zipcode_data_king_county.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Population density in King County, WA per zipcode\n",
    "\n",
    "In the main notebook **EDA.ipynb** we come up with a very simple solution to give a definition of \"central neighbourhood\". We just used a list of zip codes related to Seattle found on the internet.  Here, we want to explore a more advanced way by considering provided data giving information about the population density in each zip code area. Furthermore we will use the _plotly_ library (especially the choropleth_mapbox function) to create a visualisation. \n",
    "\n",
    "## Data about population density in Washington State\n",
    "\n",
    "We can find data about the population density for each zipcode in the USA at: <br>\n",
    "[http://zipatlas.com/us/zip-code-comparison/population-density.htm](http://zipatlas.com/us/zip-code-comparison/population-density.htm) <br>\n",
    "<br>\n",
    "As we are only interested in data from King County, we can select Washington state: <br>\n",
    "[http://zipatlas.com/us/wa/zip-code-comparison/population-density.htm](http://zipatlas.com/us/wa/zip-code-comparison/population-density.htm)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data about zip codes in Washington state"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is a github repository where we can find geographical data, i.e. information about zip code boundaries for each of the 50 states: <br>\n",
    "[https://github.com/OpenDataDE/State-zip-code-GeoJSON](https://github.com/OpenDataDE/State-zip-code-GeoJSON) <br>\n",
    "<br>\n",
    "For Washington state, the url is: <br>\n",
    "[https://github.com/OpenDataDE/State-zip-code-GeoJSON/blob/master/wa_washington_zip_codes_geo.min.json](https://github.com/OpenDataDE/State-zip-code-GeoJSON/blob/master/wa_washington_zip_codes_geo.min.json)\n",
    "\n",
    "--------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To begin with, we import the required modules and take a look at the population density data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>zip_code</th>\n",
       "      <th>lat</th>\n",
       "      <th>lon</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>population</th>\n",
       "      <th>people_per_square-mile</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>98174</td>\n",
       "      <td>47.604569</td>\n",
       "      <td>-122.335359</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Washington</td>\n",
       "      <td>180</td>\n",
       "      <td>50978.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>98121</td>\n",
       "      <td>47.614743</td>\n",
       "      <td>-122.345855</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Washington</td>\n",
       "      <td>8558</td>\n",
       "      <td>17894.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>98104</td>\n",
       "      <td>47.601701</td>\n",
       "      <td>-122.327670</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Washington</td>\n",
       "      <td>13095</td>\n",
       "      <td>17156.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>98101</td>\n",
       "      <td>47.610198</td>\n",
       "      <td>-122.334555</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Washington</td>\n",
       "      <td>9010</td>\n",
       "      <td>16603.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>98102</td>\n",
       "      <td>47.634416</td>\n",
       "      <td>-122.321561</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Washington</td>\n",
       "      <td>19424</td>\n",
       "      <td>14594.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>557</th>\n",
       "      <td>99146</td>\n",
       "      <td>48.957294</td>\n",
       "      <td>-118.280382</td>\n",
       "      <td>Laurier</td>\n",
       "      <td>Washington</td>\n",
       "      <td>44</td>\n",
       "      <td>1.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>558</th>\n",
       "      <td>99356</td>\n",
       "      <td>45.845700</td>\n",
       "      <td>-120.283997</td>\n",
       "      <td>Roosevelt</td>\n",
       "      <td>Washington</td>\n",
       "      <td>175</td>\n",
       "      <td>1.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>559</th>\n",
       "      <td>98283</td>\n",
       "      <td>48.731429</td>\n",
       "      <td>-121.472545</td>\n",
       "      <td>Rockport</td>\n",
       "      <td>Washington</td>\n",
       "      <td>378</td>\n",
       "      <td>0.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>560</th>\n",
       "      <td>99105</td>\n",
       "      <td>46.870311</td>\n",
       "      <td>-118.080007</td>\n",
       "      <td>Benge</td>\n",
       "      <td>Washington</td>\n",
       "      <td>57</td>\n",
       "      <td>0.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>561</th>\n",
       "      <td>98852</td>\n",
       "      <td>48.431977</td>\n",
       "      <td>-120.815494</td>\n",
       "      <td>Stehekin</td>\n",
       "      <td>Washington</td>\n",
       "      <td>100</td>\n",
       "      <td>0.44</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>562 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     zip_code        lat         lon       city        state  population  \\\n",
       "0       98174  47.604569 -122.335359    Seattle   Washington         180   \n",
       "1       98121  47.614743 -122.345855    Seattle   Washington        8558   \n",
       "2       98104  47.601701 -122.327670    Seattle   Washington       13095   \n",
       "3       98101  47.610198 -122.334555    Seattle   Washington        9010   \n",
       "4       98102  47.634416 -122.321561    Seattle   Washington       19424   \n",
       "..        ...        ...         ...        ...          ...         ...   \n",
       "557     99146  48.957294 -118.280382    Laurier   Washington          44   \n",
       "558     99356  45.845700 -120.283997  Roosevelt   Washington         175   \n",
       "559     98283  48.731429 -121.472545   Rockport   Washington         378   \n",
       "560     99105  46.870311 -118.080007      Benge   Washington          57   \n",
       "561     98852  48.431977 -120.815494   Stehekin   Washington         100   \n",
       "\n",
       "     people_per_square-mile  \n",
