{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d3e91218-da3f-4020-9bd8-d1991bf80bf5",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "# Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0a89bdb2-5257-450f-8e01-c681f23df296",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split\n",
    "import statsmodels.api as sm\n",
    "import statsmodels.formula.api as smf\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from statsmodels.stats.outliers_influence import variance_inflation_factor\n",
    "from sheltertools.utils import *\n",
    "import random\n",
    "import pickle\n",
    "random.seed(159)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1c7f4362-ba8e-4195-875b-832802e979aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(25008, 24)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shelter_data = pd.read_csv('./data/Animal_Shelter_Data.csv')\n",
    "shelter_data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e5febec8-874c-44e3-9237-dfcb2592771b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Type</th>\n",
       "      <th>Breed</th>\n",
       "      <th>Color</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Size</th>\n",
       "      <th>Date Of Birth</th>\n",
       "      <th>Impound Number</th>\n",
       "      <th>Kennel Number</th>\n",
       "      <th>Animal ID</th>\n",
       "      <th>...</th>\n",
       "      <th>Intake Subtype</th>\n",
       "      <th>Outcome Type</th>\n",
       "      <th>Outcome Subtype</th>\n",
       "      <th>Intake Condition</th>\n",
       "      <th>Outcome Condition</th>\n",
       "      <th>Intake Jurisdiction</th>\n",
       "      <th>Outcome Jurisdiction</th>\n",
       "      <th>Outcome Zip Code</th>\n",
       "      <th>Location</th>\n",
       "      <th>Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RAZOR</td>\n",
       "      <td>DOG</td>\n",
       "      <td>BOSTON TERRIER</td>\n",
       "      <td>BLACK/WHITE</td>\n",
       "      <td>Neutered</td>\n",
       "      <td>SMALL</td>\n",
       "      <td>10/29/2009</td>\n",
       "      <td>K22-043412</td>\n",
       "      <td>TRUCK</td>\n",
       "      <td>A396382</td>\n",
       "      <td>...</td>\n",
       "      <td>FIELD</td>\n",
       "      <td>RETURN TO OWNER</td>\n",
       "      <td>FLD_IDTAG</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>HEALTHY</td>\n",
       "      <td>SANTA ROSA</td>\n",
       "      <td>SANTA ROSA</td>\n",
       "      <td>95404.0</td>\n",
       "      <td>95404(38.43807, -122.71247)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>OTHER</td>\n",
       "      <td>PIGEON</td>\n",
       "      <td>GRAY/WHITE</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>SMALL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>K23-044095</td>\n",
       "      <td>TRUCK</td>\n",
       "      <td>A416206</td>\n",
       "      <td>...</td>\n",
       "      <td>FIELD</td>\n",
       "      <td>EUTHANIZE</td>\n",
       "      <td>INJ SEVERE</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>HEALTHY</td>\n",
       "      <td>SANTA ROSA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MAX</td>\n",
       "      <td>DOG</td>\n",
       "      <td>BORDER COLLIE</td>\n",
       "      <td>BLACK/TRICOLOR</td>\n",
       "      <td>Neutered</td>\n",
       "      <td>MED</td>\n",
       "      <td>03/10/2020</td>\n",
       "      <td>K23-044090</td>\n",
       "      <td>DS80</td>\n",
       "      <td>A399488</td>\n",
       "      <td>...</td>\n",
       "      <td>FIELD</td>\n",
       "      <td>RETURN TO OWNER</td>\n",
       "      <td>OVER THE COUNTER_CALL</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>PENDING</td>\n",
       "      <td>COUNTY</td>\n",
       "      <td>COUNTY</td>\n",
       "      <td>95472.0</td>\n",
       "      <td>95472(38.40179, -122.82512)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Name   Type           Breed           Color       Sex   Size  \\\n",
       "0  RAZOR    DOG  BOSTON TERRIER     BLACK/WHITE  Neutered  SMALL   \n",
       "1    NaN  OTHER          PIGEON      GRAY/WHITE   Unknown  SMALL   \n",
       "2    MAX    DOG   BORDER COLLIE  BLACK/TRICOLOR  Neutered    MED   \n",
       "\n",
       "  Date Of Birth Impound Number Kennel Number Animal ID  ... Intake Subtype  \\\n",
       "0    10/29/2009     K22-043412         TRUCK   A396382  ...          FIELD   \n",
       "1           NaN     K23-044095         TRUCK   A416206  ...          FIELD   \n",
       "2    03/10/2020     K23-044090          DS80   A399488  ...          FIELD   \n",
       "\n",
       "      Outcome Type        Outcome Subtype Intake Condition Outcome Condition  \\\n",
