{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "54c34b47-2a1e-4036-8d7c-83f49f250644",
   "metadata": {},
   "source": [
    "Project Assignment 3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b6aefff-3897-4ec0-b740-aaa38d8e85b3",
   "metadata": {},
   "source": [
    "MAPPING THE ESTIMATED POVERTY RATE OF THE UNITED STATES, 2023"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9827de89-eee3-41c8-9d99-31b3bb68fcb6",
   "metadata": {},
   "source": [
    "# Description:\n",
    "The 'Mapping the Estimated Poverty Rate of the United States, 2023' project aimed to analyze and visualize the poverty rate across states in the United States in 2023. Utilizing CyberGISX Notebook, this project calculated the 2023 U.S. poverty rate, comparing it to 2022's official poverty rate to discern trends. Additionally, this project identified states exceeding the average poverty rate and pinpointed the top five states with the highest poverty rates. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad7f3ea6-8310-4fdc-b0c4-faaaaede59c9",
   "metadata": {},
   "source": [
    "# Background:\n",
    "Poverty serves as a crucial socioeconomic metric, and comprehending how it is dispersed across the nation's landscapes can offer valuable insights into the economic well-being of communities and potential areas for targeted interventions. The U.S. Census Bureau announced the official poverty rate in 2022 was 11.5%, with 37.9 million people in poverty. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3f85554-8221-4349-9408-31411382ab49",
   "metadata": {},
   "source": [
    "# Read the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e52256df-f148-45f6-b0f9-6c8bdab74de1",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import os\n",
    "from geopandas import GeoSeries, GeoDataFrame, read_file, gpd\n",
    "from pandas import Series\n",
    "from matplotlib import pyplot as plt\n",
    "import IPython\n",
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "dcfb109b-d996-4353-b430-b3251d20acf3",
   "metadata": {},
   "outputs": [
    {
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
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       "      <th>ST_ABBREV</th>\n",
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       "      <th>TOTPOP_CY</th>\n",
       "      <th>HHPOP_CY</th>\n",
       "      <th>GQPOP_CY</th>\n",
       "      <th>POPDENS_CY</th>\n",
       "      <th>TOTHH_CY</th>\n",
       "      <th>AVGHHSZ_CY</th>\n",
       "      <th>...</th>\n",
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       "      <th>PERC_HSGRA</th>\n",
       "      <th>PERC_COLLE</th>\n",
       "      <th>PERC_OWNER</th>\n",
       "      <th>PERC_RENTE</th>\n",
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       "      <td>AZ</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>7427991</td>\n",
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       "      <td>159901</td>\n",
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       "  </tbody>\n",
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       "<p>3 rows × 163 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID     NAME ST_ABBREV STATE_NAME  TOTPOP_CY  HHPOP_CY  GQPOP_CY  \\\n",
       "0  01  Alabama        AL    Alabama    5098606   4970917    127689   \n",
       "1  02   Alaska        AK     Alaska     732320    702029     30291   \n",
       "2  04  Arizona        AZ    Arizona    7427991   7268090    159901   \n",
       "\n",
       "   POPDENS_CY  TOTHH_CY  AVGHHSZ_CY  ...  PERC_WORKA  PERC_NOHSD  PERC_HSGRA  \\\n",
       "0       100.7   2052801        2.42  ...   60.252665   11.124213   32.469333   \n",
       "1         1.3    272068        2.58  ...   62.370139    6.227315   28.664002   \n",
       "2        65.4   2832889        2.57  ...   58.614907    9.868275   24.253297   \n",
       "\n",
       "   PERC_COLLE  PERC_OWNER  PERC_RENTE  PERC_VACAN    Shape__Are    Shape__Len  \\\n",
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       "\n",
       "                                            geometry  \n",
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     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "total_pop = 'project/State.shp'\n",
    "total_pop = gpd.read_file(total_pop)\n",
    "total_pop[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f7077ae2-fab0-4535-94df-6a06f24c320e",
   "metadata": {},
   "outputs": [
    {
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       "      <th>ALAND</th>\n",
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       "      <td>04</td>\n",
       "      <td>AZ</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>2.943640e+11</td>\n",
       "      <td>8.558716e+08</td>\n",
       "      <td>6926281</td>\n",
       "      <td>1660.0</td>\n",
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       "      <td>13056.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.147132</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.138671</td>\n",
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       "      <td>2.9</td>\n",
