477e+08</td>\n",
       "      <td>31.779999</td>\n",
       "      <td>-96.449998</td>\n",
       "      <td>64.559999</td>\n",
       "      <td>-99.009998</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POLYGON ((-33.88021 -4.75337, -33.98547 -4.965...</td>\n",
       "      <td>POINT (-33.78645 -4.95675)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-4.988602</td>\n",
       "      <td>-33.986107</td>\n",
       "      <td>2833112722354712041</td>\n",
       "      <td>8.571477e+08</td>\n",
       "      <td>31.579999</td>\n",
       "      <td>-96.419998</td>\n",
       "      <td>63.949999</td>\n",
       "      <td>-98.989998</td>\n",
       "      <td>5.392</td>\n",
       "      <td>POLYGON ((-34.09081 -5.17770, -33.84856 -5.189...</td>\n",
       "      <td>POINT (-33.98611 -4.98860)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-5.019270</td>\n",
       "      <td>-34.178722</td>\n",
       "      <td>2833084363820531337</td>\n",
       "      <td>8.571477e+08</td>\n",
       "      <td>31.389999</td>\n",
       "      <td>-96.389998</td>\n",
       "      <td>63.349999</td>\n",
       "      <td>-98.969998</td>\n",
       "      <td>5.532</td>\n",
       "      <td>POLYGON ((-34.09081 -5.17770, -33.98547 -4.965...</td>\n",
       "      <td>POINT (-34.17872 -5.01927)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-5.048833</td>\n",
       "      <td>-34.364750</td>\n",
       "      <td>2833230005031123593</td>\n",
       "      <td>8.571477e+08</td>\n",
       "      <td>31.199999</td>\n",
       "      <td>-96.359998</td>\n",
       "      <td>62.749999</td>\n",
       "      <td>-98.949998</td>\n",
       "      <td>5.304</td>\n",
       "      <td>POLYGON ((-34.33319 -5.16576, -34.22763 -4.953...</td>\n",
       "      <td>POINT (-34.36475 -5.04883)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        lat        lon            sids_left  Scan_Start_Time  Solar_Zenith  \\\n",
       "0 -4.923621 -33.579193  2833105768974759241     8.571477e+08     31.989999   \n",
       "1 -4.956750 -33.786446  2833110603003551593     8.571477e+08     31.779999   \n",
       "2 -4.988602 -33.986107  2833112722354712041     8.571477e+08     31.579999   \n",
       "3 -5.019270 -34.178722  2833084363820531337     8.571477e+08     31.389999   \n",
       "4 -5.048833 -34.364750  2833230005031123593     8.571477e+08     31.199999   \n",
       "\n",
       "   Solar_Azimuth  Sensor_Zenith  Sensor_Azimuth  Water_Vapor_Infrared  \\\n",
       "0     -96.479998      65.169999      -99.029998                   NaN   \n",
       "1     -96.449998      64.559999      -99.009998                   NaN   \n",
       "2     -96.419998      63.949999      -98.989998                 5.392   \n",
       "3     -96.389998      63.349999      -98.969998                 5.532   \n",
       "4     -96.359998      62.749999      -98.949998                 5.304   \n",
       "\n",
       "                                        trixels_left  \\\n",
       "0  POLYGON ((-33.74330 -4.97737, -33.50112 -4.989...   \n",
       "1  POLYGON ((-33.88021 -4.75337, -33.98547 -4.965...   \n",
       "2  POLYGON ((-34.09081 -5.17770, -33.84856 -5.189...   \n",
       "3  POLYGON ((-34.09081 -5.17770, -33.98547 -4.965...   \n",
       "4  POLYGON ((-34.33319 -5.16576, -34.22763 -4.953...   \n",
       "\n",
       "                geometry_left  key_right  pop_est continent name iso_a3  \\\n",
       "0  POINT (-33.57919 -4.92362)        NaN      NaN       NaN  NaN    NaN   \n",
       "1  POINT (-33.78645 -4.95675)        NaN      NaN       NaN  NaN    NaN   \n",
       "2  POINT (-33.98611 -4.98860)        NaN      NaN       NaN  NaN    NaN   \n",
       "3  POINT (-34.17872 -5.01927)        NaN      NaN       NaN  NaN    NaN   \n",