       "0  RETURN TO OWNER              FLD_IDTAG          UNKNOWN           HEALTHY   \n",
       "1        EUTHANIZE             INJ SEVERE          UNKNOWN           HEALTHY   \n",
       "2  RETURN TO OWNER  OVER THE COUNTER_CALL          UNKNOWN           PENDING   \n",
       "\n",
       "  Intake Jurisdiction Outcome Jurisdiction Outcome Zip Code  \\\n",
       "0          SANTA ROSA           SANTA ROSA          95404.0   \n",
       "1          SANTA ROSA                  NaN              NaN   \n",
       "2              COUNTY               COUNTY          95472.0   \n",
       "\n",
       "                      Location Count  \n",
       "0  95404(38.43807, -122.71247)     1  \n",
       "1                          NaN     1  \n",
       "2  95472(38.40179, -122.82512)     1  \n",
       "\n",
       "[3 rows x 24 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shelter_data.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b5c055c4-f474-41b8-aa87-66affdc61d4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Name', 'Type', 'Breed', 'Color', 'Sex', 'Size', 'Date Of Birth',\n",
       "       'Impound Number', 'Kennel Number', 'Animal ID', 'Intake Date',\n",
       "       'Outcome Date', 'Days in Shelter', 'Intake Type', 'Intake Subtype',\n",
       "       'Outcome Type', 'Outcome Subtype', 'Intake Condition',\n",
       "       'Outcome Condition', 'Intake Jurisdiction', 'Outcome Jurisdiction',\n",
       "       'Outcome Zip Code', 'Location', 'Count'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shelter_data.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c2bfccc-6991-4ded-a7cc-859435f28431",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "### Data Cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2124a3b-54fb-4941-89c6-93ec9f1ee109",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "In this step, we dropped all animals that had a missing size."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3d087806-16b5-4937-8444-a2293d0867f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Name                    6567\n",
       "Type                       0\n",
       "Breed                      0\n",
       "Color                      0\n",
       "Sex                        0\n",
       "Size                       0\n",
       "Date Of Birth           6206\n",
       "Impound Number             0\n",
       "Kennel Number             12\n",
       "Animal ID                  0\n",
       "Intake Date                0\n",
       "Outcome Date             159\n",
       "Days in Shelter            0\n",
       "Intake Type                0\n",
       "Intake Subtype             0\n",
       "Outcome Type             165\n",
       "Outcome Subtype          482\n",
       "Intake Condition           0\n",
       "Outcome Condition        508\n",
       "Intake Jurisdiction        0\n",
       "Outcome Jurisdiction    3508\n",
       "Outcome Zip Code        3565\n",
       "Location                3565\n",
       "Count                      0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shelter_data.dropna(subset=['Size'], inplace=True)\n",
    "shelter_data.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c2e3541-8fcf-4ef1-bc31-0d666991354a",
   "metadata": {
    "tags": [],
    "user_expressions": []
   },
   "source": [
    "## EDA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af875d60-ad11-452a-8269-b1d61275e7a1",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "### Number of Animals in the Shelter by Type"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2b8d547-248f-45b6-a1c9-55a6e99ba1d0",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "`number_of_animals_by_type` is a function we wrote for the `sheltertools` package. It calculates the number of animals per Intake Type."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "32c97a75-b569-47f4-9bf4-3359a3313257",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Intake Type      Type \n",
       "ADOPTION RETURN  DOG        292\n",
       "                 CAT        116\n",
       "                 OTHER        4\n",
       "BORN HERE        CAT         16\n",
       "                 OTHER        1\n",
       "CONFISCATE       DOG       1456\n",
       "                 CAT        245\n",
       "                 OTHER      197\n",
       "OS APPT          DOG          1\n",
       "OWNER SURRENDER  CAT       1595\n",
       "                 DOG       1414\n",
       "                 OTHER      143\n",
       "QUARANTINE       DOG        424\n",
       "                 OTHER      277\n",
       "                 CAT        118\n",
       "STRAY            DOG      10223\n",