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       "      <td>POLYGON ((-12138854.213 4438965.000, -12138854...</td>\n",
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      "text/plain": [
       "    STATENS GEOID STUSPS     NAME         ALAND        AWATER  B17020_001  \\\n",
       "0  01779775    01     AL  Alabama  1.311755e+11  4.591898e+09     4876863   \n",
       "1  01785533    02     AK   Alaska  1.478943e+12  2.453784e+11      719086   \n",
       "2  01779777    04     AZ  Arizona  2.943640e+11  8.558716e+08     6926281   \n",
       "\n",
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       "0      1677.0      769819     12595.0  ...    0.145042         4.8   \n",
       "1       595.0       75016      2458.0  ...    0.238761         3.9   \n",
       "2      1660.0      934911     13056.0  ...    0.147132         4.5   \n",
       "\n",
       "   C17002_c_7  C17002_c_8  C17002_c_9  C17002__16  C17002__17  C17002__18  \\\n",
       "0    0.155419         6.8    0.182787         2.7    0.104325        64.9   \n",
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       "2    0.138671         6.5    0.152310         2.9    0.094738        68.3   \n",
       "\n",
       "   C17002__19                                           geometry  \n",
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     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "poverty_pop = 'project/poverty_us_2023.shp'\n",
    "poverty_pop = gpd.read_file(poverty_pop)\n",
    "poverty_pop[:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ee085c6-c987-4d20-add0-ce2a702b6af4",
   "metadata": {},
   "source": [
    "# Data preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "167e92b9-99ab-431b-adaa-1c1ebfb5928f",
   "metadata": {},
   "source": [
    "## Rename the attributes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a460c081-3c2c-4cf6-aee7-070ffe8ea93c",
   "metadata": {},
   "outputs": [
    {
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       "      <td>11.346497</td>\n",
       "      <td>4.340564e+11</td>\n",
       "      <td>2.907243e+06</td>\n",
       "      <td>POLYGON ((-12314791.031 4439600.741, -12309722...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 163 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID   States ST_ABBREV STATE_NAME  Total_pop  HHPOP_CY  GQPOP_CY  \\\n",
       "0  01  Alabama        AL    Alabama    5098606   4970917    127689   \n",
       "1  02   Alaska        AK     Alaska     732320    702029     30291   \n",
       "2  04  Arizona        AZ    Arizona    7427991   7268090    159901   \n",
       "\n",
       "   POPDENS_CY  TOTHH_CY  AVGHHSZ_CY  ...  PERC_WORKA  PERC_NOHSD  PERC_HSGRA  \\\n",
       "0       100.7   2052801        2.42  ...   60.252665   11.124213   32.469333   \n",
       "1         1.3    272068        2.58  ...   62.370139    6.227315   28.664002   \n",
       "2        65.4   2832889        2.57  ...   58.614907    9.868275   24.253297   \n",
       "\n",
       "   PERC_COLLE  PERC_OWNER  PERC_RENTE  PERC_VACAN    Shape__Are    Shape__Len  \\\n",
       "0   37.567986   61.135901   26.511792   12.352307  1.898838e+11  3.381161e+06   \n",
       "1   42.956445   53.502922   28.488984   18.008095  8.202573e+12  8.103864e+07   \n",
       "2   43.880887   58.995037   29.658466   11.346497  4.340564e+11  2.907243e+06   \n",
       "\n",
       "                                            geometry  \n",
       "0  MULTIPOLYGON (((-9804827.172 3535998.323, -980...  \n",
       "1  MULTIPOLYGON (((-19938359.968 6674706.391, -19...  \n",
       "2  POLYGON ((-12314791.031 4439600.741, -12309722...  \n",
       "\n",
       "[3 rows x 163 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_pop = total_pop.rename(columns={'NAME':'States'})\n",
    "total_pop = total_pop.rename(columns={'TOTPOP_CY':'Total_pop'})\n",
    "total_pop[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "95168c45-58b8-42be-97a0-9f1462fa369f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STATENS</th>\n",
       "      <th>GEOID</th>\n",
       "      <th>STUSPS</th>\n",
       "      <th>States</th>\n",
       "      <th>ALAND</th>\n",
       "      <th>AWATER</th>\n",
       "      <th>B17020_001</th>\n",
       "      <th>B17020_002</th>\n",
       "      <th>Poverty_pop</th>\n",
       "      <th>B17020_004</th>\n",
       "      <th>...</th>\n",
       "      <th>C17002_c_5</th>\n",
       "      <th>C17002_c_6</th>\n",
       "      <th>C17002_c_7</th>\n",
       "      <th>C17002_c_8</th>\n",
       "      <th>C17002_c_9</th>\n",
       "      <th>C17002__16</th>\n",
       "      <th>C17002__17</th>\n",
       "      <th>C17002__18</th>\n",
       "      <th>C17002__19</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>01779775</td>\n",
       "      <td>01</td>\n",
       "      <td>AL</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>1.311755e+11</td>\n",
       "      <td>4.591898e+09</td>\n",
       "      <td>4876863</td>\n",
       "      <td>1677.0</td>\n",
       "      <td>769819</td>\n",
