New_BMI.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "4e106545-5510-47bf-82df-71a43dd99e14",
   "metadata": {},
   "source": [
    "## Step 1: Import Libraries and Load the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "id": "2b577734-5c8f-400b-8133-e4531d287f2e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   SchoolYear NameHospital     Sex  EpiUnderweight  EpiHealthyWeight  \\\n",
      "0        2001      Borders  Female               2               334   \n",
      "1        2001      Borders    Male               5               301   \n",
      "2        2001      Lothian  Female              12               728   \n",
      "3        2001      Lothian    Male              17               681   \n",
      "4        2001         Fife  Female              17              1361   \n",
      "\n",
      "   EpiOverweight  EpiObese  EpiOverweightAndObese  ValidCounts  UnvalidCounts  \\\n",
      "0             54        28                     82          418             82   \n",
      "1             63        42                    105          411            105   \n",
      "2            133       106                    239          979            239   \n",
      "3            124       114                    238          936            238   \n",
      "4            231       155                    386         1764            386   \n",
      "\n",
      "   TotalCounts  \n",
      "0          500  \n",
      "1          516  \n",
      "2         1218  \n",
      "3         1174  \n",
      "4         2150  \n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 516 entries, 0 to 515\n",
      "Data columns (total 11 columns):\n",
      " #   Column                 Non-Null Count  Dtype \n",
      "---  ------                 --------------  ----- \n",
      " 0   SchoolYear             516 non-null    int64 \n",
      " 1   NameHospital           516 non-null    object\n",
      " 2   Sex                    516 non-null    object\n",
      " 3   EpiUnderweight         516 non-null    int64 \n",
      " 4   EpiHealthyWeight       516 non-null    int64 \n",
      " 5   EpiOverweight          516 non-null    int64 \n",
      " 6   EpiObese               516 non-null    int64 \n",
      " 7   EpiOverweightAndObese  516 non-null    int64 \n",
      " 8   ValidCounts            516 non-null    int64 \n",
      " 9   UnvalidCounts          516 non-null    int64 \n",
      " 10  TotalCounts            516 non-null    int64 \n",
      "dtypes: int64(9), object(2)\n",
      "memory usage: 44.5+ KB\n",
      "None\n",
      "        SchoolYear  EpiUnderweight  EpiHealthyWeight  EpiOverweight  \\\n",
      "count   516.000000      516.000000         516.00000     516.000000   \n",
      "mean   2013.383721       21.742248        1304.72093     208.102713   \n",
      "std       5.947672       25.207054        1103.90967     167.192486   \n",
      "min    2001.000000        0.000000           7.00000       0.000000   \n",
      "25%    2009.000000        3.000000         421.75000      66.750000   \n",
      "50%    2013.500000       13.000000        1158.50000     196.000000   \n",
      "75%    2018.000000       30.000000        1946.25000     292.000000   \n",
      "max    2023.000000      137.000000        4623.00000     696.000000   \n",
      "\n",
      "         EpiObese  EpiOverweightAndObese  ValidCounts  UnvalidCounts  \\\n",
      "count  516.000000             516.000000   516.000000     516.000000   \n",
      "mean   175.563953             383.666667  1710.129845     383.666667   \n",
      "std    147.842378             313.523071  1433.191567     313.523071   \n",
      "min      2.000000               2.000000    10.000000       2.000000   \n",
      "25%     52.000000             120.500000   549.000000     120.500000   \n",
      "50%    160.500000             350.500000  1558.500000     350.500000   \n",
      "75%    243.000000             537.000000  2523.250000     537.000000   \n",
      "max    737.000000            1433.000000  6150.000000    1433.000000   \n",
      "\n",
      "       TotalCounts  \n",
      "count   516.000000  \n",
      "mean   2093.796512  \n",
