Moran's I

spatial-autocorrelation.ipynb

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    "---\n",
    "title: Quantifying Spatial Autocorrelation with Moran's I\n",
    "date: 2024-10-20\n",
    "description: Quantifying spatial autocorrelation with Moran's I\n",
    "categories: [Python, Geospatial]\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "Spatial autocorrelation is a statistical concept that measures how similar values of a variable are based on their proximity to each other on a map. Positive spatial autocorrelation means that geographically nearby values of a variable tend to be similar on a map: high values tend to be located near high values, and low values near low values.\n",
    "By analyzing the spatial distribution of potential hazards, insurers can identify patterns and trends that might not be apparent when looking at data in isolation. This allows for more accurate risk assessment and pricing, ensuring that premiums are set appropriately based on the actual risk in different geospatial cohorts. Additionally, understanding geospatial correlations can help insurers develop targeted strategies for risk mitigation and improve their overall portfolio management. This approach ultimately leads to better financial stability for the insurer and fairer pricing for policyholders.\n",
    "\n",
    "It is well known that tornadoes frequently occur in \"Tornado Alley\" or the tornado belt, a loosely defined location of states including Texas, Louisiana, Oklahoma, Kansas, South Dakota, Iowa and Nebraska. In what follows, we analyze tornado events from 2000-Present and estimate the global spatial autocorrelation for these events using Moran's I, and determie if the results align with our prior assumptions of positive spatial autocorrelation. \n",
    "\n",
    "The National Oceanic and Atmospheric Administration (NOAA) documents the occurrence of storms and other significant weather phenomena having sufficient intensity to cause loss of life, injuries, significant property damage, and/or disruption to commerce. The database for events going back to 1950 is available for download [here](https://www.ncei.noaa.gov/pub/data/swdi/stormevents/csvfiles/), and serves as the starting point for our analysis. U.S. state shapefiles are available [here](https://www2.census.gov/geo/tiger/TIGER2024/STATE/).\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import geopandas as gpd\n",
    "\n",
    "np.set_printoptions(suppress=True, precision=5)\n",
    "pd.options.mode.chained_assignment = None\n",
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.width', None)\n",
    "\n",
    "# Storm data. \n",
    "noaa_path = \"F:/actu-s/CatastropheData/NOAA_Storm_Data/noaa-storm-data-1950-2024.csv.gz\"\n",
    "\n",
    "# US state shapefiles. \n",
    "state_shp = \"C:/Users/i103455/Downloads/tl_2024_us_state.zip\"\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "\n",
    "We begin by reading in the the NOAA storm event data and filter down to tornado events from 2008-present. We also remove lower severity tornado events based on the [Enhanced Fujita Scale](https://en.wikipedia.org/wiki/Enhanced_Fujita_scale):\n",
    "\n",
    "\n",
    "**Enhanced Fujita scale**:\n",
    "\n",
    "- **EFU**: Unknown\n",
    "- **EF0**: 65-85 mph (Light)\n",
    "- **EF1**: 86-110 mph (Moderate)\n",
    "- **EF2**: 111-135 mph (Cosiderable)\n",
    "- **EF3**: 136-165 mph (Severe)\n",
    "- **EF4**: 166-200 mph (Devestating)\n",
    "- **EF5**: >200 mph (Incredible)\n",
    "\n",
    "Events with TOR_F_SCALE  =  \"F0\", \"F1\", \"EF0\", \"EF1\" are excluded. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of storms: (2917, 3)\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "    .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>EVENT_ID</th>\n",
       "      <th>TOR_F_SCALE</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>105611</td>\n",
       "      <td>EF2</td>\n",
       "      <td>POINT (-96.30000 43.14210)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>80215</td>\n",
       "      <td>EF2</td>\n",
       "      <td>POINT (-86.01250 37.66250)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>80216</td>\n",
       "      <td>EF2</td>\n",
       "      <td>POINT (-85.77590 37.69650)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>80218</td>\n",
       "      <td>EF2</td>\n",
       "      <td>POINT (-85.06490 37.68890)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>79065</td>\n",
       "      <td>EF2</td>\n",
       "      <td>POINT (-85.38120 37.81130)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   EVENT_ID TOR_F_SCALE                    geometry\n",
       "0    105611         EF2  POINT (-96.30000 43.14210)\n",
       "1     80215         EF2  POINT (-86.01250 37.66250)\n",