       "      <td>12595.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.145042</td>\n",
       "      <td>4.8</td>\n",
       "      <td>0.155419</td>\n",
       "      <td>6.8</td>\n",
       "      <td>0.182787</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.104325</td>\n",
       "      <td>64.9</td>\n",
       "      <td>0.352986</td>\n",
       "      <td>MULTIPOLYGON (((-9805779.623 3536997.578, -980...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01785533</td>\n",
       "      <td>02</td>\n",
       "      <td>AK</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>1.478943e+12</td>\n",
       "      <td>2.453784e+11</td>\n",
       "      <td>719086</td>\n",
       "      <td>595.0</td>\n",
       "      <td>75016</td>\n",
       "      <td>2458.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.238761</td>\n",
       "      <td>3.9</td>\n",
       "      <td>0.328179</td>\n",
       "      <td>5.3</td>\n",
       "      <td>0.370305</td>\n",
       "      <td>2.1</td>\n",
       "      <td>0.182863</td>\n",
       "      <td>75.1</td>\n",
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       "      <td>MULTIPOLYGON (((-19938361.670 6674706.152, -19...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01779777</td>\n",
       "      <td>04</td>\n",
       "      <td>AZ</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>2.943640e+11</td>\n",
       "      <td>8.558716e+08</td>\n",
       "      <td>6926281</td>\n",
       "      <td>1660.0</td>\n",
       "      <td>934911</td>\n",
       "      <td>13056.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.147132</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.138671</td>\n",
       "      <td>6.5</td>\n",
       "      <td>0.152310</td>\n",
       "      <td>2.9</td>\n",
       "      <td>0.094738</td>\n",
       "      <td>68.3</td>\n",
       "      <td>0.277719</td>\n",
       "      <td>POLYGON ((-12138854.213 4438965.000, -12138854...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 79 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    STATENS GEOID STUSPS   States         ALAND        AWATER  B17020_001  \\\n",
       "0  01779775    01     AL  Alabama  1.311755e+11  4.591898e+09     4876863   \n",
       "1  01785533    02     AK   Alaska  1.478943e+12  2.453784e+11      719086   \n",
       "2  01779777    04     AZ  Arizona  2.943640e+11  8.558716e+08     6926281   \n",
       "\n",
       "   B17020_002  Poverty_pop  B17020_004  ...  C17002_c_5  C17002_c_6  \\\n",
       "0      1677.0       769819     12595.0  ...    0.145042         4.8   \n",
       "1       595.0        75016      2458.0  ...    0.238761         3.9   \n",
       "2      1660.0       934911     13056.0  ...    0.147132         4.5   \n",
       "\n",
       "   C17002_c_7  C17002_c_8  C17002_c_9  C17002__16  C17002__17  C17002__18  \\\n",
       "0    0.155419         6.8    0.182787         2.7    0.104325        64.9   \n",
       "1    0.328179         5.3    0.370305         2.1    0.182863        75.1   \n",
       "2    0.138671         6.5    0.152310         2.9    0.094738        68.3   \n",
       "\n",
       "   C17002__19                                           geometry  \n",
       "0    0.352986  MULTIPOLYGON (((-9805779.623 3536997.578, -980...  \n",
       "1    0.576424  MULTIPOLYGON (((-19938361.670 6674706.152, -19...  \n",
       "2    0.277719  POLYGON ((-12138854.213 4438965.000, -12138854...  \n",
       "\n",
       "[3 rows x 79 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "poverty_pop = poverty_pop.rename(columns={'NAME': 'States'})\n",
    "poverty_pop = poverty_pop.rename(columns={'B17020_003': 'Poverty_pop'})\n",
    "poverty_pop[:3]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fe5e8a24-d017-400b-b015-73894debb3df",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['STATENS', 'GEOID', 'STUSPS', 'States', 'ALAND', 'AWATER', 'B17020_001',\n",
      "       'B17020_002', 'Poverty_pop', 'B17020_004', 'B17020_005', 'B17020_006',\n",
      "       'B17020_007', 'B17020_008', 'B17020_009', 'B17020__10', 'B17020__11',\n",
      "       'B17020__12', 'B17020__13', 'B17020__14', 'B17020__15', 'B17020__16',\n",
      "       'B17020__17', 'B17020__18', 'B17020_010', 'B17020__19', 'B17020_011',\n",
      "       'B17020__20', 'B17020_012', 'B17020__21', 'B17020_013', 'B17020__22',\n",
      "       'B17020_014', 'B17020__23', 'B17020_015', 'B17020__24', 'B17020_016',\n",
      "       'B17020__25', 'B17020_017', 'B17020__26', 'B17020_cal', 'B17020_c_1',\n",
      "       'B17020_c_2', 'B17020_c_3', 'B17020_c_4', 'B17020_c_5', 'Shape__Are',\n",
      "       'Shape__Len', 'B17020_c_6', 'B17020_c_7', 'C17002_002', 'C17002_003',\n",
      "       'C17002_004', 'C17002_005', 'C17002_006', 'C17002_007', 'C17002_008',\n",
      "       'C17002_009', 'C17002__10', 'C17002__11', 'C17002__12', 'C17002__13',\n",
      "       'C17002__14', 'C17002__15', 'C17002_cal', 'C17002_c_1', 'C17002_c_2',\n",
      "       'C17002_c_3', 'C17002_c_4', 'C17002_c_5', 'C17002_c_6', 'C17002_c_7',\n",
      "       'C17002_c_8', 'C17002_c_9', 'C17002__16', 'C17002__17', 'C17002__18',\n",