       "                 CAT       6603\n",
       "                 OTHER     1417\n",
       "TRANSFER         DOG        258\n",
       "                 CAT        161\n",
       "                 OTHER       12\n",
       "Name: Type, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "animal_types = number_of_animals_by_type(shelter_data)\n",
    "animal_types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c8676771-7213-45dc-a2d1-dfefbc3c459d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# write animal_types result to file\n",
    "with open('computation_results/' + 'animal_types.pickle', 'wb') as f:\n",
    "    pickle.dump(animal_types, f)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a3d3d83-1d9b-4a9b-9f29-4b3fab4fe8ef",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "### Top Breeds by Animal Type"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ad2b1df-dafb-48bb-9f99-a1b7d8411842",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "#### Top Cat Breeds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f51b8c54-19ec-4f48-94e9-568a10930050",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "`plot_top_breeds` is a function we wrote for the `sheltertools` package. It plots the top breeds for a specified animal type."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "aade1f9b-8777-433a-a917-7f4f43b1cd6a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_top_breeds('CAT', shelter_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0506fb5-c2b1-4634-af30-ec4d10b6a364",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "#### Top Dog Breeds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a2315bfe-9ad5-477c-b278-0bbc2b8b0402",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_top_breeds('DOG', shelter_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62a6a3d9-f6c3-4448-91f3-ae72e24e48ed",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "### Most Common Names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "50a22707-f766-40aa-bb77-ca122ef18690",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Type</th>\n",
       "      <th>Name</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4614</th>\n",
       "      <td>DOG</td>\n",
       "      <td>BUDDY</td>\n",
       "      <td>131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6004</th>\n",
       "      <td>DOG</td>\n",
       "      <td>LUNA</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4402</th>\n",
       "      <td>DOG</td>\n",
       "      <td>BELLA</td>\n",
       "      <td>104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2291</th>\n",
       "      <td>CAT</td>\n",
       "      <td>MILO</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2197</th>\n",
       "      <td>CAT</td>\n",
       "      <td>LUCY</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>758</th>\n",
       "      <td>CAT</td>\n",
       "      <td>*LUKE</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7727</th>\n",
       "      <td>OTHER</td>\n",
       "      <td>*JESSICA</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7864</th>\n",
       "      <td>OTHER</td>\n",
       "      <td>*ROGER</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8036</th>\n",
       "      <td>OTHER</td>\n",
       "      <td>OREO</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Type      Name  size\n",
       "4614    DOG     BUDDY   131\n",
       "6004    DOG      LUNA   115\n",
       "4402    DOG     BELLA   104\n",
       "2291    CAT      MILO    21\n",
       "2197    CAT      LUCY    19\n",
       "758     CAT     *LUKE    17\n",
       "7727  OTHER  *JESSICA     9\n",
       "7864  OTHER    *ROGER     7\n",
       "8036  OTHER      OREO     5"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_names = shelter_data.groupby([\"Type\",\"Name\"], as_index=False).size()\n",
    "top_names = top_names.sort_values(by='size', ascending=False).groupby([\"Type\"]).head(3)\n",
    "top_names"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3c3036d-f4aa-44c9-ab8b-896a8e5a4562",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "From the table above, we can see that the top three most common names for dogs at the adoption centers are Buddy, Luna, and Bella. On the other hand, the top three most common names for adopted cats are Milo, Lucy, and Smokey."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "267f708d-7c8a-4a3c-ac96-1f19d86ad669",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "### Trend Line: which year has the most number of animal intakes?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c739c4d6-e8e7-40d5-81e6-af639c7c4af2",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "`plot_trend_line` is a function we wrote for the `sheltertools` package. It plots the count of animals by year."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b2308c15-8968-4d36-a671-2a16f9f09869",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_trend_line(shelter_data);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb913230-f551-4951-92c4-a5ce3c3cd222",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "### Outcomes By Species"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "fa8102d8-8763-4d80-9fe4-6bc03ad0dfa0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Type</th>\n",