       "2     80216         EF2  POINT (-85.77590 37.69650)\n",
       "3     80218         EF2  POINT (-85.06490 37.68890)\n",
       "4     79065         EF2  POINT (-85.38120 37.81130)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "# Obtained here: https://www.ncei.noaa.gov/pub/data/swdi/stormevents/csvfiles/\n",
    "dfstorms_all = pd.read_csv(noaa_path, low_memory=False)\n",
    "\n",
    "keep_events = [\n",
    "    \"F2\", \"EF2\", \"F3\", \"F4\", \"F5\", \"EF3\", \"EF4\", \"EF5\"\n",
    "]\n",
    "\n",
    "dfstorms = dfstorms_all[\n",
    "    (dfstorms_all.YEAR>=2008) & \n",
    "    (dfstorms_all.EVENT_TYPE==\"Tornado\") &\n",
    "    (dfstorms_all.TOR_F_SCALE.isin(keep_events))\n",
    "]\n",
    "\n",
    "dfstorms = (\n",
    "    dfstorms\n",
    "    .dropna(subset=[\"BEGIN_LAT\", \"BEGIN_LON\", \"TOR_F_SCALE\"])\n",
    "    .reset_index(drop=True)\n",
    ")\n",
    "\n",
    "# Filter storms to lower 48 states.\n",
    "storms = gpd.GeoDataFrame(\n",
    "    dfstorms,\n",
    "    geometry=gpd.points_from_xy(dfstorms.BEGIN_LON, dfstorms.BEGIN_LAT),\n",
    "    crs=\"EPSG:4326\"\n",
    ")\n",
    "\n",
    "storms = storms[[\"EVENT_ID\", \"TOR_F_SCALE\", \"geometry\"]]\n",
    "storms = storms.cx[-125:65, 24.6:50].reset_index(drop=True)\n",
    "\n",
    "print(f\"Number of storms: {storms.shape}\")\n",
    "\n",
    "storms.head()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<br>\n",
    "\n",
    "Reviewing the distribution of F and EF events:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TOR_F_SCALE\n",
       "EF2    2197\n",
       "EF3     579\n",
       "EF4     128\n",
       "EF5      13\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "storms.TOR_F_SCALE.value_counts()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<br> \n",
    "\n",
    "Load the state shapefile and overlay retained tornado events:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "import os\n",
    "import sys\n",
    "\n",
    "# This suppresses `Cannot find header.dxf (GDAL_DATA is not defined)` warning.\n",
    "os.environ['GDAL_DATA'] = os.path.join(f'{os.sep}'.join(sys.executable.split(os.sep)[:-1]), 'Library', 'share', 'gdal')\n",
    "\n",
    "# Filter to lower 48 states. \n",
    "states = gpd.read_file(state_shp).to_crs(\"EPSG:4326\")[[\"NAME\", \"ALAND\", \"geometry\"]]\n",
    "states = states.cx[-125:65, 24.6:50].reset_index(drop=True)\n",
    "\n",
    "fig, ax = plt.subplots(1, 1, figsize=(10, 8), tight_layout=True)\n",
    "ax.set_title(\"U.S. Tornadoes ex. EF0, EF1: 2008-Present\", fontsize=10)\n",
    "states.boundary.plot(ax=ax, edgecolor=\"grey\", linewidth=.35)\n",
    "storms.plot(ax=ax, color=\"blue\", marker=\"x\", markersize=25, alpha=.35)\n",
    "ax.axis(\"off\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<br>\n",
    "\n",
    "There are more tornadoes in the mid-south and southeast than expected. Nonetheless, there exists a clear spatial pattern to the events: Tornadoes do not appear randomly distributed over the lower 48 states. We can use Global Moran's I to gauge the degree of spatial autocorrelation inherent in the data. \n",
    "\n",
    "In order to assign each tornado to a state, a spatial join is performed where each event is assigned to the state polygon that encloses it:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of events: 2917.0\n"
     ]
    },
    {
     "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>NAME</th>\n",
       "      <th>ALAND</th>\n",
       "      <th>n</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>131185561946</td>\n",
       "      <td>253.0</td>\n",
       "      <td>POLYGON ((-85.12733 31.76256, -85.12753 31.762...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>294366118294</td>\n",
       "      <td>7.0</td>\n",
       "      <td>POLYGON ((-110.75069 37.00301, -110.74193 37.0...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>134658517854</td>\n",
       "      <td>133.0</td>\n",
       "      <td>POLYGON ((-90.95577 34.11871, -90.95451 34.117...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>California</td>\n",
       "      <td>403673433805</td>\n",
       "      <td>3.0</td>\n",
       "      <td>MULTIPOLYGON (((-119.99987 41.18397, -119.9998...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Colorado</td>\n",
       "      <td>268418973518</td>\n",
       "      <td>31.0</td>\n",
       "      <td>POLYGON ((-105.15504 36.99526, -105.15543 36.9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Connecticut</td>\n",
       "      <td>12541999507</td>\n",
       "      <td>0.0</td>\n",
       "      <td>POLYGON ((-72.52790 41.17777, -72.55156 41.173...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Delaware</td>\n",
       "      <td>5046692239</td>\n",