      "std    1743.889989  \n",
      "min      12.000000  \n",
      "25%     669.500000  \n",
      "50%    1904.500000  \n",
      "75%    3038.750000  \n",
      "max    7583.000000  \n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.decomposition import PCA\n",
    "import statsmodels.formula.api as smf\n",
    "import statsmodels.api as sm\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "df = pd.read_csv(\"/Users/sandeepsrinivasdwaram/Desktop/BMIData.csv\")\n",
    "\n",
    "print(df.head())\n",
    "print(df.info())\n",
    "print(df.describe())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "047520bb-aa40-4ca1-b868-6d3f457d7f09",
   "metadata": {},
   "source": [
    "## Step 2: Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "id": "aca8a2ec-af55-4e5f-9a40-72df5e582020",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SchoolYear               0\n",
      "NameHospital             0\n",
      "Sex                      0\n",
      "EpiUnderweight           0\n",
      "EpiHealthyWeight         0\n",
      "EpiOverweight            0\n",
      "EpiObese                 0\n",
      "EpiOverweightAndObese    0\n",
      "ValidCounts              0\n",
      "UnvalidCounts            0\n",
      "TotalCounts              0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(df.isnull().sum())\n",
    "numeric_cols = df.select_dtypes(include=[np.number]).columns\n",
    "df[numeric_cols] = df[numeric_cols].fillna(df[numeric_cols].median())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "55fdf36a-4cfd-49a6-9b17-69e6c986d8e4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Duplicate rows: 0\n"
     ]
    }
   ],
   "source": [
    "print(\"Duplicate rows:\", df.duplicated().sum())\n",
    "df = df.drop_duplicates()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6799e1a-7660-4a5d-ac3a-e39bb1e1577f",
   "metadata": {},
   "source": [
    "## Step 3: Create Proportional Variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "5b21603e-0199-42c0-80db-896f79d6ece4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   PropUnderweight  PropHealthyWeight  PropOverweight  PropObese  \\\n",
      "0         0.004785           0.799043        0.129187   0.066986   \n",
      "1         0.012165           0.732360        0.153285   0.102190   \n",
      "2         0.012257           0.743616        0.135853   0.108274   \n",
      "3         0.018162           0.727564        0.132479   0.121795   \n",
      "4         0.009637           0.771542        0.130952   0.087868   \n",
      "\n",
      "   PropOverweightAndObese  \n",
      "0                0.196172  \n",
      "1                0.255474  \n",
      "2                0.244127  \n",
      "3                0.254274  \n",
      "4                0.218821  \n"
     ]
    }
   ],
   "source": [
    "# Create new columns for proportions based on ValidCounts\n",
    "df['PropUnderweight'] = df['EpiUnderweight'] / df['ValidCounts']\n",
    "df['PropHealthyWeight'] = df['EpiHealthyWeight'] / df['ValidCounts']\n",
    "df['PropOverweight'] = df['EpiOverweight'] / df['ValidCounts']\n",
    "df['PropObese'] = df['EpiObese'] / df['ValidCounts']\n",
    "df['PropOverweightAndObese'] = df['EpiOverweightAndObese'] / df['ValidCounts']\n",
    "print(df[['PropUnderweight', 'PropHealthyWeight', 'PropOverweight', 'PropObese', 'PropOverweightAndObese']].head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2684bfb8-8d96-4ca6-a58b-a11eff0a4419",
   "metadata": {},
   "source": [
    "These new columns allow you to compare hospitals on a common scale, regardless of how many children they serve."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "020b5fd6-89b4-40bc-a74c-6f958943082d",
   "metadata": {},
   "source": [
    "## Step 4: Exploratory Data Analysis (EDA) – Summary Statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "9020090b-f5e4-440a-9448-0847ec65e201",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       PropUnderweight  PropHealthyWeight  PropOverweight   PropObese\n",
      "count       516.000000         516.000000      516.000000  516.000000\n",
      "mean          0.011183           0.757434        0.125710    0.105673\n",