       "0                  50978.44  \n",
       "1                  17894.56  \n",
       "2                  17156.75  \n",
       "3                  16603.32  \n",
       "4                  14594.02  \n",
       "..                      ...  \n",
       "557                    1.18  \n",
       "558                    1.15  \n",
       "559                    0.70  \n",
       "560                    0.69  \n",
       "561                    0.44  \n",
       "\n",
       "[562 rows x 7 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import plotly.express as px\n",
    "import json\n",
    "\n",
    "df = pd.read_csv('data/washington_pop-density_by_zipcode.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, I removed some columns from the original dataset on the website that are not neccessary for our aims and separated both lat/lon values as well as city/state values to single columns.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 562 entries, 0 to 561\n",
      "Data columns (total 7 columns):\n",
      " #   Column                  Non-Null Count  Dtype  \n",
      "---  ------                  --------------  -----  \n",
      " 0   zip_code                562 non-null    int64  \n",
      " 1   lat                     562 non-null    float64\n",
      " 2   lon                     562 non-null    float64\n",
      " 3   city                    562 non-null    object \n",
      " 4   state                   562 non-null    object \n",
      " 5   population              562 non-null    int64  \n",
      " 6   people_per_square-mile  562 non-null    float64\n",
      "dtypes: float64(3), int64(2), object(2)\n",
      "memory usage: 30.9+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>zip_code</th>\n",
       "      <th>lat</th>\n",
       "      <th>lon</th>\n",
       "      <th>population</th>\n",
       "      <th>people_per_square-mile</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>562.000000</td>\n",
       "      <td>562.000000</td>\n",
       "      <td>562.000000</td>\n",
       "      <td>562.000000</td>\n",
       "      <td>562.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>98626.556940</td>\n",
       "      <td>47.337763</td>\n",
       "      <td>-121.118412</td>\n",
       "      <td>10486.862989</td>\n",
       "      <td>1169.045979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>399.216846</td>\n",
       "      <td>0.794253</td>\n",
       "      <td>2.063541</td>\n",
       "      <td>12581.052062</td>\n",
       "      <td>3063.449197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>98001.000000</td>\n",
       "      <td>45.603287</td>\n",
       "      <td>-124.634935</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.440000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>98292.500000</td>\n",
       "      <td>46.802790</td>\n",
       "      <td>-122.576219</td>\n",
       "      <td>765.250000</td>\n",
       "      <td>16.310000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>98583.000000</td>\n",
       "      <td>47.432645</td>\n",
       "      <td>-122.147100</td>\n",
       "      <td>4054.000000</td>\n",
       "      <td>108.155000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>98989.000000</td>\n",
       "      <td>47.829806</td>\n",
       "      <td>-119.387312</td>\n",
       "      <td>19392.500000</td>\n",
       "      <td>1012.867500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>99403.000000</td>\n",
       "      <td>48.984669</td>\n",
       "      <td>-117.079512</td>\n",
       "      <td>64214.000000</td>\n",
       "      <td>50978.440000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           zip_code         lat         lon    population  \\\n",
       "count    562.000000  562.000000  562.000000    562.000000   \n",
       "mean   98626.556940   47.337763 -121.118412  10486.862989   \n",
       "std      399.216846    0.794253    2.063541  12581.052062   \n",
       "min    98001.000000   45.603287 -124.634935      1.000000   \n",
       "25%    98292.500000   46.802790 -122.576219    765.250000   \n",
       "50%    98583.000000   47.432645 -122.147100   4054.000000   \n",
       "75%    98989.000000   47.829806 -119.387312  19392.500000   \n",
       "max    99403.000000   48.984669 -117.079512  64214.000000   \n",
       "\n",
       "       people_per_square-mile  \n",
       "count              562.000000  \n",
       "mean              1169.045979  \n",
       "std               3063.449197  \n",
       "min                  0.440000  \n",
       "25%                 16.310000  \n",
       "50%                108.155000  \n",
       "75%               1012.867500  \n",
       "max              50978.440000  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's get have some insights on the zip code boundary data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Opening JSON file\n",
    "f = open('data/wa_washington_zip_codes_geo.min.json')\n",
    "\n",
    "# returns JSON object\n",
    "data = json.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['type', 'features'])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.keys()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data about zip code boundaries is stored in a nested dictionary. So, 'type' is the first key and has the value 'FeatureCollection' and the second key, 'features', is a list containing itself in total 598 entries. These entries contain all information and are (nested) lists, dictionaries etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'FeatureCollection'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['type']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'type': 'Feature',\n",
       "  'properties': {'STATEFP10': '53',\n",
       "   'ZCTA5CE10': '98822',\n",
       "   'GEOID10': '5398822',\n",
       "   'CLASSFP10': 'B5',\n",
       "   'MTFCC10': 'G6350',\n",
       "   'FUNCSTAT10': 'S',\n",
       "   'ALAND10': 1131837710,\n",
       "   'AWATER10': 5582389,\n",
       "   'INTPTLAT10': '+47.9019257',\n",
       "   'INTPTLON10': '-120.5504512',\n",
       "   'PARTFLG10': 'N'},\n",
       "  'geometry': {'type': 'Polygon',\n",
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       "     [-120.712297, 48.011709],\n",
       "     [-120.712168, 48.012286],\n",
       "     [-120.712786, 48.013186],\n",