      "       'C17002__19', 'geometry'],\n",
      "      dtype='object')\n",
      "Index(['ID', 'States', 'ST_ABBREV', 'STATE_NAME', 'Total_pop', 'HHPOP_CY',\n",
      "       'GQPOP_CY', 'POPDENS_CY', 'TOTHH_CY', 'AVGHHSZ_CY',\n",
      "       ...\n",
      "       'PERC_WORKA', 'PERC_NOHSD', 'PERC_HSGRA', 'PERC_COLLE', 'PERC_OWNER',\n",
      "       'PERC_RENTE', 'PERC_VACAN', 'Shape__Are', 'Shape__Len', 'geometry'],\n",
      "      dtype='object', length=163)\n"
     ]
    }
   ],
   "source": [
    "print(poverty_pop.columns)\n",
    "print(total_pop.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf30c387-4b5d-4038-b065-df3713c5910a",
   "metadata": {},
   "source": [
    "## Create a bar chart to show poverty population of each state"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "dd8f9168-a2ec-4858-9e21-b2bfaa71ee49",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 864x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "# Create a bar chart to show poverty population for each state\n",
    "plt.figure(figsize=(12,8))\n",
    "poverty_pop.plot.bar(x='States', y='Poverty_pop', legend=None)\n",
    "plt.xlabel('States')\n",
    "plt.ylabel('Poverty Population')\n",
    "plt.title('Poverty Population by State, 2023')\n",
    "plt.xticks(rotation=90)  # Rotate x-axis labels for better visibility\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b8dabff-1197-46a7-98e8-1e6575ac85c3",
   "metadata": {},
   "source": [
    "## Join the datasets together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "39e6d2f9-6dbd-4fc6-8ee0-9a226466026c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STATENS</th>\n",
       "      <th>GEOID</th>\n",
       "      <th>STUSPS</th>\n",
       "      <th>States</th>\n",
       "      <th>ALAND</th>\n",
       "      <th>AWATER</th>\n",
       "      <th>B17020_001</th>\n",
       "      <th>B17020_002</th>\n",
       "      <th>Poverty_pop</th>\n",
       "      <th>B17020_004</th>\n",
       "      <th>...</th>\n",
       "      <th>PERC_WORKA</th>\n",
       "      <th>PERC_NOHSD</th>\n",
       "      <th>PERC_HSGRA</th>\n",
       "      <th>PERC_COLLE</th>\n",
       "      <th>PERC_OWNER</th>\n",
       "      <th>PERC_RENTE</th>\n",
       "      <th>PERC_VACAN</th>\n",
       "      <th>Shape__Are_y</th>\n",
       "      <th>Shape__Len_y</th>\n",
       "      <th>geometry_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>01779775</td>\n",
       "      <td>01</td>\n",
       "      <td>AL</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>1.311755e+11</td>\n",
       "      <td>4.591898e+09</td>\n",
       "      <td>4876863</td>\n",
       "      <td>1677.0</td>\n",
       "      <td>769819</td>\n",
       "      <td>12595.0</td>\n",
       "      <td>...</td>\n",
       "      <td>60.252665</td>\n",
       "      <td>11.124213</td>\n",
       "      <td>32.469333</td>\n",
       "      <td>37.567986</td>\n",
       "      <td>61.135901</td>\n",
       "      <td>26.511792</td>\n",
       "      <td>12.352307</td>\n",
       "      <td>1.898838e+11</td>\n",
       "      <td>3.381161e+06</td>\n",
       "      <td>MULTIPOLYGON (((-9804827.172 3535998.323, -980...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01785533</td>\n",
       "      <td>02</td>\n",
       "      <td>AK</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>1.478943e+12</td>\n",
       "      <td>2.453784e+11</td>\n",
       "      <td>719086</td>\n",
       "      <td>595.0</td>\n",
       "      <td>75016</td>\n",
       "      <td>2458.0</td>\n",
       "      <td>...</td>\n",
       "      <td>62.370139</td>\n",
       "      <td>6.227315</td>\n",
       "      <td>28.664002</td>\n",
       "      <td>42.956445</td>\n",
       "      <td>53.502922</td>\n",
       "      <td>28.488984</td>\n",
       "      <td>18.008095</td>\n",
       "      <td>8.202573e+12</td>\n",
       "      <td>8.103864e+07</td>\n",
       "      <td>MULTIPOLYGON (((-19938359.968 6674706.391, -19...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01779777</td>\n",
       "      <td>04</td>\n",
       "      <td>AZ</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>2.943640e+11</td>\n",
       "      <td>8.558716e+08</td>\n",
       "      <td>6926281</td>\n",
       "      <td>1660.0</td>\n",
       "      <td>934911</td>\n",
       "      <td>13056.0</td>\n",
       "      <td>...</td>\n",
       "      <td>58.614907</td>\n",
       "      <td>9.868275</td>\n",
       "      <td>24.253297</td>\n",
       "      <td>43.880887</td>\n",
       "      <td>58.995037</td>\n",
       "      <td>29.658466</td>\n",
       "      <td>11.346497</td>\n",
       "      <td>4.340564e+11</td>\n",
       "      <td>2.907243e+06</td>\n",
       "      <td>POLYGON ((-12314791.031 4439600.741, -12309722...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>00068085</td>\n",
       "      <td>05</td>\n",
       "      <td>AR</td>\n",
       "      <td>Arkansas</td>\n",
       "      <td>1.346608e+11</td>\n",
       "      <td>3.121950e+09</td>\n",