       "      <td>4.0</td>\n",
       "      <td>POLYGON ((-75.50949 39.68652, -75.50942 39.686...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>District of Columbia</td>\n",
       "      <td>158316181</td>\n",
       "      <td>0.0</td>\n",
       "      <td>POLYGON ((-77.11975 38.93435, -77.11886 38.935...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Florida</td>\n",
       "      <td>138965379385</td>\n",
       "      <td>40.0</td>\n",
       "      <td>MULTIPOLYGON (((-83.10874 24.62949, -83.10711 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Georgia</td>\n",
       "      <td>149485762701</td>\n",
       "      <td>153.0</td>\n",
       "      <td>POLYGON ((-81.09538 31.52098, -81.09710 31.519...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Idaho</td>\n",
       "      <td>214050504522</td>\n",
       "      <td>0.0</td>\n",
       "      <td>POLYGON ((-116.35844 49.00047, -116.34805 49.0...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Illinois</td>\n",
       "      <td>143778206717</td>\n",
       "      <td>140.0</td>\n",
       "      <td>POLYGON ((-87.89243 38.28285, -87.89334 38.282...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Indiana</td>\n",
       "      <td>92786694938</td>\n",
       "      <td>96.0</td>\n",
       "      <td>POLYGON ((-86.32960 38.18180, -86.33037 38.182...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Iowa</td>\n",
       "      <td>144660344616</td>\n",
       "      <td>123.0</td>\n",
       "      <td>POLYGON ((-95.86095 43.50004, -95.85979 43.500...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Kansas</td>\n",
       "      <td>211753821560</td>\n",
       "      <td>129.0</td>\n",
       "      <td>POLYGON ((-94.61764 37.76124, -94.61766 37.760...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Kentucky</td>\n",
       "      <td>102266755818</td>\n",
       "      <td>118.0</td>\n",
       "      <td>MULTIPOLYGON (((-89.57120 36.55214, -89.57114 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Louisiana</td>\n",
       "      <td>111920866908</td>\n",
       "      <td>122.0</td>\n",
       "      <td>POLYGON ((-92.72474 33.01439, -92.72365 33.014...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Maine</td>\n",
       "      <td>79888396620</td>\n",
       "      <td>0.0</td>\n",
       "      <td>POLYGON ((-67.80569 45.68005, -67.80363 45.677...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Maryland</td>\n",
       "      <td>25151223822</td>\n",
       "      <td>5.0</td>\n",
       "      <td>POLYGON ((-75.75600 39.24607, -75.75579 39.243...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Massachusetts</td>\n",
       "      <td>20204400635</td>\n",
       "      <td>3.0</td>\n",
       "      <td>POLYGON ((-71.25515 42.73655, -71.25510 42.736...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    NAME         ALAND      n  \\\n",
       "0                Alabama  131185561946  253.0   \n",
       "1                Arizona  294366118294    7.0   \n",
       "2               Arkansas  134658517854  133.0   \n",
       "3             California  403673433805    3.0   \n",
       "4               Colorado  268418973518   31.0   \n",
       "5            Connecticut   12541999507    0.0   \n",
       "6               Delaware    5046692239    4.0   \n",
       "7   District of Columbia     158316181    0.0   \n",
       "8                Florida  138965379385   40.0   \n",
       "9                Georgia  149485762701  153.0   \n",
       "10                 Idaho  214050504522    0.0   \n",
       "11              Illinois  143778206717  140.0   \n",
       "12               Indiana   92786694938   96.0   \n",
       "13                  Iowa  144660344616  123.0   \n",
       "14                Kansas  211753821560  129.0   \n",
       "15              Kentucky  102266755818  118.0   \n",
       "16             Louisiana  111920866908  122.0   \n",
       "17                 Maine   79888396620    0.0   \n",
       "18              Maryland   25151223822    5.0   \n",
       "19         Massachusetts   20204400635    3.0   \n",
       "\n",
       "                                             geometry  \n",
       "0   POLYGON ((-85.12733 31.76256, -85.12753 31.762...  \n",
       "1   POLYGON ((-110.75069 37.00301, -110.74193 37.0...  \n",
       "2   POLYGON ((-90.95577 34.11871, -90.95451 34.117...  \n",
       "3   MULTIPOLYGON (((-119.99987 41.18397, -119.9998...  \n",
       "4   POLYGON ((-105.15504 36.99526, -105.15543 36.9...  \n",
       "5   POLYGON ((-72.52790 41.17777, -72.55156 41.173...  \n",
       "6   POLYGON ((-75.50949 39.68652, -75.50942 39.686...  \n",
       "7   POLYGON ((-77.11975 38.93435, -77.11886 38.935...  \n",
       "8   MULTIPOLYGON (((-83.10874 24.62949, -83.10711 ...  \n",