       "     [-120.713898, 48.013607],\n",
       "     [-120.714886, 48.014198],\n",
       "     [-120.716179, 48.014971],\n",
       "     [-120.718587, 48.01534],\n",
       "     [-120.720709, 48.017216],\n",
       "     [-120.720942, 48.018428],\n",
       "     [-120.723731, 48.019096],\n",
       "     [-120.724612, 48.019902],\n",
       "     [-120.724936, 48.020199],\n",
       "     [-120.726083, 48.020868],\n",
       "     [-120.727198, 48.02283],\n",
       "     [-120.727014, 48.023567],\n",
       "     [-120.7269, 48.024505],\n",
       "     [-120.7273, 48.025814],\n",
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       "     [-120.728596, 48.029781],\n",
       "     [-120.729054, 48.031467],\n",
       "     [-120.72905, 48.032069],\n",
       "     [-120.729943, 48.033275],\n",
       "     [-120.730299, 48.033894],\n",
       "     [-120.730078, 48.034737],\n",
       "     [-120.729799, 48.035345],\n",
       "     [-120.729929, 48.035974],\n",
       "     [-120.730242, 48.037473],\n",
       "     [-120.730559, 48.038613],\n",
       "     [-120.730857, 48.038943],\n",
       "     [-120.731455, 48.039234],\n",
       "     [-120.733372, 48.039569],\n",
       "     [-120.735206, 48.039695],\n",
       "     [-120.736283, 48.040236],\n",
       "     [-120.738373, 48.041775],\n",
       "     [-120.741494, 48.043445],\n",
       "     [-120.742005, 48.044361],\n",
       "     [-120.742102, 48.046344],\n",
       "     [-120.741628, 48.047433],\n",
       "     [-120.741697, 48.047987],\n",
       "     [-120.742054, 48.048413],\n",
       "     [-120.742782, 48.049081],\n",
       "     [-120.743427, 48.049501],\n",
       "     [-120.743616, 48.050039],\n",
       "     [-120.743828, 48.050922],\n",
       "     [-120.743932, 48.051628],\n",
       "     [-120.744398, 48.052015],\n",
       "     [-120.74514, 48.052354],\n",
       "     [-120.745473, 48.052812],\n",
       "     [-120.747048, 48.056644],\n",
       "     [-120.747666, 48.05764],\n",
       "     [-120.747768, 48.058724],\n",
       "     [-120.747461, 48.060046],\n",
       "     [-120.74812, 48.062311],\n",
       "     [-120.748486, 48.063483],\n",
       "     [-120.748732, 48.066765],\n",
       "     [-120.748699, 48.067884],\n",
       "     [-120.748673, 48.068794],\n",
       "     [-120.748219, 48.070525],\n",
       "     [-120.747879, 48.071286],\n",
       "     [-120.747669, 48.072288],\n",
       "     [-120.747653, 48.07305],\n",
       "     [-120.747745, 48.073821],\n",
       "     [-120.748325, 48.075186],\n",
       "     [-120.749217, 48.076681],\n",
       "     [-120.749251, 48.077107],\n",
       "     [-120.749052, 48.078293],\n",
       "     [-120.749206, 48.078743],\n",
       "     [-120.750042, 48.079492],\n",
       "     [-120.751209, 48.080346],\n",
       "     [-120.751209, 48.080544],\n",
       "     [-120.751209, 48.081139],\n",
       "     [-120.751209, 48.081338],\n",
       "     [-120.755473, 48.083259],\n",
       "     [-120.758261, 48.083769],\n",
       "     [-120.760731, 48.084791],\n",
       "     ...],\n",
       "    [[-120.350303, 47.709061],\n",
       "     [-120.348414, 47.709551],\n",
       "     [-120.347907, 47.709803],\n",
       "     [-120.3474, 47.710003],\n",
       "     [-120.346401, 47.710399],\n",
       "     [-120.338861, 47.71339],\n",
       "     [-120.336087, 47.714491],\n",
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       "     [-120.336449, 47.714722],\n",
       "     [-120.337139, 47.714863],\n",
       "     [-120.337415, 47.714955],\n",
       "     [-120.338383, 47.715005],\n",
       "     [-120.338446, 47.715005],\n",
       "     [-120.339142, 47.715005],\n",
       "     [-120.339625, 47.715236],\n",
       "     [-120.339971, 47.715703],\n",
       "     [-120.340386, 47.716496],\n",
       "     [-120.340502, 47.716758],\n",
       "     [-120.34087, 47.717051],\n",
       "     [-120.342527, 47.717054],\n",
       "     [-120.342941, 47.717099],\n",
       "     [-120.343287, 47.717193],\n",
       "     [-120.343633, 47.71752],\n",
       "     [-120.343563, 47.717982],\n",
       "     [-120.343288, 47.718308],\n",
       "     [-120.343099, 47.718479],\n",
       "     [-120.34308, 47.718497],\n",
       "     [-120.342597, 47.719102],\n",
       "     [-120.342459, 47.719662],\n",
       "     [-120.34246, 47.720314],\n",
       "     [-120.342598, 47.720736],\n",
       "     [-120.342601, 47.72077],\n",
       "     [-120.34254, 47.720778],\n",
       "     [-120.342462, 47.72079],\n",
       "     [-120.34236, 47.720803],\n",
       "     [-120.3423, 47.720812],\n",
       "     [-120.342354, 47.721022],\n",
       "     [-120.342456, 47.721403],\n",
       "     [-120.342468, 47.721438],\n",
       "     [-120.342543, 47.721643],\n",
       "     [-120.342646, 47.721868],\n",
       "     [-120.342778, 47.722104],\n",
       "     [-120.343151, 47.722699],\n",
       "     [-120.343421, 47.723129],\n",
       "     [-120.343672, 47.723527],\n",
       "     [-120.343753, 47.723628],\n",
       "     [-120.343784, 47.723666],\n",
       "     [-120.343917, 47.723792],\n",
       "     [-120.34405, 47.723895],\n",
       "     [-120.344207, 47.723994],\n",
       "     [-120.344376, 47.72408],\n",
       "     [-120.344556, 47.724154],\n",
       "     [-120.344762, 47.724219],\n",
       "     [-120.34498, 47.724269],\n",
       "     [-120.345202, 47.724302],\n",
       "     [-120.345428, 47.724318],\n",
       "     [-120.345598, 47.724319],\n",
       "     [-120.346076, 47.724309],\n",
       "     [-120.347139, 47.72429],\n",
       "     [-120.347399, 47.724296],\n",
       "     [-120.347706, 47.724319],\n",
       "     [-120.348001, 47.724357],\n",
       "     [-120.348276, 47.724407],\n",
       "     [-120.348567, 47.724476],\n",
       "     [-120.350489, 47.725018],\n",
       "     [-120.350703, 47.725096],\n",
       "     [-120.350886, 47.725178],\n",
       "     [-120.351062, 47.725275],\n",
       "     [-120.351219, 47.725378],\n",
       "     [-120.351366, 47.725495],\n",
       "     [-120.351497, 47.725621],\n",
       "     [-120.351612, 47.72576],\n",
       "     [-120.351705, 47.7259],\n",
       "     [-120.351781, 47.726056],\n",
       "     [-120.351991, 47.726726],\n",