       "4  POINT (-34.36475 -5.04883)        NaN      NaN       NaN  NaN    NaN   \n",
       "\n",
       "   gdp_md_est geometry_right sids_right trixels_right  \n",
       "0         NaN           None        NaN          None  \n",
       "1         NaN           None        NaN          None  \n",
       "2         NaN           None        NaN          None  \n",
       "3         NaN           None        NaN          None  \n",
       "4         NaN           None        NaN          None  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:11:18.526146Z",
     "iopub.status.busy": "2022-09-15T05:11:18.525962Z",
     "iopub.status.idle": "2022-09-15T05:11:18.543700Z",
     "shell.execute_reply": "2022-09-15T05:11:18.543153Z"
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "joined = geopandas.GeoDataFrame(joined).set_geometry('trixels_left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:11:18.546143Z",
     "iopub.status.busy": "2022-09-15T05:11:18.545932Z",
     "iopub.status.idle": "2022-09-15T05:11:31.296729Z",
     "shell.execute_reply": "2022-09-15T05:11:31.296200Z"
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.grid(True)\n",
    "\n",
    "#ax.set_ylim(-10, 10)\n",
    "#ax.set_xlim(-60, -30)\n",
    "samerica.plot(ax=ax, color='green')\n",
    "joined.plot(ax=ax, column='name')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:11:31.298884Z",
     "iopub.status.busy": "2022-09-15T05:11:31.298651Z",
     "iopub.status.idle": "2022-09-15T05:11:31.314329Z",
     "shell.execute_reply": "2022-09-15T05:11:31.313840Z"
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "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>lat</th>\n",
       "      <th>lon</th>\n",
       "      <th>sids_left</th>\n",
       "      <th>Scan_Start_Time</th>\n",
       "      <th>Solar_Zenith</th>\n",
       "      <th>Solar_Azimuth</th>\n",
       "      <th>Sensor_Zenith</th>\n",
       "      <th>Sensor_Azimuth</th>\n",
       "      <th>Water_Vapor_Infrared</th>\n",
       "      <th>trixels_left</th>\n",
       "      <th>geometry_left</th>\n",
       "      <th>key_right</th>\n",
       "      <th>pop_est</th>\n",
       "      <th>continent</th>\n",
       "      <th>name</th>\n",
       "      <th>iso_a3</th>\n",
       "      <th>gdp_md_est</th>\n",
       "      <th>geometry_right</th>\n",
       "      <th>sids_right</th>\n",
       "      <th>trixels_right</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-4.923621</td>\n",
       "      <td>-33.579193</td>\n",
       "      <td>2833105768974759241</td>\n",
       "      <td>8.571477e+08</td>\n",
       "      <td>31.989999</td>\n",
       "      <td>-96.479998</td>\n",
       "      <td>65.169999</td>\n",
       "      <td>-99.029998</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POLYGON ((-33.74330 -4.97737, -33.50112 -4.989...</td>\n",
       "      <td>POINT (-33.57919 -4.92362)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-4.956750</td>\n",
       "      <td>-33.786446</td>\n",
       "      <td>2833110603003551593</td>\n",
       "      <td>8.571477e+08</td>\n",
       "      <td>31.779999</td>\n",
       "      <td>-96.449998</td>\n",
       "      <td>64.559999</td>\n",
       "      <td>-99.009998</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POLYGON ((-33.88021 -4.75337, -33.98547 -4.965...</td>\n",
       "      <td>POINT (-33.78645 -4.95675)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-4.988602</td>\n",
       "      <td>-33.986107</td>\n",
       "      <td>2833112722354712041</td>\n",
       "      <td>8.571477e+08</td>\n",
       "      <td>31.579999</td>\n",
       "      <td>-96.419998</td>\n",
       "      <td>63.949999</td>\n",
       "      <td>-98.989998</td>\n",