       "9   POLYGON ((-81.09538 31.52098, -81.09710 31.519...  \n",
       "10  POLYGON ((-116.35844 49.00047, -116.34805 49.0...  \n",
       "11  POLYGON ((-87.89243 38.28285, -87.89334 38.282...  \n",
       "12  POLYGON ((-86.32960 38.18180, -86.33037 38.182...  \n",
       "13  POLYGON ((-95.86095 43.50004, -95.85979 43.500...  \n",
       "14  POLYGON ((-94.61764 37.76124, -94.61766 37.760...  \n",
       "15  MULTIPOLYGON (((-89.57120 36.55214, -89.57114 ...  \n",
       "16  POLYGON ((-92.72474 33.01439, -92.72365 33.014...  \n",
       "17  POLYGON ((-67.80569 45.68005, -67.80363 45.677...  \n",
       "18  POLYGON ((-75.75600 39.24607, -75.75579 39.243...  \n",
       "19  POLYGON ((-71.25515 42.73655, -71.25510 42.736...  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "dfn = (\n",
    "    states\n",
    "    .sjoin(storms)\n",
    "    .groupby([\"NAME\", \"ALAND\"], as_index=False).size()\n",
    "    .rename({\"size\": \"n\"}, axis=1)\n",
    ")\n",
    "\n",
    "# Merge dfn with states to get back geometry associated with each state.\n",
    "# gdf will be a GeoDataFrame.\n",
    "gdf = (\n",
    "    states\n",
    "    .merge(dfn, on=[\"NAME\", \"ALAND\"], how=\"left\")\n",
    "    .fillna(value={\"n\": 0})[[\"NAME\", \"ALAND\", \"n\", \"geometry\"]]\n",
    "    .sort_values(\"NAME\")\n",
    "    .reset_index(drop=True)\n",
    ")\n",
    "\n",
    "print(f\"Total number of events: {gdf['n'].sum()}\")\n",
    "\n",
    "gdf.head(20)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "\n",
    "Visualizing the number of tornadoes by state:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "cmap = \"turbo\"\n",
    "\n",
    "fig, ax = plt.subplots(1, 1, figsize=(10, 8), tight_layout=True)\n",
    "ax.set_title(\"U.S. Tornadoes by State ex. EF0, EF1: 2000-Present\", fontsize=9)\n",
    "gdf.plot(\n",
    "    ax=ax, column=\"n\", edgecolor=\"gray\", linewidth=.50, \n",
    "    cmap=cmap, alpha=.750, legend=True,\n",
    "    legend_kwds={\"label\": \"Nbr. Tornadoes\", \"orientation\": \"vertical\", \"shrink\": .35}\n",
    "    )\n",
    "ax.axis(\"off\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<br>\n",
    "\n",
    "Texas appears to have a large number of events, but this may be due to the fact that Texas has the largest land area of any state in the lower 48. If tornadoes were randomly distributed, we wouldn’t expect to see clusters of similar values on the map. However, our attention is drawn to south central and south eastern states, where hues are brighter compared with coastal regions. \n",
    "\n",
    "Let's take a look at number of events divided by ALAND:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "cmap = \"turbo\"\n",
    "\n",
    "gdf[\"n_div_ALAND\"] = gdf[\"n\"] / gdf[\"ALAND\"]\n",
    "\n",
    "fig, ax = plt.subplots(1, 1, figsize=(10, 8), tight_layout=True)\n",
    "ax.set_title(\"U.S. tornadoes by state / land area ex. F0, EF0, F1, EF1: 2000-Present\", fontsize=9)\n",
    "gdf.plot(\n",
    "    ax=ax, column=\"n_div_ALAND\", edgecolor=\"gray\", linewidth=.50, \n",
    "    cmap=cmap, alpha=.750, legend=True,\n",
    "    legend_kwds={\"label\": \"Nbr. Tornadoes\", \"orientation\": \"vertical\", \"shrink\": .35}\n",
    "    )\n",
    "ax.axis(\"off\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<br>\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<br>\n",
    "\n",
    "Mississippi and Alabama are consistent with the raw counts choropleth, but Texas doesn't stand out as much when normalized by total land area. Nonetheless, raw tornado counts are used for the subsequent analysis. \n",
    "\n",
    "<br>\n",
    "\n",
    "\n",
    "### Spatial Weights\n",
    "\n",
    "In order to quantify spatial autocorrelation, it is first necessary to define the idea of closeness or proximity between geospatial units. \n",
    "The spatial weights matrix $W$ encodes the spatial relationships between different locations in a dataset in much the same way as an adjacency matrix used in Graph Theory and Network Science. For a dataset with $N$ geospatial units, $W$ \n",
    "will have dimension $N \\times N$, with 0's along the main diagonal. Each element $w_{ij}$ represents the spatial relationship between locations $i$ and $j$. The relationship can be based on distance, contiguity or some other criteria. More information of spatial weights matrices is available [here](https://geographicdata.science/book/notebooks/04_spatial_weights.html). \n",
    "  \n",
    "We use the Queen contiguity matrix, which is a row-standardized, symmetric matrix that indicates whether two areas are neighbors based on whether they share a vertex or edge. The value at cell $w_{i,j}$ is 1 if $i$ and $j$ are neighbors and 0 otherwise. Using PySAL, the weights matrix with Queen contiguity can be created as follows:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    0   1   2   3   4   5   6   7   8   9   10  11  12  13  14  15  16  17  \\\n",