       "     [-120.35218, 47.727155],\n",
       "     [-120.352204, 47.727209],\n",
       "     [-120.352263, 47.727447],\n",
       "     [-120.3523, 47.727682],\n",
       "     [-120.352315, 47.727945],\n",
       "     [-120.352318, 47.728144],\n",
       "     [-120.352379, 47.729524],\n",
       "     [-120.352393, 47.729598],\n",
       "     [-120.352438, 47.729773],\n",
       "     [-120.352508, 47.729953],\n",
       "     [-120.352606, 47.730139],\n",
       "     [-120.352728, 47.730318],\n",
       "     [-120.352824, 47.730433],\n",
       "     [-120.352855, 47.730471],\n",
       "     [-120.353014, 47.73063],\n",
       "     [-120.353182, 47.730771],\n",
       "     [-120.353378, 47.73091],\n",
       "     [-120.353578, 47.731031],\n",
       "     [-120.353805, 47.731146],\n",
       "     [-120.354048, 47.731249],\n",
       "     [-120.354294, 47.731334],\n",
       "     [-120.354534, 47.731401],\n",
       "     [-120.354769, 47.731454],\n",
       "     [-120.35503, 47.731497],\n",
       "     [-120.355302, 47.731527],\n",
       "     [-120.355381, 47.731531],\n",
       "     [-120.355578, 47.731541],\n",
       "     [-120.356332, 47.731557],\n",
       "     [-120.356335, 47.73148],\n",
       "     [-120.356343, 47.73131],\n",
       "     [-120.356344, 47.731291],\n",
       "     [-120.356355, 47.731252],\n",
       "     [-120.356377, 47.731179],\n",
       "     [-120.356844, 47.731217],\n",
       "     [-120.357041, 47.731233],\n",
       "     [-120.358167, 47.731085],\n",
       "     [-120.358231, 47.731044],\n",
       "     [-120.35863, 47.730797],\n",
       "     [-120.359942, 47.730562],\n",
       "     [-120.360506, 47.730587],\n",
       "     [-120.361945, 47.730653],\n",
       "     [-120.362567, 47.730843],\n",
       "     [-120.363032, 47.731086],\n",
       "     [-120.363189, 47.731168],\n",
       "     [-120.363189, 47.731795],\n",
       "     [-120.363191, 47.733125],\n",
       "     [-120.363488, 47.734022],\n",
       "     [-120.363607, 47.734381],\n",
       "     [-120.363607, 47.735173],\n",
       "     [-120.363538, 47.73541],\n",
       "     [-120.363531, 47.735463],\n",
       "     [-120.363397, 47.735669],\n",
       "     [-120.363336, 47.735841],\n",
       "     [-120.36327, 47.735865],\n",
       "     [-120.363124, 47.735922],\n",
       "     [-120.363087, 47.735959],\n",
       "     [-120.363038, 47.736009],\n",
       "     [-120.363115, 47.736041],\n",
       "     [-120.363192, 47.736073],\n",
       "     [-120.363693, 47.736282],\n",
       "     [-120.365658, 47.737102],\n",
       "     [-120.365972, 47.737233],\n",
       "     [-120.36618, 47.737338],\n",
       "     [-120.366243, 47.737373],\n",
       "     [-120.366267, 47.737388],\n",
       "     [-120.366298, 47.737407],\n",
       "     [-120.366357, 47.737444],\n",
       "     [-120.366541, 47.737575],\n",
       "     [-120.3666, 47.737625],\n",
       "     [-120.366648, 47.737665],\n",
       "     [-120.367065, 47.738032],\n",
       "     [-120.367213, 47.738134],\n",
       "     [-120.367373, 47.738218],\n",
       "     [-120.367505, 47.738273],\n",
       "     [-120.367539, 47.738287],\n",
       "     [-120.367732, 47.738345],\n",
       "     [-120.367865, 47.738373],\n",
       "     [-120.368038, 47.738399],\n",
       "     [-120.368224, 47.738412],\n",
       "     [-120.368397, 47.738411],\n",
       "     [-120.368403, 47.738411],\n",
       "     [-120.368588, 47.738395],\n",
       "     [-120.368754, 47.738369],\n",
       "     [-120.368923, 47.738329],\n",
       "     [-120.369008, 47.738303],\n",
       "     [-120.369338, 47.738223],\n",
       "     [-120.369963, 47.738071],\n",
       "     [-120.370484, 47.737945],\n",
       "     [-120.370815, 47.737807],\n",
       "     [-120.371055, 47.737695],\n",
       "     [-120.371262, 47.737585],\n",
       "     [-120.371475, 47.737461],\n",
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       "     [-120.372041, 47.73705],\n",
       "     [-120.372319, 47.736823],\n",
       "     [-120.37232, 47.736689],\n",
       "     [-120.37232, 47.736651],\n",
       "     [-120.372323, 47.736445],\n",
       "     [-120.371934, 47.736347],\n",
       "     [-120.371317, 47.736398],\n",
       "     [-120.368868, 47.737009],\n",
       "     [-120.36881, 47.736907],\n",
       "     [-120.36879, 47.736819],\n",
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       "     [-120.368683, 47.736513],\n",
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       "     [-120.368697, 47.736398],\n",
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       "     [-120.369036, 47.736197],\n",
       "     [-120.369183, 47.736093],\n",
       "     [-120.369237, 47.736071],\n",
       "     [-120.369306, 47.736065],\n",
       "     [-120.369383, 47.736029],\n",
       "     [-120.369488, 47.735914],\n",
       "     [-120.369517, 47.735837],\n",
       "     [-120.369507, 47.735702],\n",
       "     [-120.369509, 47.73561],\n",
       "     [-120.369548, 47.735533],\n",
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       "     [-120.369651, 47.735445],\n",
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       "     [-120.370123, 47.735442],\n",
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       "     [-120.370641, 47.735026],\n",
       "     [-120.370629, 47.734925],\n",
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       "     [-120.37068, 47.734796],\n",
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       "     [-120.370916, 47.7345],\n",
       "     [-120.37092, 47.734362],\n",
       "     [-120.370886, 47.734237],\n",
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       "     [-120.370802, 47.734046],\n",
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       "      [-124.738682, 48.391589],\n",
       "      [-124.738456, 48.391476],\n",
       "      [-124.738347, 48.391356],\n",
       "      [-124.738343, 48.391239],\n",
       "      [-124.738434, 48.391166],\n",
       "      [-124.73855, 48.39115],\n",
       "      [-124.73868, 48.39118],\n",
       "      [-124.738762, 48.391206],\n",
       "      [-124.738917, 48.391166],\n",
       "      [-124.738947, 48.391158],\n",
       "      [-124.73904, 48.391125],\n",
       "      [-124.739134, 48.391146],\n",