       "      <th>Outcome Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DOG</td>\n",
       "      <td>RETURN TO OWNER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OTHER</td>\n",
       "      <td>EUTHANIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DOG</td>\n",
       "      <td>RETURN TO OWNER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CAT</td>\n",
       "      <td>DISPOSAL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DOG</td>\n",
       "      <td>TRANSFER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25003</th>\n",
       "      <td>CAT</td>\n",
       "      <td>ADOPTION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25004</th>\n",
       "      <td>OTHER</td>\n",
       "      <td>TRANSFER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25005</th>\n",
       "      <td>DOG</td>\n",
       "      <td>EUTHANIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25006</th>\n",
       "      <td>DOG</td>\n",
       "      <td>TRANSFER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25007</th>\n",
       "      <td>OTHER</td>\n",
       "      <td>RETURN TO OWNER</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>24973 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Type     Outcome Type\n",
       "0        DOG  RETURN TO OWNER\n",
       "1      OTHER        EUTHANIZE\n",
       "2        DOG  RETURN TO OWNER\n",
       "3        CAT         DISPOSAL\n",
       "4        DOG         TRANSFER\n",
       "...      ...              ...\n",
       "25003    CAT         ADOPTION\n",
       "25004  OTHER         TRANSFER\n",
       "25005    DOG        EUTHANIZE\n",
       "25006    DOG         TRANSFER\n",
       "25007  OTHER  RETURN TO OWNER\n",
       "\n",
       "[24973 rows x 2 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select species and outcome type\n",
    "outcome_data = shelter_data.loc[:,[\"Type\", \"Outcome Type\"]]\n",
    "outcome_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a9c57633-6a98-4edc-b108-dead9d78152d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# write animal_types result to file\n",
    "with open('computation_results/' + 'species_outcome.pickle', 'wb') as f:\n",
    "    pickle.dump(outcome_data, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4c6151e9-5c0c-4df8-9ab5-d7d962ede0a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Type            0\n",
       "Outcome Type    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Drop NA\n",
    "outcome_data.dropna(subset=['Outcome Type'], inplace=True)\n",
    "outcome_data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f90caa09-aeec-400b-aca8-c1fee9fcb298",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>percent</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Type</th>\n",
       "      <th>Outcome Type</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"7\" valign=\"top\">OTHER</th>\n",
       "      <th>TRANSFER</th>\n",
       "      <td>42.793682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EUTHANIZE</th>\n",
       "      <td>21.816387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADOPTION</th>\n",
       "      <td>21.273445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RETURN TO OWNER</th>\n",
       "      <td>9.871668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DIED</th>\n",
       "      <td>2.270484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DISPOSAL</th>\n",
       "      <td>1.727542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ESCAPED/STOLEN</th>\n",
       "      <td>0.246792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"8\" valign=\"top\">DOG</th>\n",
       "      <th>RETURN TO OWNER</th>\n",
       "      <td>50.250609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADOPTION</th>\n",
       "      <td>23.600172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TRANSFER</th>\n",
       "      <td>14.556781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EUTHANIZE</th>\n",
       "      <td>10.826292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RTOS</th>\n",