       "      <td>2923735</td>\n",
       "      <td>1020.0</td>\n",
       "      <td>468113</td>\n",
       "      <td>8062.0</td>\n",
       "      <td>...</td>\n",
       "      <td>59.279771</td>\n",
       "      <td>10.207925</td>\n",
       "      <td>35.205226</td>\n",
       "      <td>34.904755</td>\n",
       "      <td>57.623065</td>\n",
       "      <td>29.776736</td>\n",
       "      <td>12.600199</td>\n",
       "      <td>2.054028e+11</td>\n",
       "      <td>2.683084e+06</td>\n",
       "      <td>POLYGON ((-10503535.097 4369606.658, -10503414...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>01779778</td>\n",
       "      <td>06</td>\n",
       "      <td>CA</td>\n",
       "      <td>California</td>\n",
       "      <td>4.036718e+11</td>\n",
       "      <td>2.029357e+10</td>\n",
       "      <td>38701352</td>\n",
       "      <td>3861.0</td>\n",
       "      <td>4741175</td>\n",
       "      <td>41071.0</td>\n",
       "      <td>...</td>\n",
       "      <td>61.878353</td>\n",
       "      <td>14.095767</td>\n",
       "      <td>21.614179</td>\n",
       "      <td>46.340204</td>\n",
       "      <td>52.005259</td>\n",
       "      <td>41.329172</td>\n",
       "      <td>6.665569</td>\n",
       "      <td>6.491796e+11</td>\n",
       "      <td>8.059338e+06</td>\n",
       "      <td>MULTIPOLYGON (((-13048031.362 3865261.112, -13...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 241 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    STATENS GEOID STUSPS      States         ALAND        AWATER  B17020_001  \\\n",
       "0  01779775    01     AL     Alabama  1.311755e+11  4.591898e+09     4876863   \n",
       "1  01785533    02     AK      Alaska  1.478943e+12  2.453784e+11      719086   \n",
       "2  01779777    04     AZ     Arizona  2.943640e+11  8.558716e+08     6926281   \n",
       "3  00068085    05     AR    Arkansas  1.346608e+11  3.121950e+09     2923735   \n",
       "4  01779778    06     CA  California  4.036718e+11  2.029357e+10    38701352   \n",
       "\n",
       "   B17020_002  Poverty_pop  B17020_004  ...  PERC_WORKA  PERC_NOHSD  \\\n",
       "0      1677.0       769819     12595.0  ...   60.252665   11.124213   \n",
       "1       595.0        75016      2458.0  ...   62.370139    6.227315   \n",
       "2      1660.0       934911     13056.0  ...   58.614907    9.868275   \n",
       "3      1020.0       468113      8062.0  ...   59.279771   10.207925   \n",
       "4      3861.0      4741175     41071.0  ...   61.878353   14.095767   \n",
       "\n",
       "   PERC_HSGRA  PERC_COLLE  PERC_OWNER  PERC_RENTE  PERC_VACAN  Shape__Are_y  \\\n",
       "0   32.469333   37.567986   61.135901   26.511792   12.352307  1.898838e+11   \n",
       "1   28.664002   42.956445   53.502922   28.488984   18.008095  8.202573e+12   \n",
       "2   24.253297   43.880887   58.995037   29.658466   11.346497  4.340564e+11   \n",
       "3   35.205226   34.904755   57.623065   29.776736   12.600199  2.054028e+11   \n",
       "4   21.614179   46.340204   52.005259   41.329172    6.665569  6.491796e+11   \n",
       "\n",
       "   Shape__Len_y                                         geometry_y  \n",
       "0  3.381161e+06  MULTIPOLYGON (((-9804827.172 3535998.323, -980...  \n",
       "1  8.103864e+07  MULTIPOLYGON (((-19938359.968 6674706.391, -19...  \n",
       "2  2.907243e+06  POLYGON ((-12314791.031 4439600.741, -12309722...  \n",
       "3  2.683084e+06  POLYGON ((-10503535.097 4369606.658, -10503414...  \n",
       "4  8.059338e+06  MULTIPOLYGON (((-13048031.362 3865261.112, -13...  \n",
       "\n",
       "[5 rows x 241 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_pop.crs = poverty_pop.crs\n",
    "\n",
    "# Perform an inner join based on the 'States' column\n",
    "merged_populations = poverty_pop.merge(total_pop, on='States', how='inner')\n",
    "\n",
    "# Display the first few rows of the merged GeoDataFrame to verify the join\n",
    "merged_populations.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b530061c-86b0-432a-8a92-a5697f0d1937",
   "metadata": {},
   "source": [
    "## Create a new attibute and calculate poverty rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c2cb889d-7432-4488-8b6d-f835c163b017",
   "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>STATENS</th>\n",
       "      <th>GEOID</th>\n",
       "      <th>STUSPS</th>\n",
       "      <th>States</th>\n",
       "      <th>ALAND</th>\n",
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       "      <th>0</th>\n",
       "      <td>01779775</td>\n",
       "      <td>01</td>\n",
       "      <td>AL</td>\n",
       "      <td>Alabama</td>\n",
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       "      <td>4876863</td>\n",
       "      <td>1677.0</td>\n",
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       "      <td>3.381161e+06</td>\n",
       "      <td>MULTIPOLYGON (((-9804827.172 3535998.323, -980...</td>\n",
       "      <td>15.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01785533</td>\n",
       "      <td>02</td>\n",