       "      [-124.739145, 48.391135],\n",
       "      [-124.739326, 48.390972],\n",
       "      [-124.739563, 48.391081],\n",
       "      [-124.739685, 48.391223],\n",
       "      [-124.739766, 48.391199],\n",
       "      [-124.739911, 48.390995],\n",
       "      [-124.74003, 48.391047],\n",
       "      [-124.740057, 48.391159],\n",
       "      [-124.740127, 48.391158],\n",
       "      [-124.740205, 48.391071],\n",
       "      [-124.740226, 48.390999],\n",
       "      [-124.740223, 48.390914],\n",
       "      [-124.740362, 48.39088],\n",
       "      [-124.740663, 48.390812]]],\n",
       "    [[[-124.734487, 48.389732],\n",
       "      [-124.734732, 48.389751],\n",
       "      [-124.73511, 48.389889],\n",
       "      [-124.735311, 48.389953],\n",
       "      [-124.735417, 48.389992],\n",
       "      [-124.735427, 48.389929],\n",
       "      [-124.735413, 48.389857],\n",
       "      [-124.735553, 48.389864],\n",
       "      [-124.735975, 48.389898],\n",
       "      [-124.736256, 48.389948],\n",
       "      [-124.73633, 48.390046],\n",
       "      [-124.736458, 48.390044],\n",
       "      [-124.736584, 48.390024],\n",
       "      [-124.736621, 48.390019],\n",
       "      [-124.736752, 48.390112],\n",
       "      [-124.736884, 48.390217],\n",
       "      [-124.736934, 48.390311],\n",
       "      [-124.736902, 48.390388],\n",
       "      [-124.73648, 48.390682],\n",
       "      [-124.736412, 48.390755],\n",
       "      [-124.736438, 48.390823],\n",
       "      [-124.736602, 48.390843],\n",
       "      [-124.736734, 48.390944],\n",
       "      [-124.736843, 48.391059],\n",
       "      [-124.737111, 48.391055],\n",
       "      [-124.737172, 48.391122],\n",
       "      [-124.737057, 48.391196],\n",
       "      [-124.737036, 48.391259],\n",
       "      [-124.737144, 48.391325],\n",
       "      [-124.73725, 48.391364],\n",
       "      [-124.737333, 48.391416],\n",
       "      [-124.737396, 48.391532],\n",
       "      [-124.737482, 48.391661],\n",
       "      [-124.737675, 48.391847],\n",
       "      [-124.737702, 48.391955],\n",
       "      [-124.737554, 48.392065],\n",
       "      [-124.737243, 48.392196],\n",
       "      [-124.737304, 48.392271],\n",
       "      [-124.738306, 48.392216],\n",
       "      [-124.7386, 48.392261],\n",
       "      [-124.738707, 48.392322],\n",
       "      [-124.738614, 48.392351],\n",
       "      [-124.737763, 48.392363],\n",
       "      [-124.737963, 48.392419],\n",
       "      [-124.738513, 48.392456],\n",
       "      [-124.738492, 48.39251],\n",
       "      [-124.73797, 48.392639],\n",
       "      [-124.737855, 48.392668],\n",
       "      [-124.737318, 48.392685],\n",
       "      [-124.737156, 48.39271],\n",
       "      [-124.737288, 48.392816],\n",
       "      [-124.737325, 48.392892],\n",
       "      [-124.737224, 48.392988],\n",
       "      [-124.737118, 48.392981],\n",
       "      [-124.736941, 48.39292],\n",
       "      [-124.736882, 48.392908],\n",
       "      [-124.73675, 48.393121],\n",
       "      [-124.736612, 48.393191],\n",
       "      [-124.736051, 48.393321],\n",
       "      [-124.736018, 48.393218],\n",
       "      [-124.735891, 48.392945],\n",
       "      [-124.735687, 48.392764],\n",
       "      [-124.735475, 48.392713],\n",
       "      [-124.735347, 48.392737],\n",
       "      [-124.735201, 48.392888],\n",
       "      [-124.735022, 48.393116],\n",
       "      [-124.734978, 48.393215],\n",
       "      [-124.734782, 48.393268],\n",
       "      [-124.734409, 48.393287],\n",
       "      [-124.734185, 48.393245],\n",
       "      [-124.734038, 48.393148],\n",
       "      [-124.734018, 48.393135],\n",
       "      [-124.733873, 48.392998],\n",
       "      [-124.733837, 48.392945],\n",
       "      [-124.734011, 48.392911],\n",
       "      [-124.734126, 48.392873],\n",
       "      [-124.734136, 48.392819],\n",
       "      [-124.733738, 48.392775],\n",
       "      [-124.733407, 48.392659],\n",
       "      [-124.733429, 48.392618],\n",
       "      [-124.733662, 48.392605],\n",
       "      [-124.733932, 48.392651],\n",
       "      [-124.733941, 48.39257],\n",
       "      [-124.733566, 48.392521],\n",
       "      [-124.73326, 48.392463],\n",
       "      [-124.733177, 48.392406],\n",
       "      [-124.733162, 48.392325],\n",
       "      [-124.733638, 48.392232],\n",
       "      [-124.733519, 48.39218],\n",
       "      [-124.733191, 48.39214],\n",
       "      [-124.733154, 48.392078],\n",
       "      [-124.733198, 48.392005],\n",
       "      [-124.733758, 48.391997],\n",
       "      [-124.733651, 48.391931],\n",
       "      [-124.733217, 48.391874],\n",
       "      [-124.733074, 48.391805],\n",
       "      [-124.733093, 48.391674],\n",
       "      [-124.732929, 48.391645],\n",
       "      [-124.732799, 48.391615],\n",
       "      [-124.732807, 48.391165],\n",
       "      [-124.732929, 48.390948],\n",
       "      [-124.73282, 48.390837],\n",
       "      [-124.732802, 48.390666],\n",
       "      [-124.733117, 48.390639],\n",
       "      [-124.733502, 48.390664],\n",
       "      [-124.733382, 48.390558],\n",
       "      [-124.733369, 48.390505],\n",
       "      [-124.73353, 48.390448],\n",
       "      [-124.733555, 48.390447],\n",
       "      [-124.733869, 48.390443],\n",
       "      [-124.733784, 48.390372],\n",
       "      [-124.733548, 48.390281],\n",
       "      [-124.733661, 48.390172],\n",
       "      [-124.733731, 48.39009],\n",
       "      [-124.733818, 48.389994],\n",
       "      [-124.73399, 48.390013],\n",
       "      [-124.734256, 48.390158],\n",
       "      [-124.734443, 48.39016],\n",
       "      [-124.734203, 48.389979],\n",
       "      [-124.734389, 48.389945],\n",
       "      [-124.734164, 48.389854],\n",
       "      [-124.734277, 48.389753],\n",
       "      [-124.734487, 48.389732]]],\n",
       "    [[[-124.706679, 48.359154],\n",
       "      [-124.706847, 48.359292],\n",
       "      [-124.706891, 48.359326],\n",
       "      [-124.706932, 48.359362],\n",
       "      [-124.707066, 48.359472],\n",
       "      [-124.70718, 48.359623],\n",
       "      [-124.707376, 48.359863],\n",
       "      [-124.707634, 48.360156],\n",