       "      <td>0.264929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DISPOSAL</th>\n",
       "      <td>0.250609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DIED</th>\n",
       "      <td>0.214807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ESCAPED/STOLEN</th>\n",
       "      <td>0.035801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"8\" valign=\"top\">CAT</th>\n",
       "      <th>ADOPTION</th>\n",
       "      <td>40.948276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TRANSFER</th>\n",
       "      <td>26.576679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EUTHANIZE</th>\n",
       "      <td>16.254537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RETURN TO OWNER</th>\n",
       "      <td>13.214610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DISPOSAL</th>\n",
       "      <td>1.780853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DIED</th>\n",
       "      <td>1.020871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RTOS</th>\n",
       "      <td>0.124773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ESCAPED/STOLEN</th>\n",
       "      <td>0.079401</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         percent\n",
       "Type  Outcome Type              \n",
       "OTHER TRANSFER         42.793682\n",
       "      EUTHANIZE        21.816387\n",
       "      ADOPTION         21.273445\n",
       "      RETURN TO OWNER   9.871668\n",
       "      DIED              2.270484\n",
       "      DISPOSAL          1.727542\n",
       "      ESCAPED/STOLEN    0.246792\n",
       "DOG   RETURN TO OWNER  50.250609\n",
       "      ADOPTION         23.600172\n",
       "      TRANSFER         14.556781\n",
       "      EUTHANIZE        10.826292\n",
       "      RTOS              0.264929\n",
       "      DISPOSAL          0.250609\n",
       "      DIED              0.214807\n",
       "      ESCAPED/STOLEN    0.035801\n",
       "CAT   ADOPTION         40.948276\n",
       "      TRANSFER         26.576679\n",
       "      EUTHANIZE        16.254537\n",
       "      RETURN TO OWNER  13.214610\n",
       "      DISPOSAL          1.780853\n",
       "      DIED              1.020871\n",
       "      RTOS              0.124773\n",
       "      ESCAPED/STOLEN    0.079401"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the proportion of species within each outcome type\n",
    "top_outcome = outcome_data.groupby([ \"Type\",\"Outcome Type\"],as_index=False).size()\n",
    "top_outcome = top_outcome.groupby([ \"Type\",\"Outcome Type\"], group_keys=False).agg({\"size\":\"sum\"}).groupby(\n",
    "    level=0,group_keys=False).apply(lambda x: 100*x/x.sum()).sort_values(\n",
    "    by=[\"Type\",\"size\", \"Outcome Type\"], ascending=[False, False, True])\n",
    "top_outcome =top_outcome.rename(columns={\"size\":\"percent\"})\n",
    "top_outcome"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2cdc9edf-c2e6-49e3-9793-ec221851ca01",
   "metadata": {},
   "outputs": [],
   "source": [
    "# write top outcome result to file\n",
    "with open('computation_results/' + 'top_outcome.pickle', 'wb') as f:\n",
    "    pickle.dump(top_outcome, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "b1e89a14-e0a9-4df1-88a0-50faa095a36e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create bar plot to visualize most common outcome type within each species\n",
    "ax = top_outcome.pivot_table(index=\"Type\", columns=\"Outcome Type\").plot(kind='bar')\n",
    "ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n",
    "ax.set_ylabel(\"% of Outcome Type\")\n",
    "ax.set_title(\"Proportion of Outcome Within Each Species\");\n",
    "fig = ax.get_figure()\n",
    "fig.set_size_inches(8, 6) \n",
    "fig.savefig('figures/' + 'Proportion_of_Outcome_Within_Each_Species', bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "354a6e96-fb83-4190-a85c-cc37f2918431",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "Adoption was the most common outcome for cats at 41%. Half of the dogs in the shelter are being returned to owner, whereas most of the other species (43%) are being transferred. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f13a4d3a-0ad1-4f16-b8ef-ff06186cc3ec",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "### Shelter Performance"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3422ad13-8c22-43ca-ad3e-454639e63ac0",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "In this section, we analyze shelter performance based on Adoption rate, Transfer rate, Return-to-owner rate, and Euthanasia Rate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "9627eb41-9e4b-4973-9605-3d097fc7cfdc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">percent</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Outcome Type</th>\n",