       "      <td>AK</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>1.478943e+12</td>\n",
       "      <td>2.453784e+11</td>\n",
       "      <td>719086</td>\n",
       "      <td>595.0</td>\n",
       "      <td>75016</td>\n",
       "      <td>2458.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6.227315</td>\n",
       "      <td>28.664002</td>\n",
       "      <td>42.956445</td>\n",
       "      <td>53.502922</td>\n",
       "      <td>28.488984</td>\n",
       "      <td>18.008095</td>\n",
       "      <td>8.202573e+12</td>\n",
       "      <td>8.103864e+07</td>\n",
       "      <td>MULTIPOLYGON (((-19938359.968 6674706.391, -19...</td>\n",
       "      <td>10.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01779777</td>\n",
       "      <td>04</td>\n",
       "      <td>AZ</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>2.943640e+11</td>\n",
       "      <td>8.558716e+08</td>\n",
       "      <td>6926281</td>\n",
       "      <td>1660.0</td>\n",
       "      <td>934911</td>\n",
       "      <td>13056.0</td>\n",
       "      <td>...</td>\n",
       "      <td>9.868275</td>\n",
       "      <td>24.253297</td>\n",
       "      <td>43.880887</td>\n",
       "      <td>58.995037</td>\n",
       "      <td>29.658466</td>\n",
       "      <td>11.346497</td>\n",
       "      <td>4.340564e+11</td>\n",
       "      <td>2.907243e+06</td>\n",
       "      <td>POLYGON ((-12314791.031 4439600.741, -12309722...</td>\n",
       "      <td>12.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>00068085</td>\n",
       "      <td>05</td>\n",
       "      <td>AR</td>\n",
       "      <td>Arkansas</td>\n",
       "      <td>1.346608e+11</td>\n",
       "      <td>3.121950e+09</td>\n",
       "      <td>2923735</td>\n",
       "      <td>1020.0</td>\n",
       "      <td>468113</td>\n",
       "      <td>8062.0</td>\n",
       "      <td>...</td>\n",
       "      <td>10.207925</td>\n",
       "      <td>35.205226</td>\n",
       "      <td>34.904755</td>\n",
       "      <td>57.623065</td>\n",
       "      <td>29.776736</td>\n",
       "      <td>12.600199</td>\n",
       "      <td>2.054028e+11</td>\n",
       "      <td>2.683084e+06</td>\n",
       "      <td>POLYGON ((-10503535.097 4369606.658, -10503414...</td>\n",
       "      <td>15.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>01779778</td>\n",
       "      <td>06</td>\n",
       "      <td>CA</td>\n",
       "      <td>California</td>\n",
       "      <td>4.036718e+11</td>\n",
       "      <td>2.029357e+10</td>\n",
       "      <td>38701352</td>\n",
       "      <td>3861.0</td>\n",
       "      <td>4741175</td>\n",
       "      <td>41071.0</td>\n",
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       "      <td>6.491796e+11</td>\n",
       "      <td>8.059338e+06</td>\n",
       "      <td>MULTIPOLYGON (((-13048031.362 3865261.112, -13...</td>\n",
       "      <td>11.89</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 242 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    STATENS GEOID STUSPS      States         ALAND        AWATER  B17020_001  \\\n",
       "0  01779775    01     AL     Alabama  1.311755e+11  4.591898e+09     4876863   \n",
       "1  01785533    02     AK      Alaska  1.478943e+12  2.453784e+11      719086   \n",
       "2  01779777    04     AZ     Arizona  2.943640e+11  8.558716e+08     6926281   \n",
       "3  00068085    05     AR    Arkansas  1.346608e+11  3.121950e+09     2923735   \n",
       "4  01779778    06     CA  California  4.036718e+11  2.029357e+10    38701352   \n",
       "\n",
       "   B17020_002  Poverty_pop  B17020_004  ...  PERC_NOHSD  PERC_HSGRA  \\\n",
       "0      1677.0       769819     12595.0  ...   11.124213   32.469333   \n",
       "1       595.0        75016      2458.0  ...    6.227315   28.664002   \n",
       "2      1660.0       934911     13056.0  ...    9.868275   24.253297   \n",
       "3      1020.0       468113      8062.0  ...   10.207925   35.205226   \n",
       "4      3861.0      4741175     41071.0  ...   14.095767   21.614179   \n",
       "\n",
       "   PERC_COLLE  PERC_OWNER  PERC_RENTE  PERC_VACAN  Shape__Are_y  Shape__Len_y  \\\n",
       "0   37.567986   61.135901   26.511792   12.352307  1.898838e+11  3.381161e+06   \n",
       "1   42.956445   53.502922   28.488984   18.008095  8.202573e+12  8.103864e+07   \n",
       "2   43.880887   58.995037   29.658466   11.346497  4.340564e+11  2.907243e+06   \n",
       "3   34.904755   57.623065   29.776736   12.600199  2.054028e+11  2.683084e+06   \n",
       "4   46.340204   52.005259   41.329172    6.665569  6.491796e+11  8.059338e+06   \n",
       "\n",
       "                                          geometry_y  Poverty_rate  \n",
       "0  MULTIPOLYGON (((-9804827.172 3535998.323, -980...         15.10  \n",
       "1  MULTIPOLYGON (((-19938359.968 6674706.391, -19...         10.24  \n",
       "2  POLYGON ((-12314791.031 4439600.741, -12309722...         12.59  \n",
       "3  POLYGON ((-10503535.097 4369606.658, -10503414...         15.32  \n",