       "      [-124.707857, 48.360292],\n",
       "      [-124.708203, 48.36057],\n",
       "      [-124.708208, 48.360575],\n",
       "      [-124.708388, 48.360748],\n",
       "      [-124.708645, 48.361014],\n",
       "      [-124.708991, 48.361288],\n",
       "      [-124.709036, 48.361449],\n",
       "      [-124.709086, 48.361749],\n",
       "      [-124.709203, 48.362004],\n",
       "      [-124.709411, 48.36228],\n",
       "      [-124.709528, 48.362526],\n",
       "      [-124.70956, 48.362561],\n",
       "      [-124.709703, 48.362716],\n",
       "      [-124.709884, 48.362799],\n",
       "      [-124.710074, 48.36285],\n",
       "      [-124.710337, 48.362999],\n",
       "      [-124.710548, 48.363095],\n",
       "      [-124.710681, 48.363206],\n",
       "      [-124.710848, 48.363464],\n",
       "      [-124.710978, 48.363489],\n",
       "      [-124.711315, 48.36348],\n",
       "      [-124.711352, 48.363682],\n",
       "      [-124.711346, 48.363803],\n",
       "      [-124.711399, 48.363906],\n",
       "      [-124.711617, 48.363898],\n",
       "      [-124.711856, 48.363935],\n",
       "      [-124.711976, 48.363969],\n",
       "      [-124.712114, 48.36394],\n",
       "      [-124.712172, 48.363932],\n",
       "      [-124.71223, 48.363925],\n",
       "      [-124.712262, 48.36392],\n",
       "      [-124.712453, 48.364003],\n",
       "      [-124.712628, 48.364131],\n",
       "      [-124.712656, 48.364152],\n",
       "      [-124.712767, 48.364205],\n",
       "      [-124.712943, 48.364121],\n",
       "      [-124.713039, 48.364021],\n",
       "      [-124.713209, 48.364063],\n",
       "      [-124.713163, 48.364163],\n",
       "      [-124.713148, 48.364329],\n",
       "      [-124.713144, 48.364509],\n",
       "      [-124.71289, 48.364603],\n",
       "      [-124.712538, 48.364775],\n",
       "      [-124.712442, 48.365078],\n",
       "      [-124.712514, 48.36523],\n",
       "      [-124.712578, 48.365273],\n",
       "      [-124.712605, 48.365291],\n",
       "      [-124.712649, 48.365421],\n",
       "      [-124.712741, 48.365487],\n",
       "      [-124.71289, 48.365503],\n",
       "      [-124.713, 48.365542],\n",
       "      [-124.713034, 48.36564],\n",
       "      [-124.712986, 48.365708],\n",
       "      [-124.712845, 48.365909],\n",
       "      [-124.71299, 48.366118],\n",
       "      [-124.713203, 48.366272],\n",
       "      [-124.713517, 48.366461],\n",
       "      [-124.714708, 48.367068],\n",
       "      [-124.714999, 48.367172],\n",
       "      [-124.715205, 48.367223],\n",
       "      [-124.715439, 48.367282],\n",
       "      [-124.715801, 48.367421],\n",
       "      [-124.716138, 48.367438],\n",
       "      [-124.716411, 48.367587],\n",
       "      [-124.71669, 48.367632],\n",
       "      [-124.716894, 48.3678],\n",
       "      [-124.716987, 48.367907],\n",
       "      [-124.717109, 48.367986],\n",
       "      [-124.717306, 48.36797],\n",
       "      [-124.717535, 48.367971],\n",
       "      [-124.717599, 48.3681],\n",
       "      [-124.717675, 48.368311],\n",
       "      [-124.717891, 48.368519],\n",
       "      [-124.718266, 48.368774],\n",
       "      [-124.718738, 48.368938],\n",
       "      [-124.719048, 48.369032],\n",
       "      [-124.719327, 48.369073],\n",
       "      [-124.719595, 48.369078],\n",
       "      [-124.719873, 48.369078],\n",
       "      [-124.720082, 48.369111],\n",
       "      [-124.720205, 48.369222],\n",
       "      [-124.72033, 48.369395],\n",
       "      [-124.720405, 48.369579],\n",
       "      [-124.720469, 48.369704],\n",
       "      [-124.720649, 48.369755],\n",
       "      [-124.720828, 48.369752],\n",
       "      [-124.721047, 48.36979],\n",
       "      [-124.721328, 48.369889],\n",
       "      [-124.721881, 48.370114],\n",
       "      [-124.72215, 48.370137],\n",
       "      [-124.722381, 48.37015],\n",
       "      [-124.722637, 48.370166],\n",
       "      [-124.723769, 48.370212],\n",
       "      [-124.724108, 48.370265],\n",
       "      [-124.724362, 48.370437],\n",
       "      [-124.724534, 48.370542],\n",
       "      [-124.724643, 48.370545],\n",
       "      [-124.724785, 48.370651],\n",
       "      [-124.724849, 48.370763],\n",
       "      [-124.724891, 48.370773],\n",
       "      [-124.724933, 48.370784],\n",
       "      [-124.724969, 48.370792],\n",
       "      [-124.725095, 48.370732],\n",
       "      [-124.725262, 48.370675],\n",
       "      [-124.72546, 48.370641],\n",
       "      [-124.725877, 48.370666],\n",
       "      [-124.726023, 48.370606],\n",
       "      [-124.726181, 48.37059],\n",
       "      [-124.726312, 48.370628],\n",
       "      [-124.726338, 48.370826],\n",
       "      [-124.726345, 48.370826],\n",
       "      [-124.726487, 48.370828],\n",
       "      [-124.726648, 48.37088],\n",
       "      [-124.726601, 48.370961],\n",
       "      [-124.726464, 48.371004],\n",
       "      [-124.726436, 48.371067],\n",
       "      [-124.726537, 48.371115],\n",
       "      [-124.726686, 48.371144],\n",
       "      [-124.726866, 48.371169],\n",
       "      [-124.726918, 48.371235],\n",
       "      [-124.72681, 48.371273],\n",
       "      [-124.726711, 48.371297],\n",
       "      [-124.726744, 48.371368],\n",
       "      [-124.726873, 48.371384],\n",
       "      [-124.727022, 48.371396],\n",
       "      [-124.727202, 48.371429],\n",
       "      [-124.727314, 48.371531],\n",
       "      [-124.727269, 48.371639],\n",
       "      [-124.727243, 48.371757],\n",
       "      [-124.727198, 48.371901],\n",
       "      [-124.727241, 48.371995],\n",
       "      [-124.727407, 48.372218],\n",
       "      [-124.72746, 48.372329],\n",
       "      [-124.727453, 48.372401],\n",
       "      [-124.727301, 48.372588],\n",
       "      [-124.727313, 48.372655],\n",
       "      [-124.727443, 48.372699],\n",
       "      [-124.727563, 48.372728],\n",
       "      [-124.727594, 48.372777],\n",
       "      [-124.727548, 48.37285],\n",
       "      [-124.727432, 48.372937],\n",
       "      [-124.727355, 48.373019],\n",
       "      [-124.727271, 48.373196],\n",
       "      [-124.727262, 48.373506],\n",
       "      [-124.727225, 48.373574],\n",