       "      <th>ADOPTION</th>\n",
       "      <th>DIED</th>\n",
       "      <th>DISPOSAL</th>\n",
       "      <th>ESCAPED/STOLEN</th>\n",
       "      <th>EUTHANIZE</th>\n",
       "      <th>RETURN TO OWNER</th>\n",
       "      <th>RTOS</th>\n",
       "      <th>TRANSFER</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Type</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CAT</th>\n",
       "      <td>40.948276</td>\n",
       "      <td>1.020871</td>\n",
       "      <td>1.780853</td>\n",
       "      <td>0.079401</td>\n",
       "      <td>16.254537</td>\n",
       "      <td>13.214610</td>\n",
       "      <td>0.124773</td>\n",
       "      <td>26.576679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DOG</th>\n",
       "      <td>23.600172</td>\n",
       "      <td>0.214807</td>\n",
       "      <td>0.250609</td>\n",
       "      <td>0.035801</td>\n",
       "      <td>10.826292</td>\n",
       "      <td>50.250609</td>\n",
       "      <td>0.264929</td>\n",
       "      <td>14.556781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OTHER</th>\n",
       "      <td>21.273445</td>\n",
       "      <td>2.270484</td>\n",
       "      <td>1.727542</td>\n",
       "      <td>0.246792</td>\n",
       "      <td>21.816387</td>\n",
       "      <td>9.871668</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.793682</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                percent                                                \\\n",
       "Outcome Type   ADOPTION      DIED  DISPOSAL ESCAPED/STOLEN  EUTHANIZE   \n",
       "Type                                                                    \n",
       "CAT           40.948276  1.020871  1.780853       0.079401  16.254537   \n",
       "DOG           23.600172  0.214807  0.250609       0.035801  10.826292   \n",
       "OTHER         21.273445  2.270484  1.727542       0.246792  21.816387   \n",
       "\n",
       "                                                   \n",
       "Outcome Type RETURN TO OWNER      RTOS   TRANSFER  \n",
       "Type                                               \n",
       "CAT                13.214610  0.124773  26.576679  \n",
       "DOG                50.250609  0.264929  14.556781  \n",
       "OTHER               9.871668       NaN  42.793682  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display the overall rates for each species and outcome type throughout all years\n",
    "rates_df = top_outcome.pivot_table(index=\"Type\", columns=\"Outcome Type\")\n",
    "rates_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "9fdf0f9f-9c01-4885-939a-d981b41b95b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# write shelter performance result to file\n",
    "with open('computation_results/' + 'rates_df.pickle', 'wb') as f:\n",
    "    pickle.dump(rates_df, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "73d4ca85-2adc-4346-8191-82fbf35743c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Outcome Date</th>\n",
       "      <th>Outcome Type</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-12-26</td>\n",
       "      <td>RETURN TO OWNER</td>\n",
       "      <td>2022.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-03-15</td>\n",
       "      <td>EUTHANIZE</td>\n",
       "      <td>2023.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-03-15</td>\n",
       "      <td>RETURN TO OWNER</td>\n",
       "      <td>2023.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-12-27</td>\n",
       "      <td>DISPOSAL</td>\n",
       "      <td>2022.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-03-15</td>\n",
       "      <td>TRANSFER</td>\n",
       "      <td>2023.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25003</th>\n",
       "      <td>2019-10-23</td>\n",
       "      <td>ADOPTION</td>\n",
       "      <td>2019.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25004</th>\n",
       "      <td>2018-10-10</td>\n",
       "      <td>TRANSFER</td>\n",
       "      <td>2018.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25005</th>\n",
       "      <td>2014-10-02</td>\n",
       "      <td>EUTHANIZE</td>\n",
       "      <td>2014.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25006</th>\n",
       "      <td>2020-08-20</td>\n",
       "      <td>TRANSFER</td>\n",
       "      <td>2020.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25007</th>\n",
       "      <td>2018-03-13</td>\n",
       "      <td>RETURN TO OWNER</td>\n",