       "0    0   0   0   0   0   0   0   0   1   1   0   0   0   0   0   0   0   0   \n",
       "1    0   0   0   1   1   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "2    0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   \n",
       "3    0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "4    0   1   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   \n",
       "5    0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "6    0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "7    0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "8    1   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   \n",
       "9    1   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   \n",
       "10   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "11   0   0   0   0   0   0   0   0   0   0   0   0   1   1   0   1   0   0   \n",
       "12   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   1   0   0   \n",
       "13   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   \n",
       "14   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "15   0   0   0   0   0   0   0   0   0   0   0   1   1   0   0   0   0   0   \n",
       "16   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "17   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "18   0   0   0   0   0   0   1   1   0   0   0   0   0   0   0   0   0   0   \n",
       "19   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "20   0   0   0   0   0   0   0   0   0   0   0   1   1   0   0   0   0   0   \n",
       "21   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   \n",
       "22   1   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   \n",
       "23   0   0   1   0   0   0   0   0   0   0   0   1   0   1   1   1   0   0   \n",
       "24   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   \n",
       "25   0   0   0   0   1   0   0   0   0   0   0   0   0   1   1   0   0   0   \n",
       "26   0   1   0   1   0   0   0   0   0   0   1   0   0   0   0   0   0   0   \n",
       "27   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   \n",
       "28   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   \n",
       "29   0   1   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "30   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "31   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   \n",
       "32   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "33   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   1   0   0   \n",
       "34   0   0   1   0   1   0   0   0   0   0   0   0   0   0   1   0   0   0   \n",
       "35   0   0   0   1   0   0   0   0   0   0   1   0   0   0   0   0   0   0   \n",
       "36   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   \n",
       "37   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "38   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   \n",
       "39   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   \n",
       "40   1   0   1   0   0   0   0   0   0   1   0   0   0   0   0   1   0   0   \n",
       "41   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   \n",
       "42   0   1   0   0   1   0   0   0   0   0   1   0   0   0   0   0   0   0   \n",
       "43   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "44   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   1   0   0   \n",
       "45   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   \n",
       "46   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   \n",
       "47   0   0   0   0   0   0   0   0   0   0   0   1   0   1   0   0   0   0   \n",
       "48   0   0   0   0   1   0   0   0   0   0   1   0   0   0   0   0   0   0   \n",
       "\n",
       "    18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  \\\n",
       "0    0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "1    0   0   0   0   0   0   0   0   1   0   0   1   0   0   0   0   0   0   \n",
       "2    0   0   0   0   1   1   0   0   0   0   0   0   0   0   0   0   1   0   \n",
       "3    0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   1   \n",
       "4    0   0   0   0   0   0   0   1   0   0   0   1   0   0   0   0   1   0   \n",
       "5    0   1   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0   \n",
       "6    1   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   \n",
       "7    1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "8    0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "9    0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   \n",
       "10   0   0   0   0   0   0   1   0   1   0   0   0   0   0   0   0   0   1   \n",