       "4  MULTIPOLYGON (((-13048031.362 3865261.112, -13...         11.89  \n",
       "\n",
       "[5 rows x 242 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Perform the division and create a new column 'Poverty_Rate'\n",
    "merged_populations['Poverty_rate'] = round(merged_populations['Poverty_pop'] / merged_populations['Total_pop'] * 100,2)\n",
    "\n",
    "# Display the first few rows of the GeoDataFrame to verify the new column\n",
    "\n",
    "merged_populations_gdf = gpd.GeoDataFrame(merged_populations, geometry='geometry_y')\n",
    "merged_populations_gdf.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd58a7c3-b5fd-4e0a-8453-30b88c0c30bb",
   "metadata": {},
   "source": [
    "## Calculate average poverty rate of US and compare it with the official poverty rate in 2022"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f73e2e47-d70a-44a9-8fb9-eafd3b4c301b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Poverty Rate for the United States: 11.86 %.\n",
      "The poverty rate increases by 0.36 percentage from 2022 to 2023.\n",
      "This is higher than the 2022 poverty rate.\n"
     ]
    }
   ],
   "source": [
    "# To calculate mean poverty rate of the United States in 2023 and compare it with 2023\n",
    "mean_2023_poverty_rate = round(merged_populations_gdf['Poverty_rate'].mean(),2)\n",
    "print(\"Mean Poverty Rate for the United States:\", mean_2023_poverty_rate,\"%.\")\n",
    "\n",
    "poverty_rate_2022 = 11.5\n",
    "\n",
    "# Calculate the change in poverty rate from 2022 to 2023\n",
    "poverty_rate_change = mean_2023_poverty_rate - poverty_rate_2022\n",
    "\n",
    "# Compare the change with the given threshold\n",
    "if poverty_rate_change > 0:\n",
    "    print(f\"The poverty rate increases by {poverty_rate_change:.2f} percentage from 2022 to 2023.\")\n",
    "    print(\"This is higher than the 2022 poverty rate.\")\n",
    "elif poverty_rate_change < 0:\n",
    "    print(f\"The poverty rate decreases by {-poverty_rate_change:.2f} percentage from 2022 to 2023.\")\n",
    "    print(\"This is lower than the 2022 poverty rate.\")\n",
    "else:\n",
    "    print(\"The poverty rate remains the same from 2022 to 2023.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46088941-7abd-4295-a717-df496120d574",
   "metadata": {},
   "source": [
    "# Mapping and Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27032672-8d31-4dba-afc2-fc8626fdcb54",
   "metadata": {},
   "source": [
    "## Continental US poverty rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "45cf2638-9913-4012-85db-934a7e10f3b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Remove rows for Alaska (AK) and Hawaii (HI)\n",
    "continental_us_gdf = merged_populations_gdf[~merged_populations_gdf['STUSPS'].isin(['AK', 'HI'])]\n",
    "\n",
    "continental_us_gdf = continental_us_gdf.to_crs(epsg=5070)\n",
    "fig, ax = plt.subplots(1, 1, figsize=(12, 8))\n",
    "\n",
    "# Plot the GeoDataFrame using 'Poverty_Rate' column for coloring\n",
    "continental_us_gdf.plot(column='Poverty_rate', cmap='YlOrRd', linewidth=0.5, edgecolor='0.8', \n",
    "                        legend=True, ax=ax, legend_kwds={'label': \"Poverty Rate (%)\", 'orientation': \"vertical\"})\n",
    "\n",
    "# Annotate states with poverty rate greater than 14%\n",
    "high_poverty_states = continental_us_gdf[continental_us_gdf['Poverty_rate'] > 11.86]\n",
    "for x, y, label in zip(high_poverty_states.geometry.centroid.x, high_poverty_states.geometry.centroid.y, high_poverty_states['STUSPS']):\n",
    "    ax.text(x, y, label, fontsize=10, ha='center', va='center')\n",
    "\n",
    "# Set a clear title for the map\n",
    "ax.set_title('Poverty Rate by State, 2023', fontsize=16)\n",
    "\n",
    "# Display the map\n",
    "plt.axis('off') \n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca8b9944-b89b-49cc-86e0-71595abd7806",
   "metadata": {},
   "source": [
    "## Alaska poverty rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "46b36e56-84a9-4ba6-8710-9a539a16f0b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Filter rows for Alaska (AK)\n",
    "alaska_gdf = merged_populations_gdf[merged_populations_gdf['STUSPS'] == 'AK'].copy()  # Use the copy() method\n",
    "\n",
    "# Round the 'Poverty_rate' column to 2 decimal points\n",
    "alaska_gdf['Poverty_rate_rounded'] = alaska_gdf['Poverty_rate'].round(2)\n",
    "\n",
    "# Create a plot for Alaska with Alaska Albers Equal Area Conic projection (EPSG:3338)\n",
    "fig, ax = plt.subplots(1, 1, figsize=(12, 8))\n",
    "alaska_gdf = alaska_gdf.to_crs(epsg=3338)  # Change the projection to Alaska Albers Equal Area Conic\n",
    "\n",
    "# Plot the GeoDataFrame for Alaska using 'Poverty_rate_rounded' column for labeling\n",
    "alaska_gdf.plot(column='Poverty_rate_rounded', cmap='YlOrRd', linewidth=0.8, edgecolor='0.8', \n",
    "                legend=False, ax=ax)\n",
    "\n",
    "# Add labels with rounded poverty rates and percentage sign for each state\n",
    "for x, y, label in zip(alaska_gdf.geometry.centroid.x, alaska_gdf.geometry.centroid.y, alaska_gdf['Poverty_rate_rounded']):\n",