      "std           0.007941           0.031983        0.020968    0.021884\n",
      "min           0.000000           0.583333        0.000000    0.046875\n",
      "25%           0.005970           0.744919        0.114445    0.092561\n",
      "50%           0.009811           0.761176        0.123808    0.101467\n",
      "75%           0.014950           0.776438        0.135451    0.114766\n",
      "max           0.050000           0.840708        0.244898    0.250000\n"
     ]
    }
   ],
   "source": [
    "print(df[['PropUnderweight', 'PropHealthyWeight', 'PropOverweight', 'PropObese']].describe())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "535b92e8-8360-4cf8-9417-e9af312cad2d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['PropUnderweight', 'PropHealthyWeight', 'PropOverweight', 'PropObese']].hist(bins=20, figsize=(12, 8), edgecolor='black')\n",
    "plt.suptitle(\"Distribution of BMI Proportions\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3de7a204-edf5-43d6-93dc-3cb36d7377f8",
   "metadata": {},
   "source": [
    "This helps you see the average trends and differences in the BMI categories. The histo show that most kids (70–80%) are at a healthy weight across hospitals, while around 10% are overweight and another 10% are obese. Very few kids (0–2%) are underweight. This pattern highlights the issue of overweight and obesity, especially in hospitals where these numbers are much higher than usual."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f070601e-a3ac-4b48-bf0e-4ef841f1ad1f",
   "metadata": {},
   "source": [
    "## Step 5: Analyze Trends Over Time (SchoolYear)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "36487e7c-bf2a-4ee2-b06a-4cf17d7a6959",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    SchoolYear  PropUnderweight  PropHealthyWeight  PropOverweight  PropObese\n",
      "0         2001         0.014237           0.755882        0.130036   0.099844\n",
      "1         2002         0.016210           0.748644        0.130714   0.104432\n",
      "2         2003         0.012998           0.758594        0.130420   0.097988\n",
      "3         2004         0.012765           0.742699        0.122960   0.121576\n",
      "4         2005         0.012955           0.750621        0.130682   0.105742\n",
      "5         2006         0.014303           0.764450        0.120995   0.100253\n",
      "6         2007         0.016162           0.771667        0.118039   0.094132\n",
      "7         2008         0.017211           0.773590        0.115641   0.093558\n",
      "8         2009         0.013772           0.761248        0.121190   0.103790\n",
      "9         2010         0.014889           0.761986        0.123864   0.099261\n",
      "10        2011         0.010902           0.760933        0.125219   0.102946\n",
      "11        2012         0.010541           0.769212        0.119813   0.100433\n",
      "12        2013         0.009514           0.755249        0.129242   0.105996\n",
      "13        2014         0.008523           0.761657        0.126016   0.103804\n",
      "14        2015         0.008858           0.765697        0.125420   0.100026\n",
      "15        2016         0.007723           0.755939        0.128413   0.107924\n",
      "16        2017         0.008314           0.759063        0.128308   0.104315\n",
      "17        2018         0.008136           0.755003        0.129367   0.107493\n",
      "18        2019         0.007891           0.753314        0.134141   0.104654\n",
      "19        2020         0.010595           0.698768        0.134929   0.155707\n",
      "20        2021         0.009515           0.744283        0.128071   0.118131\n",
      "21        2022         0.010181           0.760467        0.121638   0.107714\n",
      "22        2023         0.011717           0.753640        0.127709   0.106935\n"
     ]
    }
   ],
   "source": [
    "yearly_trends = df.groupby('SchoolYear')[['PropUnderweight', 'PropHealthyWeight', 'PropOverweight', 'PropObese']].mean().reset_index()\n",