       "      [-124.727108, 48.373635],\n",
       "      [-124.726933, 48.373701],\n",
       "      [-124.726873, 48.373724],\n",
       "      [-124.726766, 48.373779],\n",
       "      [-124.726729, 48.373861],\n",
       "      [-124.726732, 48.373951],\n",
       "      [-124.726763, 48.374009],\n",
       "      [-124.726857, 48.37412],\n",
       "      [-124.727041, 48.374297],\n",
       "      [-124.727182, 48.374367],\n",
       "      [-124.727218, 48.374533],\n",
       "      [-124.727261, 48.374645],\n",
       "      [-124.727529, 48.374785],\n",
       "      [-124.727572, 48.374812],\n",
       "      [-124.727874, 48.375004],\n",
       "      [-124.728203, 48.37508],\n",
       "      [-124.728991, 48.3755],\n",
       "      [-124.729354, 48.375657],\n",
       "      [-124.729478, 48.375812],\n",
       "      [-124.729663, 48.375989],\n",
       "      [-124.729754, 48.376047],\n",
       "      [-124.730021, 48.376043],\n",
       "      [-124.730202, 48.376098],\n",
       "      [-124.730354, 48.376195],\n",
       "      [-124.730448, 48.376333],\n",
       "      [-124.730423, 48.376473],\n",
       "      [-124.73058, 48.376727],\n",
       "      [-124.730668, 48.376926],\n",
       "      [-124.730669, 48.376928],\n",
       "      [-124.730811, 48.377398],\n",
       "      [-124.730632, 48.37736],\n",
       "      [-124.730448, 48.377206],\n",
       "      [-124.730238, 48.37715],\n",
       "      [-124.730059, 48.377153],\n",
       "      [-124.730037, 48.377361],\n",
       "      [-124.729952, 48.37751],\n",
       "      [-124.730105, 48.377625],\n",
       "      [-124.730268, 48.378059],\n",
       "      [-124.730309, 48.378395],\n",
       "      [-124.730405, 48.378574],\n",
       "      [-124.730319, 48.378692],\n",
       "      [-124.730084, 48.378777],\n",
       "      [-124.729997, 48.378819],\n",
       "      [-124.73015, 48.378956],\n",
       "      [-124.730303, 48.37907],\n",
       "      [-124.730575, 48.379188],\n",
       "      [-124.730697, 48.379285],\n",
       "      [-124.730732, 48.379442],\n",
       "      [-124.730856, 48.379597],\n",
       "      [-124.730889, 48.379696],\n",
       "      [-124.73107, 48.379752],\n",
       "      [-124.731278, 48.379748],\n",
       "      [-124.73131, 48.379829],\n",
       "      [-124.731438, 48.380065],\n",
       "      [-124.731592, 48.380243],\n",
       "      [-124.731474, 48.380281],\n",
       "      [-124.731485, 48.3806],\n",
       "      [-124.731611, 48.380814],\n",
       "      [-124.731777, 48.381306],\n",
       "      [-124.731694, 48.381488],\n",
       "      [-124.731517, 48.381531],\n",
       "      [-124.731128, 48.381456],\n",
       "      [-124.730462, 48.381151],\n",
       "      [-124.729951, 48.381001],\n",
       "      [-124.729705, 48.380744],\n",
       "      [-124.729522, 48.38063],\n",
       "      [-124.729312, 48.380592],\n",
       "      [-124.729293, 48.380612],\n",
       "      [-124.729275, 48.380633],\n",
       "      [-124.729255, 48.380652],\n",
       "      [-124.729651, 48.380907],\n",
       "      [-124.729867, 48.381137],\n",
       "      [-124.730081, 48.381314],\n",
       "      [-124.730052, 48.381355],\n",
       "      [-124.729814, 48.381336],\n",
       "      [-124.729452, 48.381207],\n",
       "      [-124.7293, 48.381087],\n",
       "      [-124.729149, 48.381049],\n",
       "      [-124.729093, 48.381131],\n",
       "      [-124.729124, 48.381147],\n",
       "      [-124.729244, 48.38121],\n",
       "      [-124.729276, 48.381268],\n",
       "      [-124.729008, 48.381272],\n",
       "      [-124.729071, 48.38137],\n",
       "      [-124.729343, 48.381483],\n",
       "      [-124.729467, 48.381643],\n",
       "      [-124.729349, 48.38168],\n",
       "      [-124.729171, 48.381683],\n",
       "      [-124.729234, 48.381781],\n",
       "      [-124.729384, 48.381819],\n",
       "      [-124.729448, 48.381958],\n",
       "      [-124.729806, 48.381993],\n",
       "      [-124.729986, 48.382031],\n",
       "      [-124.730111, 48.382186],\n",
       "      [-124.730264, 48.382323],\n",
       "      [-124.730385, 48.38238],\n",
       "      [-124.730562, 48.382319],\n",
       "      [-124.730768, 48.382257],\n",
       "      [-124.730773, 48.382415],\n",
       "      [-124.730932, 48.382709],\n",
       "      [-124.731023, 48.382766],\n",
       "      [-124.730941, 48.382848],\n",
       "      [-124.730822, 48.382967],\n",
       "      [-124.730557, 48.38307],\n",
       "      [-124.730317, 48.382997],\n",
       "      [-124.730194, 48.382975],\n",
       "      [-124.730107, 48.38296],\n",
       "      [-124.72993, 48.383003],\n",
       "      [-124.729837, 48.382906],\n",
       "      [-124.729715, 48.382809],\n",
       "      [-124.729475, 48.382749],\n",
       "      [-124.729412, 48.382651],\n",
       "      [-124.729439, 48.382574],\n",
       "      [-124.729405, 48.382435],\n",
       "      [-124.729284, 48.382379],\n",
       "      [-124.729104, 48.382341],\n",
       "      [-124.728868, 48.382385],\n",
       "      [-124.728876, 48.382641],\n",
       "      [-124.728729, 48.382644],\n",
       "      [-124.72861, 48.382686],\n",
       "      [-124.728527, 48.382885],\n",
       "      [-124.728502, 48.382901],\n",
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       "      [-124.637592, 48.386585],\n",
       "      [-124.637841, 48.38646],\n",
       "      [-124.638103, 48.386268],\n",
       "      [-124.638318, 48.386251],\n",
       "      [-124.638384, 48.386246],\n",
       "      [-124.638785, 48.38619],\n",
       "      [-124.639033, 48.385593],\n",
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       "      [-124.639013, 48.38495],\n",
       "      [-124.638926, 48.384551],\n",
       "      ...]]]}}]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['features'][0:3]  # show first 3 entries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "598"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data['features'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Each zip code area contains individual _properties_ by which we can address it and has therefore its own _properties_ dictionary. For the First area it is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'STATEFP10': '53', 'ZCTA5CE10': '98822', 'GEOID10': '5398822', 'CLASSFP10': 'B5', 'MTFCC10': 'G6350', 'FUNCSTAT10': 'S', 'ALAND10': 1131837710, 'AWATER10': 5582389, 'INTPTLAT10': '+47.9019257', 'INTPTLON10': '-120.5504512', 'PARTFLG10': 'N'}\n"