       "      <td>2018.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>24973 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Outcome Date     Outcome Type    year\n",
       "0       2022-12-26  RETURN TO OWNER  2022.0\n",
       "1       2023-03-15        EUTHANIZE  2023.0\n",
       "2       2023-03-15  RETURN TO OWNER  2023.0\n",
       "3       2022-12-27         DISPOSAL  2022.0\n",
       "4       2023-03-15         TRANSFER  2023.0\n",
       "...            ...              ...     ...\n",
       "25003   2019-10-23         ADOPTION  2019.0\n",
       "25004   2018-10-10         TRANSFER  2018.0\n",
       "25005   2014-10-02        EUTHANIZE  2014.0\n",
       "25006   2020-08-20         TRANSFER  2020.0\n",
       "25007   2018-03-13  RETURN TO OWNER  2018.0\n",
       "\n",
       "[24973 rows x 3 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Add year column to the dataframe using Outcome Date\n",
    "outcome_data2 = shelter_data.loc[:,[\"Outcome Date\",\"Outcome Type\"]]\n",
    "outcome_data2[\"Outcome Date\"] = pd.to_datetime(outcome_data2['Outcome Date'])\n",
    "outcome_data2[\"year\"] = pd.DatetimeIndex(outcome_data2['Outcome Date']).year\n",
    "outcome_data2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "9548f7e3-48b9-4bd9-a075-d4750d4a64ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>Outcome Type</th>\n",
       "      <th>percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>ADOPTION</td>\n",
       "      <td>37.661113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>RETURN TO OWNER</td>\n",
       "      <td>33.511474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>TRANSFER</td>\n",
       "      <td>14.052185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>EUTHANIZE</td>\n",
       "      <td>13.297705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>DIED</td>\n",
       "      <td>0.911663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2023.0</td>\n",
       "      <td>EUTHANIZE</td>\n",
       "      <td>13.112392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>2023.0</td>\n",
       "      <td>DIED</td>\n",
       "      <td>1.008646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2023.0</td>\n",
       "      <td>DISPOSAL</td>\n",
       "      <td>1.008646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>2023.0</td>\n",
       "      <td>RTOS</td>\n",
       "      <td>0.576369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2023.0</td>\n",
       "      <td>ESCAPED/STOLEN</td>\n",
       "      <td>0.288184</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>71 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      year     Outcome Type    percent\n",
       "0   2014.0         ADOPTION  37.661113\n",
       "1   2014.0  RETURN TO OWNER  33.511474\n",
       "2   2014.0         TRANSFER  14.052185\n",
       "3   2014.0        EUTHANIZE  13.297705\n",
       "4   2014.0             DIED   0.911663\n",
       "..     ...              ...        ...\n",
       "66  2023.0        EUTHANIZE  13.112392\n",
       "67  2023.0             DIED   1.008646\n",
       "68  2023.0         DISPOSAL   1.008646\n",
       "69  2023.0             RTOS   0.576369\n",
       "70  2023.0   ESCAPED/STOLEN   0.288184\n",
       "\n",
       "[71 rows x 3 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the proportion of outcome type in each year\n",
    "yearly_rate = outcome_data2.groupby([ \"year\",\"Outcome Type\"],as_index=False).size()\n",
    "yearly_rate = yearly_rate.groupby([\"year\",\"Outcome Type\"], group_keys=False).agg({\"size\":\"sum\"}).groupby(\n",
    "    level=0,group_keys=False).apply(lambda x: 100*x/x.sum()).sort_values(\n",
    "    by=[\"year\",\"size\", \"Outcome Type\"], ascending=[True, False, True]).reset_index()\n",
    "yearly_rate =yearly_rate.rename(columns={\"size\":\"percent\"})\n",
    "yearly_rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "2d6880e5-4cc6-48df-ad75-9d7fef5b6679",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize rates\n",
    "adoption = trend_proportion(\"ADOPTION\", yearly_rate)\n",
    "euthanize = trend_proportion(\"EUTHANIZE\", yearly_rate)\n",
    "transferred = trend_proportion(\"TRANSFER\", yearly_rate)\n",
    "rto = trend_proportion(\"RETURN TO OWNER\", yearly_rate)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e25a3bf1-7bf2-4f11-96ad-3e8a3dc15b51",
   "metadata": {
    "tags": [],
    "user_expressions": []
   },
   "source": [
    "It appears that as the adoption rate declines throughout the years, the shelter chooses to transfer than animals rather than euthanizing. "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}