    "print(yearly_trends)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "6d1020cf-4e92-46e6-aef5-5578e096e7d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "for col in ['PropUnderweight', 'PropHealthyWeight', 'PropOverweight', 'PropObese']:\n",
    "    sns.lineplot(data=yearly_trends, x='SchoolYear', y=col, marker='o', label=col)\n",
    "    \n",
    "plt.xticks(rotation=45)\n",
    "plt.title(\"BMI Proportion Trends Over School Years\")\n",
    "plt.xlabel(\"School Year\")\n",
    "plt.ylabel(\"Average Proportion\")\n",
    "plt.legend()\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3184628b-c24e-4c8c-aa67-cc99e1b01a08",
   "metadata": {},
   "source": [
    "BMI categories proportions change over time."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e80f0e0-16cc-43dc-8336-86b4a693b116",
   "metadata": {},
   "source": [
    "## Step 6: Compare Hospitals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "cec8cb04-caee-4b15-89c2-d523ba48d2d2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            NameHospital  PropUnderweight  PropHealthyWeight  PropOverweight  \\\n",
      "0     Ayrshire and Arran         0.013475           0.744227        0.128681   \n",
      "1                Borders         0.008409           0.772596        0.125012   \n",
      "2  Dumfries and Galloway         0.007731           0.742292        0.137032   \n",
      "3                   Fife         0.009044           0.758541        0.127450   \n",
      "4           Forth Valley         0.010546           0.776265        0.119511   \n",
      "\n",
      "   PropObese  \n",
      "0   0.113617  \n",
      "1   0.093983  \n",
      "2   0.112945  \n",
      "3   0.104966  \n",
      "4   0.093678  \n"
     ]
    }
   ],
   "source": [
    "hospital_summary = df.groupby('NameHospital')[['PropUnderweight', 'PropHealthyWeight', 'PropOverweight', 'PropObese']].mean().reset_index()\n",
    "print(hospital_summary.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "id": "4ad3fc84-6e63-4c18-b5d4-bbf5d5b30381",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 6))\n",
    "sns.barplot(data=hospital_summary, x='PropObese', y='NameHospital', palette='viridis')\n",
    "plt.title(\"Average Proportion of Obese Children by Hospital\")\n",
    "plt.xlabel(\"Proportion Obese\")\n",
    "plt.ylabel(\"Hospital\")\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "hospital_heatmap = hospital_summary.set_index('NameHospital')\n",
    "plt.figure(figsize=(12, 10))\n",
    "sns.heatmap(hospital_heatmap, annot=True, cmap=\"YlGnBu\", fmt=\".2f\")\n",
    "plt.title(\"BMI Proportions by Hospital\")\n",
    "plt.ylabel(\"Hospital\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24c66d7a-97bd-4e85-ade6-928bf103b0bb",
   "metadata": {},
   "source": [
    "This compares how different hospitals perform in terms of BMI categories distributions."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3af12416-2523-4ac0-8be5-c0c5c8322b26",
   "metadata": {},
   "source": [
    "## Step 7: Compare by Gender"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "6b2c3598-60bf-4a41-9951-63ef9d18c8d8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      Sex  PropUnderweight  PropHealthyWeight  PropOverweight  PropObese\n",
      "0  Female         0.008608           0.766216        0.124067   0.101109\n",
      "1    Male         0.013758           0.748652        0.127353   0.110238\n"
     ]
    }
   ],
   "source": [
    "gender_summary = df.groupby('Sex')[['PropUnderweight', 'PropHealthyWeight', 'PropOverweight', 'PropObese']].mean().reset_index()\n",
    "print(gender_summary)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "ec7df8fd-2f3e-444a-bf69-57910e50b26a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gender_summary_melted = gender_summary.melt(id_vars='Sex', var_name='BMI_Category', value_name='Average_Proportion')\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.barplot(data=gender_summary_melted, x='Sex', y='Average_Proportion', hue='BMI_Category', palette='viridis')\n",
    "plt.title(\"BMI Proportions by Gender\")\n",
    "plt.ylabel(\"Average Proportion\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef1f184a-a681-41f2-a945-26995c3acdd7",
   "metadata": {},
   "source": [