       "11   0   0   1   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "12   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   \n",
       "13   0   0   0   1   0   1   0   1   0   0   0   0   0   0   0   0   0   0   \n",
       "14   0   0   0   0   0   1   0   1   0   0   0   0   0   0   0   0   1   0   \n",
       "15   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   1   0   0   \n",
       "16   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "17   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   \n",
       "18   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "19   0   0   0   0   0   0   0   0   0   1   0   0   1   0   0   0   0   0   \n",
       "20   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   1   0   0   \n",
       "21   0   0   1   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   \n",
       "22   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "23   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   1   0   \n",
       "24   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   \n",
       "25   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "26   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   \n",
       "27   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "28   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0   \n",
       "29   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   \n",
       "30   0   1   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   \n",
       "31   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "32   0   0   0   1   0   0   1   0   0   0   0   0   0   0   0   0   0   0   \n",
       "33   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "34   0   0   0   0   0   1   0   0   0   0   0   1   0   0   0   0   0   0   \n",
       "35   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   \n",
       "36   1   0   0   0   0   0   0   0   0   0   1   0   1   0   0   1   0   0   \n",
       "37   0   1   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0   \n",
       "38   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   \n",
       "39   0   0   0   1   0   0   1   1   0   0   0   0   0   0   1   0   0   0   \n",
       "40   0   0   0   0   1   1   0   0   0   0   0   0   0   1   0   0   0   0   \n",
       "41   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   1   0   \n",
       "42   0   0   0   0   0   0   0   0   1   0   0   1   0   0   0   0   0   0   \n",
       "43   0   1   0   0   0   0   0   0   0   1   0   0   1   0   0   0   0   0   \n",
       "44   1   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   \n",
       "45   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   \n",
       "46   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   \n",
       "47   0   0   1   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   \n",
       "48   0   0   0   0   0   0   1   1   0   0   0   0   0   0   0   0   0   0   \n",
       "\n",
       "    36  37  38  39  40  41  42  43  44  45  46  47  48  \n",
       "0    0   0   0   0   1   0   0   0   0   0   0   0   0  \n",
       "1    0   0   0   0   0   0   1   0   0   0   0   0   0  \n",
       "2    0   0   0   0   1   1   0   0   0   0   0   0   0  \n",
       "3    0   0   0   0   0   0   0   0   0   0   0   0   0  \n",
       "4    0   0   0   0   0   0   1   0   0   0   0   0   1  \n",
       "5    0   1   0   0   0   0   0   0   0   0   0   0   0  \n",
       "6    1   0   0   0   0   0   0   0   0   0   0   0   0  \n",
       "7    0   0   0   0   0   0   0   0   1   0   0   0   0  \n",
       "8    0   0   0   0   0   0   0   0   0   0   0   0   0  \n",
       "9    0   0   1   0   1   0   0   0   0   0   0   0   0  \n",
       "10   0   0   0   0   0   0   1   0   0   1   0   0   1  \n",
       "11   0   0   0   0   0   0   0   0   0   0   0   1   0  \n",
       "12   0   0   0   0   0   0   0   0   0   0   0   0   0  \n",
       "13   0   0   0   1   0   0   0   0   0   0   0   1   0  \n",
       "14   0   0   0   0   0   0   0   0   0   0   0   0   0  \n",
       "15   0   0   0   0   1   0   0   0   1   0   1   0   0  \n",
       "16   0   0   0   0   0   1   0   0   0   0   0   0   0  \n",
       "17   0   0   0   0   0   0   0   0   0   0   0   0   0  \n",
       "18   1   0   0   0   0   0   0   0   1   0   1   0   0  \n",
       "19   0   1   0   0   0   0   0   1   0   0   0   0   0  \n",
       "20   0   0   0   0   0   0   0   0   0   0   0   1   0  \n",
       "21   0   0   0   1   0   0   0   0   0   0   0   1   0  \n",
       "22   0   0   0   0   1   0   0   0   0   0   0   0   0  \n",
       "23   0   0   0   0   1   0   0   0   0   0   0   0   0  \n",
       "24   0   0   0   1   0   0   0   0   0   0   0   0   1  \n",