     ]
    }
   ],
   "source": [
    "print(data[\"features\"][0][\"properties\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As our population data provides zip codes, we will use them to link the two datasets. Within the \"properties\" dictionary it is the key **'ZCTA5CE10'**. For the first zip code area it has the key-value '98822'. <br>\n",
    "So, the dictionary keys stay fixed, but the values may change for each zip code. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'STATEFP10': '53', 'ZCTA5CE10': '98821', 'GEOID10': '5398821', 'CLASSFP10': 'B5', 'MTFCC10': 'G6350', 'FUNCSTAT10': 'S', 'ALAND10': 4754899, 'AWATER10': 198324, 'INTPTLAT10': '+47.5497169', 'INTPTLON10': '-120.5586129', 'PARTFLG10': 'N'}\n"
     ]
    }
   ],
   "source": [
    "print(data[\"features\"][1][\"properties\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Filtering\n",
    "\n",
    "As we are only interested in zip codes belonging to King County and not all over Washington state, we reduce the data in the population density table accordingly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import King County House sales dataset\n",
    "df_KC = pd.read_csv('data/King_County_House_prices_dataset.csv')\n",
    "\n",
    "# reduce dataframe df to zip codes in King County only\n",
    "df = df[df['zip_code'].isin(df_KC['zipcode'])]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualisation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can map the datasets combined using _plotly choropleth mapbox_. A documentation about the parameters can be found here: [https://plotly.github.io/plotly.py-docs/generated/plotly.express.choropleth_mapbox.html](https://plotly.github.io/plotly.py-docs/generated/plotly.express.choropleth_mapbox.html). Note, that we assign our population density dataset to *data_frame* and our dataset containing the geographical information about the zip code areas (i.e. the polygons) to the parameter *geojson*. <br>\n",
    "To connect these data via zip code, the parameters *featureidkey* and *locations* become important as these are assigned to the corresponding zip code information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = px.choropleth_mapbox(data_frame=df,  \n",
    "                            geojson=data,\n",
    "                            featureidkey=\"properties.ZCTA5CE10\",\n",
    "                            locations=\"zip_code\",\n",
    "                            color=\"people_per_square-mile\",\n",
    "                            hover_name=\"zip_code\", \n",
    "                            hover_data=[\"city\", \"lat\", \"lon\", \"population\", \"people_per_square-mile\"],                            \n",
    "                            center={\"lat\": 47.604569, \"lon\": -122.335359},\n",
    "                            mapbox_style=\"open-street-map\", \n",
    "                            zoom=9)\n",
    "\n",
    "fig.update_layout(title=\"Population density per square mile\",\n",
    "                    legend_title=\"People per square mile\", \n",
    "                    margin={\"r\":0,\"t\":0,\"l\":0,\"b\":0})\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It appears, that we have some gaps in our data. Otherwise, it may still be ok, as these gaps are either nature reserves, airports or the harbour of Seattle. Maybe these areas do not belong to the municipal governance of King County, but for our purpose it is still fine.<br>\n",
    "<br>\n",
    "To conclude our aim to proper define a metric for \"central neighbourhood\" let's have a look at the distribution of the density and plot a histogram:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "alignmentgroup": "True",
         "bingroup": "x",
         "hovertemplate": "people_per_square-mile=%{x}<br>count=%{y}<extra></extra>",
         "legendgroup": "",
         "marker": {
          "color": "#636efa",
          "pattern": {
           "shape": ""
          }
         },
         "name": "",
         "nbinsx": 20,
         "offsetgroup": "",
         "orientation": "v",
         "showlegend": false,
         "type": "histogram",
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    "fig2 = px.histogram(df, x=\"people_per_square-mile\", nbins=20)\n",
    "fig2.update_layout(\n",
    "    title=\"Distribution of Population Density in King County\",\n",
    "    xaxis_title=\"Population density in square miles\",\n",
    "    yaxis_title=\"# zip code areas\")\n",
    "fig2.show()\n"
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   "source": [
    "Now we may define a threshold for being central in terms of population density regarding to percentiles:"
   ]
  },
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   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "p75, p80, p85, p90, p95 = df['people_per_square-mile'].quantile([0.75, 0.80, 0.85, 0.90, 0.95])"
   ]
  },
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   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
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     "name": "stdout",
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     "text": [
      "percentile 75%:  5700.135\n",
      "percentile 80%:  6476.98\n",
      "percentile 85%:  6760.4825\n",
      "percentile 90%:  7791.96\n",
      "percentile 95%:  8509.7075\n"
     ]
    }
   ],
   "source": [
    "print('percentile 75%: ', p75)\n",
    "print('percentile 80%: ', p80)\n",
    "print('percentile 85%: ', p85)\n",
    "print('percentile 90%: ', p90)\n",
    "print('percentile 95%: ', p95)"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Summary\n",
    "\n",
    "Within this notebook we have explored an alternative way to define the term 'central' by using additional data regarding the population density in Washington state, especially in King County. Using this more advanced approach we may now apply it to the main analysis in **EDA.ipynb** to gain more solid or better results for the stakeholder."
   ]
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   "source": []
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