    "Highlights any gender-based differences in BMI categories distributions."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d7b3665-97fa-41a1-b769-f99c6f325584",
   "metadata": {},
   "source": [
    "## Step 8: Create Pivot Tables for Quick Comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "id": "5975e486-4b31-402d-9556-349ebe936e77",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                          PropHealthyWeight                                \\\n",
      "SchoolYear                             2001      2002      2003      2004   \n",
      "NameHospital                                                                \n",
      "Ayrshire and Arran                      NaN       NaN       NaN       NaN   \n",
      "Borders                            0.765702       NaN  0.762698  0.734882   \n",
      "Dumfries and Galloway                   NaN       NaN       NaN  0.741763   \n",
      "Fife                               0.754291  0.748538  0.749290  0.746864   \n",
      "Forth Valley                            NaN       NaN       NaN       NaN   \n",
      "Grampian                                NaN       NaN       NaN       NaN   \n",
      "Greater Glasgow and Clyde               NaN       NaN       NaN       NaN   \n",
      "Highland                                NaN       NaN       NaN       NaN   \n",
      "Lanarkshire                        0.767947  0.764356  0.748501  0.761026   \n",
      "Lothian                            0.735590  0.715051  0.763816  0.751594   \n",
      "Orkney                                  NaN       NaN       NaN       NaN   \n",
      "Shetland                                NaN       NaN       NaN       NaN   \n",
      "Tayside                                 NaN  0.766630  0.758475  0.771095   \n",
      "Western Isles                           NaN       NaN  0.768780  0.691667   \n",
      "\n",
      "                                                                             \\\n",
      "SchoolYear                     2005      2006      2007      2008      2009   \n",
      "NameHospital                                                                  \n",
      "Ayrshire and Arran              NaN       NaN  0.762970  0.790614  0.754415   \n",
      "Borders                    0.774600  0.778650  0.798154  0.777707  0.749924   \n",
      "Dumfries and Galloway      0.755944  0.740752  0.749264  0.762014  0.740107   \n",
      "Fife                       0.712269  0.739064  0.754805  0.774083  0.760919   \n",
      "Forth Valley               0.754467  0.782134  0.800566  0.783753  0.771899   \n",
      "Grampian                        NaN       NaN       NaN       NaN  0.781285   \n",
      "Greater Glasgow and Clyde       NaN  0.768879  0.800598  0.810744  0.777570   \n",
      "Highland                        NaN       NaN       NaN  0.739298  0.745857   \n",
      "Lanarkshire                0.764178  0.772415  0.772267  0.788321  0.792131   \n",
      "Lothian                    0.756610  0.748536  0.753249  0.759754  0.763933   \n",
      "Orkney                          NaN       NaN       NaN       NaN       NaN   \n",
      "Shetland                        NaN       NaN       NaN  0.789483  0.764092   \n",
      "Tayside                    0.748345  0.763674  0.785068  0.761606  0.765186   \n",
      "Western Isles              0.738553  0.785948  0.739731  0.745699  0.728902   \n",
      "\n",
      "                                     ... PropUnderweight                      \\\n",
      "SchoolYear                     2010  ...            2014      2015      2016   \n",
      "NameHospital                         ...                                       \n",
      "Ayrshire and Arran         0.725677  ...        0.012167  0.012046  0.013274   \n",
      "Borders                    0.785869  ...        0.009860  0.007313  0.006233   \n",
      "Dumfries and Galloway      0.755617  ...        0.000675  0.003609  0.005327   \n",
      "Fife                       0.762007  ...        0.008151  0.007935  0.010645   \n",
      "Forth Valley               0.790432  ...        0.007969  0.011843  0.004946   \n",