       "25   0   0   0   1   0   0   0   0   0   0   0   0   1  \n",
       "26   0   0   0   0   0   0   1   0   0   0   0   0   0  \n",
       "27   0   0   0   0   0   0   0   1   0   0   0   0   0  \n",
       "28   1   0   0   0   0   0   0   0   0   0   0   0   0  \n",
       "29   0   0   0   0   0   1   1   0   0   0   0   0   0  \n",
       "30   1   1   0   0   0   0   0   1   0   0   0   0   0  \n",
       "31   0   0   1   0   1   0   0   0   1   0   0   0   0  \n",
       "32   0   0   0   1   0   0   0   0   0   0   0   0   0  \n",
       "33   1   0   0   0   0   0   0   0   0   0   1   0   0  \n",
       "34   0   0   0   0   0   1   0   0   0   0   0   0   0  \n",
       "35   0   0   0   0   0   0   0   0   0   1   0   0   0  \n",
       "36   0   0   0   0   0   0   0   0   0   0   1   0   0  \n",
       "37   0   0   0   0   0   0   0   0   0   0   0   0   0  \n",
       "38   0   0   0   0   0   0   0   0   0   0   0   0   0  \n",
       "39   0   0   0   0   0   0   0   0   0   0   0   0   1  \n",
       "40   0   0   0   0   0   0   0   0   1   0   0   0   0  \n",
       "41   0   0   0   0   0   0   0   0   0   0   0   0   0  \n",
       "42   0   0   0   0   0   0   0   0   0   0   0   0   1  \n",
       "43   0   0   0   0   0   0   0   0   0   0   0   0   0  \n",
       "44   0   0   0   0   1   0   0   0   0   0   1   0   0  \n",
       "45   0   0   0   0   0   0   0   0   0   0   0   0   0  \n",
       "46   1   0   0   0   0   0   0   0   1   0   0   0   0  \n",
       "47   0   0   0   0   0   0   0   0   0   0   0   0   0  \n",
       "48   0   0   0   1   0   0   1   0   0   0   0   0   0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "from pysal.lib import weights\n",
    "\n",
    "# Queen contiguity.\n",
    "wq = weights.contiguity.Queen.from_dataframe(gdf, use_index=True)\n",
    "\n",
    "# Convert to dense matrix for viewing:\n",
    "W = pd.DataFrame(*wq.full()).astype(int)\n",
    "\n",
    "W\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<br>\n",
    "\n",
    "The number of neighbors for each state is available in `wq`'s `cardinalities` attribute:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: 4,\n",
       " 1: 5,\n",
       " 2: 6,\n",
       " 3: 3,\n",
       " 4: 7,\n",
       " 5: 3,\n",
       " 6: 3,\n",
       " 7: 2,\n",
       " 8: 2,\n",
       " 9: 5,\n",
       " 10: 6,\n",
       " 11: 6,\n",
       " 12: 4,\n",
       " 13: 6,\n",
       " 14: 4,\n",
       " 15: 7,\n",
       " 16: 3,\n",
       " 17: 1,\n",
       " 18: 5,\n",
       " 19: 5,\n",
       " 20: 5,\n",
       " 21: 5,\n",
       " 22: 4,\n",
       " 23: 8,\n",
       " 24: 4,\n",
       " 25: 6,\n",
       " 26: 5,\n",
       " 27: 3,\n",
       " 28: 3,\n",
       " 29: 5,\n",
       " 30: 6,\n",
       " 31: 4,\n",
       " 32: 3,\n",
       " 33: 5,\n",
       " 34: 6,\n",
       " 35: 4,\n",
       " 36: 6,\n",
       " 37: 3,\n",
       " 38: 2,\n",
       " 39: 6,\n",
       " 40: 8,\n",
       " 41: 4,\n",
       " 42: 6,\n",
       " 43: 3,\n",
       " 44: 6,\n",
       " 45: 2,\n",
       " 46: 5,\n",
       " 47: 4,\n",
       " 48: 6}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "wq.cardinalities\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<br>\n",
    "\n",
    "`gdf` is sorted by NAME, so index 0 represents Alabama, index 1 = Arizona, etc. Iowa is at index 13. The columns with value 1 for row index 13 represent Iowa's neighbors in terms of Queen contiguity:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11        Illinois\n",
       "21       Minnesota\n",
       "23        Missouri\n",
       "25        Nebraska\n",
       "39    South Dakota\n",
       "47       Wisconsin\n",
       "Name: NAME, dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "iowa = W.loc[13]\n",
    "\n",
    "iowa_neighbor_indices = iowa[iowa==1].index\n",
    "\n",
    "iowa_neighbor_names = gdf.loc[iowa_neighbor_indices, \"NAME\"]\n",
    "\n",
    "iowa_neighbor_names\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<br>\n",
    "\n",
    "Spatial lag calculates the average number of tornadoes for a given state's neighbors, and assigns the result to the state:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# Row standardized weights.\n",
    "wq.transform = \"r\"\n",
    "\n",
    "lag = weights.lag_spatial(wq, gdf[\"n\"])\n",
    "\n",
    "gdf[\"lag\"] = lag\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<br>\n",
    "\n",
    "For Iowa, the spatial lag is 79.83. If we compute the average number of tornadoes from Illinois, Minnesota, Missouri, Nebraska, South Dakota and Wisconsin, we should get 79.83:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iowa spatial lag - actual / expected: 79.83 / 79.83\n"
     ]
    }
   ],
   "source": [