    "    ax.text(x, y, f\"{label}%\", fontsize=10, ha='center', va='center')\n",
    "\n",
    "# Set a clear title for the map\n",
    "ax.set_title('Poverty Rate of Alaska, 2023', fontsize=16)\n",
    "\n",
    "# Display the map without axis\n",
    "plt.axis('off') \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36b3d99d-bf0b-41d1-8c01-f018c6b36f43",
   "metadata": {},
   "source": [
    "## Hawaii poverty rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "6d5d87c0-fb09-48cf-a3b3-a9b307a71fe9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Filter rows for Hawaii (HI)\n",
    "hawaii_gdf = merged_populations_gdf[merged_populations_gdf['STUSPS'] == 'HI'].copy()  # Use the copy() method\n",
    "\n",
    "# Round the 'Poverty_rate' column to 2 decimal points\n",
    "hawaii_gdf['Poverty_rate_rounded'] = hawaii_gdf['Poverty_rate'].round(2)\n",
    "\n",
    "# Create a plot for Hawaii with Hawaii Albers Equal Area Conic projection (EPSG:102007)\n",
    "fig, ax = plt.subplots(1, 1, figsize=(8, 8))\n",
    "hawaii_gdf = hawaii_gdf.to_crs(epsg=32604)  # Change the projection to Hawaii Albers Equal Area Conic\n",
    "\n",
    "# Plot the GeoDataFrame for Hawaii using 'Poverty_rate_rounded' column for labeling\n",
    "hawaii_gdf.plot(column='Poverty_rate_rounded', cmap='YlOrRd', linewidth=0.8, edgecolor='0.8', \n",
    "                legend=False, ax=ax)\n",
    "\n",
    "# Add labels with rounded poverty rates and percentage sign for Hawaii\n",
    "for x, y, label in zip(hawaii_gdf.geometry.centroid.x, hawaii_gdf.geometry.centroid.y, hawaii_gdf['Poverty_rate_rounded']):\n",
    "    ax.text(x, y, f\"{label}%\", fontsize=10, ha='center', va='center')\n",
    "\n",
    "# Set a clear title for the map\n",
    "ax.set_title('Poverty Rate of Hawaii, 2023', fontsize=16)\n",
    "\n",
    "# Display the map without axis\n",
    "plt.axis('off') \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f31cbcd-1b28-43e3-ba74-a40b1846cf21",
   "metadata": {},
   "source": [
    "## Top five states with highest poverty rate in the U.S."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2dc36df9-cb46-4e62-ba90-e402abc9a493",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Sort the GeoDataFrame by 'Poverty_rate' column in descending order and select the top 5 states\n",
    "top_5_states = merged_populations_gdf.sort_values(by='Poverty_rate', ascending=False).head(5)\n",
    "\n",
    "# Create the choropleth map for the top 5 states with highest poverty rates\n",
    "continental_us_gdf = continental_us_gdf.to_crs(epsg=5070)\n",
    "fig, ax = plt.subplots(1, 1, figsize=(12, 8))\n",
    "\n",
    "# Plot the top 5 states using 'Poverty_rate' column for coloring\n",
    "top_5_states.plot(column='Poverty_rate', cmap='YlOrRd', linewidth=0.8, edgecolor='0.8', \n",
    "                  legend=True, ax=ax, legend_kwds={'label': \"Poverty Rate (%)\", 'orientation': \"horizontal\"})\n",
    "\n",
    "# Add labels and rounded poverty rates for the top 5 states\n",
    "for x, y, label, rate in zip(top_5_states.geometry.centroid.x, top_5_states.geometry.centroid.y, top_5_states['States'], top_5_states['Poverty_rate']):\n",
    "    ax.text(x, y, f\"{label}\\nPoverty Rate: {round(rate, 2)}%\", fontsize=8, ha='center', va='center')\n",
    "\n",
    "# Set a clear title for the map\n",
    "ax.set_title('Top 5 States with Highest Poverty Rate, 2023', fontsize=16)\n",
    "\n",
    "# Display the map\n",
    "plt.axis('off') \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbdb2128-1a6e-446b-ac65-2c03bb7a1b13",
   "metadata": {},
   "source": [
    "# Results:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e3c2d56-c4fa-41bb-b023-6d31ba1edf19",
   "metadata": {},
   "source": [
    "## The estimated average poverty rate in 2023 is 11.86%, increased by 0.36 percentage compared to the official poverty rate of the United States in 2022."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f67df795-f39b-4eef-817c-5abbeb76799b",
   "metadata": {},
   "source": [
    "## There are 23 states in the United States have a poverty rate higher than the estimated average poverty rate. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dca5828a-45e3-468a-82c5-c5d25bf8ed60",
   "metadata": {},
   "source": [
    "## Most of the states in the southern part and eastern part of the United States have a poverty rate higher than the estimated average poverty rate."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e75bfc0a-e01c-496b-91dd-10f8341bb655",
   "metadata": {},
   "source": [
    "## The top five states with highest poverty rate are New Mexico, Louisiana, Mississippi, Kentucky and West Virgina. These states might require increased social welfare programs and economic development initiatives from the government to address the rising poverty rates. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6f81caaf-ae0d-4741-a64e-dcdd43b69295",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3-0.8.0",
   "language": "python",
   "name": "python3-0.8.0"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}