      "Grampian                   0.787659  ...        0.009154  0.013647  0.006169   \n",
      "Greater Glasgow and Clyde  0.803211  ...        0.014640  0.011551  0.011244   \n",
      "Highland                   0.737046  ...        0.006506  0.008604  0.007013   \n",
      "Lanarkshire                0.791863  ...        0.019470  0.017645  0.013012   \n",
      "Lothian                    0.765770  ...        0.009028  0.011339  0.011533   \n",
      "Orkney                     0.740447  ...        0.000000  0.000000  0.005102   \n",
      "Shetland                   0.771420  ...        0.000000  0.007398  0.004000   \n",
      "Tayside                    0.739473  ...        0.007242  0.007728  0.005871   \n",
      "Western Isles              0.711315  ...        0.014464  0.003356  0.003759   \n",
      "\n",
      "                                                                             \\\n",
      "SchoolYear                     2017      2018      2019      2020      2021   \n",
      "NameHospital                                                                  \n",
      "Ayrshire and Arran         0.014204  0.014591  0.011321  0.012792  0.013011   \n",
      "Borders                    0.005412  0.004188       NaN       NaN  0.010955   \n",
      "Dumfries and Galloway      0.008077  0.006778  0.009010       NaN  0.007130   \n",
      "Fife                       0.008182  0.010024  0.010204       NaN  0.015558   \n",
      "Forth Valley               0.012196  0.009312  0.013614       NaN  0.007382   \n",
      "Grampian                   0.006810  0.007318       NaN       NaN  0.010237   \n",
      "Greater Glasgow and Clyde  0.011121  0.008249       NaN  0.006501  0.013944   \n",
      "Highland                   0.008960  0.006473  0.009402  0.003455  0.007949   \n",
      "Lanarkshire                0.016753  0.014631  0.009554       NaN  0.010851   \n",
      "Lothian                    0.011212  0.010509  0.009923  0.007006  0.010179   \n",
      "Orkney                     0.000000  0.000000  0.005882  0.010417  0.000000   \n",
      "Shetland                   0.000000  0.004630  0.000000  0.012195  0.007576   \n",
      "Tayside                    0.009558  0.007944       NaN       NaN  0.010309   \n",
      "Western Isles              0.003906  0.009259  0.000000  0.021800  0.008130   \n",
      "\n",
      "                                               \n",
      "SchoolYear                     2022      2023  \n",
      "NameHospital                                   \n",
      "Ayrshire and Arran         0.008313  0.009619  \n",
      "Borders                    0.012776  0.006684  \n",
      "Dumfries and Galloway      0.008666  0.013690  \n",
      "Fife                       0.010847  0.010768  \n",
      "Forth Valley               0.011157  0.026992  \n",
      "Grampian                   0.011404  0.006511  \n",
      "Greater Glasgow and Clyde  0.016002  0.011311  \n",
      "Highland                   0.011639  0.008362  \n",
      "Lanarkshire                0.008193  0.007448  \n",
      "Lothian                    0.018613  0.019416  \n",
      "Orkney                     0.000000  0.005102  \n",
      "Shetland                   0.015000  0.018343  \n",
      "Tayside                    0.009931  0.007747  \n",
      "Western Isles              0.000000  0.012043  \n",
      "\n",
      "[14 rows x 92 columns]\n"
     ]
    }
   ],
   "source": [
    "pivot = pd.pivot_table(\n",
    "    df, \n",
    "    index='NameHospital', \n",
    "    columns='SchoolYear', \n",
    "    values=['PropUnderweight', 'PropHealthyWeight', 'PropOverweight', 'PropObese'],\n",
    "    aggfunc='mean'\n",
    ")\n",
    "print(pivot)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aec3163e-c026-4138-9ca7-e502aa9fa797",
   "metadata": {},
   "source": [
    "By creating matrix of our data we can reveal patterns across hospitals and years"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e401b45-5de8-4a9e-9b93-ff979b7511a5",
   "metadata": {},
   "source": [
    "## Clustering"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb544603-9ba9-4648-b77b-ae5e0561b945",
   "metadata": {},
   "source": [