       "      <td>5.392</td>\n",
       "      <td>POLYGON ((-34.09081 -5.17770, -33.84856 -5.189...</td>\n",
       "      <td>POINT (-33.98611 -4.98860)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-5.019270</td>\n",
       "      <td>-34.178722</td>\n",
       "      <td>2833084363820531337</td>\n",
       "      <td>8.571477e+08</td>\n",
       "      <td>31.389999</td>\n",
       "      <td>-96.389998</td>\n",
       "      <td>63.349999</td>\n",
       "      <td>-98.969998</td>\n",
       "      <td>5.532</td>\n",
       "      <td>POLYGON ((-34.09081 -5.17770, -33.98547 -4.965...</td>\n",
       "      <td>POINT (-34.17872 -5.01927)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-5.048833</td>\n",
       "      <td>-34.364750</td>\n",
       "      <td>2833230005031123593</td>\n",
       "      <td>8.571477e+08</td>\n",
       "      <td>31.199999</td>\n",
       "      <td>-96.359998</td>\n",
       "      <td>62.749999</td>\n",
       "      <td>-98.949998</td>\n",
       "      <td>5.304</td>\n",
       "      <td>POLYGON ((-34.33319 -5.16576, -34.22763 -4.953...</td>\n",
       "      <td>POINT (-34.36475 -5.04883)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        lat        lon            sids_left  Scan_Start_Time  Solar_Zenith  \\\n",
       "0 -4.923621 -33.579193  2833105768974759241     8.571477e+08     31.989999   \n",
       "1 -4.956750 -33.786446  2833110603003551593     8.571477e+08     31.779999   \n",
       "2 -4.988602 -33.986107  2833112722354712041     8.571477e+08     31.579999   \n",
       "3 -5.019270 -34.178722  2833084363820531337     8.571477e+08     31.389999   \n",
       "4 -5.048833 -34.364750  2833230005031123593     8.571477e+08     31.199999   \n",
       "\n",
       "   Solar_Azimuth  Sensor_Zenith  Sensor_Azimuth  Water_Vapor_Infrared  \\\n",
       "0     -96.479998      65.169999      -99.029998                   NaN   \n",
       "1     -96.449998      64.559999      -99.009998                   NaN   \n",
       "2     -96.419998      63.949999      -98.989998                 5.392   \n",
       "3     -96.389998      63.349999      -98.969998                 5.532   \n",
       "4     -96.359998      62.749999      -98.949998                 5.304   \n",
       "\n",
       "                                        trixels_left  \\\n",
       "0  POLYGON ((-33.74330 -4.97737, -33.50112 -4.989...   \n",
       "1  POLYGON ((-33.88021 -4.75337, -33.98547 -4.965...   \n",
       "2  POLYGON ((-34.09081 -5.17770, -33.84856 -5.189...   \n",
       "3  POLYGON ((-34.09081 -5.17770, -33.98547 -4.965...   \n",
       "4  POLYGON ((-34.33319 -5.16576, -34.22763 -4.953...   \n",
       "\n",
       "                geometry_left  key_right  pop_est continent name iso_a3  \\\n",
       "0  POINT (-33.57919 -4.92362)        NaN      NaN       NaN  NaN    NaN   \n",
       "1  POINT (-33.78645 -4.95675)        NaN      NaN       NaN  NaN    NaN   \n",
       "2  POINT (-33.98611 -4.98860)        NaN      NaN       NaN  NaN    NaN   \n",
       "3  POINT (-34.17872 -5.01927)        NaN      NaN       NaN  NaN    NaN   \n",
       "4  POINT (-34.36475 -5.04883)        NaN      NaN       NaN  NaN    NaN   \n",
       "\n",
       "   gdp_md_est geometry_right sids_right trixels_right  \n",
       "0         NaN           None        NaN          None  \n",
       "1         NaN           None        NaN          None  \n",
       "2         NaN           None        NaN          None  \n",
       "3         NaN           None        NaN          None  \n",
       "4         NaN           None        NaN          None  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": []
  }
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