    "\n",
    "actual = gdf.loc[iowa_neighbor_indices, \"n\"].mean()\n",
    "\n",
    "print(f\"Iowa spatial lag - actual / expected: {actual:.2f} / 79.83\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<br> \n",
    "\n",
    "Visualizing the spatial lag can provide further insight into the underlying process. It tends to smooth spatial data, making it easier to identify patterns and trends:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "cmap = \"turbo\"\n",
    "\n",
    "fig, ax = plt.subplots(1, 1, figsize=(10, 8), tight_layout=True)\n",
    "ax.set_title(\"Spatial lag\", fontsize=9)\n",
    "gdf.plot(\n",
    "    ax=ax, column=\"lag\", edgecolor=\"gray\", linewidth=.50, \n",
    "    cmap=cmap, alpha=.750, legend=True,\n",
    "    legend_kwds={\"label\": \"Nbr. Tornadoes\", \"orientation\": \"vertical\", \"shrink\": .35}\n",
    "    )\n",
    "ax.axis(\"off\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<br>\n",
    "\n",
    "## Global Moran's I\n",
    "\n",
    "Now that we've defined the spatial weights matrix, it is straightforward to quantify spatial autocorrelation. \n",
    "Global Moran's I is a measure of the overall clustering of spatial data, defined as\n",
    "\n",
    "$$\n",
    "I = \\frac{N}{W} \\frac{\\sum_{i=1}^{N} \\sum_{j=1}^{N} w_{ij}(x_{i} - \\bar{x})(x_{j} - \\bar{x})}{\\sum_{i=1}^{N} (x_{i} - \\bar{x})^{2}},\n",
    "$$\n",
    "\n",
    "\n",
    "where\n",
    "\n",
    "- $N$: The number of spatial units, 49 in our case (lower 48 + District of Columbia)\n",
    "- $W$: The sum of values in the spatial weights matrix\n",
    "- $x$: The variable of interest (tornadoes)\n",
    "- $\\bar{x}$: The global mean of $x$ over all spatial units\n",
    "- $w_{ij}$: Elements of the spatial weights matrix which encodes spatial interaction\n",
    "\n",
    "<br>\n",
    "\n",
    "We'll again rely on Queen contiguity. We first compute Global Moran's I using the formula above, then compare the result with the value returned by PySAL."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Manual calculation of Global Moran's I: 0.60.\n"
     ]
    }
   ],
   "source": [
    "\n",
    "wq = weights.contiguity.Queen.from_dataframe(gdf, use_index=True)\n",
    "W = pd.DataFrame(*wq.full()).values\n",
    "\n",
    "# Computing Moran's I manually. \n",
    "N = gdf.shape[0]\n",
    "\n",
    "# Average number tornadoes over all states.\n",
    "xbar = gdf[\"n\"].mean()\n",
    "\n",
    "# Denominator of Moran's I.\n",
    "denom = np.sum((gdf[\"n\"] - xbar)**2)\n",
    "\n",
    "# Update numerator at each iteration.\n",
    "numer = 0\n",
    "\n",
    "for i in range(N):\n",
    "    x_i = gdf.at[i, \"n\"]\n",
    "    for j in range(N):\n",
    "        x_j = gdf.at[j, \"n\"]\n",
    "        w_ij = W[i, j]\n",
    "        numer+=w_ij * (x_i - xbar) * (x_j - xbar)\n",
    "        \n",
    "\n",
    "# Compute Global Moran's I.\n",
    "I1 = (N / W.sum().sum()) * numer / denom\n",
    "\n",
    "print(f\"Manual calculation of Global Moran's I: {I1:.2f}.\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<br>\n",
    "\n",
    "Using PySAL:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PySAL calculation of Global Moran's I: 0.61.\n"
     ]
    }
   ],
   "source": [
    "\n",
    "from esda.moran import Moran\n",
    "\n",
    "I2 = Moran(gdf[\"n\"].values,  wq)\n",
    "\n",
    "print(f\"PySAL calculation of Global Moran's I: {I2.I:.2f}.\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Pretty close. \n",
    "\n",
    "As a rule of thumb:\n",
    "\n",
    "- If $I$ is above $\\frac{-1}{N - 1}$, there exists positive spatial correlation (values are clustered)\n",
    "- If $I$ is below $\\frac{-1}{N - 1}$, there exists negative spatial correlation (neighboring values are dissimilar)\n",
    "- If $I \\approx \\frac{-1}{N-1}$, there exists no spatial correlation\n",
    "\n",
    "<br>\n",
    "\n",
    "The significance of a correlation in Moran's I is determined by the z-score and p-value, assuming an expected value of $-1 / (N - 1)$. The null hypothesis states that tornadoes are spatially uncorrelated. PySAL returns the p-value of Global Moran's I under the normality assumption:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PySAL Global Moran's I p-value: 3.106619400835348e-11\n"
     ]
    }
   ],
   "source": [
    "\n",
    "print(f\"PySAL Global Moran's I p-value: {I2.p_norm}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Which suggests it is very unlikely that the observed degree of clustering of tornadoes arose by chance.  \n",
    "\n",
    "\n",
    "There are many other techniques that can be used to assess spatial autocorrelation. These will be explored in a future post. "
   ]
  }
 ],
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