    "## Step 1: Prepare the Data for Clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "id": "2ee4ada4-a566-4748-a9b5-98716e1de9d2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            NameHospital  PropUnderweight  PropHealthyWeight  PropOverweight  \\\n",
      "0     Ayrshire and Arran         0.013475           0.744227        0.128681   \n",
      "1                Borders         0.008409           0.772596        0.125012   \n",
      "2  Dumfries and Galloway         0.007731           0.742292        0.137032   \n",
      "3                   Fife         0.009044           0.758541        0.127450   \n",
      "4           Forth Valley         0.010546           0.776265        0.119511   \n",
      "\n",
      "   PropObese  \n",
      "0   0.113617  \n",
      "1   0.093983  \n",
      "2   0.112945  \n",
      "3   0.104966  \n",
      "4   0.093678  \n"
     ]
    }
   ],
   "source": [
    "hospital_df = df.groupby('NameHospital').agg({\n",
    "    'PropUnderweight': 'mean',\n",
    "    'PropHealthyWeight': 'mean',\n",
    "    'PropOverweight': 'mean',\n",
    "    'PropObese': 'mean'\n",
    "}).reset_index()\n",
    "print(hospital_df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f1f6562-b04d-4c5f-90fe-324dde092b8e",
   "metadata": {},
   "source": [
    "## Step 2: Standardize the Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "id": "d33adc4f-f9b0-48fa-aa9d-f7e5483867f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "features = ['PropUnderweight', 'PropHealthyWeight', 'PropOverweight', 'PropObese']\n",
    "X = hospital_df[features]\n",
    "scaler = StandardScaler()\n",
    "X_scaled = scaler.fit_transform(X)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52b2966e-1574-45d7-9676-63c7435f5f39",
   "metadata": {},
   "source": [
    "## Step 3: Determine the Optimal Number of Clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "5358c870-36a0-4a17-9c21-b27ee173eb40",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "inertia = []\n",
    "k_range = range(1, 11) \n",
    "for k in k_range:\n",
    "    kmeans = KMeans(n_clusters=k, random_state=42)\n",
    "    kmeans.fit(X_scaled)\n",
    "    inertia.append(kmeans.inertia_)\n",
    "plt.figure(figsize=(8, 4))\n",
    "plt.plot(k_range, inertia, marker='o')\n",
    "plt.xlabel('Number of Clusters (k)')\n",
    "plt.ylabel('Inertia')\n",
    "plt.title('Elbow Method For Optimal k')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2bec571b-10b2-4696-94fa-b7daeaa44586",
   "metadata": {},
   "source": [
    "## Step 4: Apply K-Means Clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "id": "b6d9b377-22c9-436b-abc6-caf29dfff500",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            NameHospital  PropUnderweight  PropHealthyWeight  PropOverweight  \\\n",
      "0     Ayrshire and Arran         0.013475           0.744227        0.128681   \n",
      "1                Borders         0.008409           0.772596        0.125012   \n",
      "2  Dumfries and Galloway         0.007731           0.742292        0.137032   \n",
      "3                   Fife         0.009044           0.758541        0.127450   \n",
      "4           Forth Valley         0.010546           0.776265        0.119511   \n",
      "\n",
      "   PropObese  Cluster  \n",
      "0   0.113617        1  \n",
      "1   0.093983        0  \n",
      "2   0.112945        2  \n",
      "3   0.104966        0  \n",
      "4   0.093678        0  \n"
     ]
    }
   ],
   "source": [
    "optimal_k = 3\n",
    "kmeans = KMeans(n_clusters=optimal_k, random_state=42)\n",
    "hospital_df['Cluster'] = kmeans.fit_predict(X_scaled)\n",
    "print(hospital_df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7b5cdf4-d2b8-4e18-990e-71bc44d2ec74",
   "metadata": {},
   "source": [
    "## Step 5: Analyze and Visualize the Clusters"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9895140-7034-4bd5-91c6-0d53282b3f3f",
   "metadata": {},
   "source": [
    "## a. View Cluster Centers (in the standardized space)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "id": "c01a764c-ef8e-4da9-905c-3ab412c9a235",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cluster Centers (Standardized):\n",
      "[[ 0.27277218  0.67064432 -0.53733425 -0.65457816]\n",
      " [ 0.46421339 -1.06955053  0.10206212  1.41651882]\n",
      " [-1.12779213 -1.29889926  1.54396135  1.0193886 ]]\n",
      "Cluster Centers (Original Scale):\n",
      "   PropUnderweight  PropHealthyWeight  PropOverweight  PropObese\n",
      "0         0.011966           0.766883        0.121255   0.099896\n",
      "1         0.012719           0.741425        0.127122   0.118733\n",
      "2         0.006457           0.738070        0.140352   0.115121\n"
     ]
    }
   ],
   "source": [
    "print(\"Cluster Centers (Standardized):\")\n",
    "print(kmeans.cluster_centers_)\n",
    "centers_original = scaler.inverse_transform(kmeans.cluster_centers_)\n",
    "centers_df = pd.DataFrame(centers_original, columns=features)\n",
    "print(\"Cluster Centers (Original Scale):\")\n",
    "print(centers_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6981a36f-7827-4c92-ae2e-b1458412f346",
   "metadata": {},
   "source": [
    "## b. Visualize Clusters Using PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "id": "24821aa6-2708-42d7-8d69-993f239bdfe7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Reduce dimensions to 2 components for visualization\n",
    "pca = PCA(n_components=2)\n",
    "X_pca = pca.fit_transform(X_scaled)\n",
    "# Add PCA components to the hospital dataframe\n",
    "hospital_df['PCA1'] = X_pca[:, 0]\n",
    "hospital_df['PCA2'] = X_pca[:, 1]\n",
    "# Create a scatter plot of the clusters\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.scatterplot(x='PCA1', y='PCA2', hue='Cluster', data=hospital_df, palette='viridis', s=100)\n",
    "plt.title('Hospital Clusters (PCA Visualization)')\n",
    "plt.xlabel('PCA Component 1')\n",
    "plt.ylabel('PCA Component 2')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d29bdf44-5b52-44a5-a3df-6a290b025e3e",
   "metadata": {},
   "source": [
    "## c. Examine Cluster Profiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "id": "d51c0dbe-9ce0-45ee-bae5-3420ed9039e0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Cluster  PropUnderweight  PropHealthyWeight  PropOverweight  PropObese\n",
      "0        0         0.011966           0.766883        0.121255   0.099896\n",
      "1        1         0.012719           0.741425        0.127122   0.118733\n",
      "2        2         0.006457           0.738070        0.140352   0.115121\n"
     ]
    }
   ],
   "source": [
    "cluster_summary = hospital_df.groupby('Cluster')[features].mean().reset_index()\n",
    "print(cluster_summary)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8fd14bd-92a2-48eb-b02c-149994b6af7e",
   "metadata": {},
   "source": [
    "## Linear Regression on Proportions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66652cbb-9d9f-4e50-ae4d-01d54c483ba5",
   "metadata": {},
   "source": [
    "## Step 1: Create the Outcome Variable (Proportion)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "id": "ba8795f0-8ef2-4ebd-8b2d-af4b32ebf1de",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   EpiObese  ValidCounts  PropObese\n",
      "0        28          418   0.066986\n",
      "1        42          411   0.102190\n",
      "2       106          979   0.108274\n",
      "3       114          936   0.121795\n",
      "4       155         1764   0.087868\n"
     ]
    }
   ],
   "source": [
    "print(df[['EpiObese', 'ValidCounts', 'PropObese']].head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40c9c3b4-a50e-4ca3-99ae-22669950f292",
   "metadata": {},
   "source": [
    "## Step 2: Prepare Predictor Variables\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "id": "d66b9db2-5ba9-4e74-aaea-1f6c24f80cab",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['SchoolYear'] = df['SchoolYear'].astype('category')\n",
    "df['Sex'] = df['Sex'].astype('category')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4023498-40be-4ba6-9d1a-209700ea762e",
   "metadata": {},
   "source": [
    "## Step 3: Fit a Linear Regression Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "id": "6803cd3b-cdf7-451c-8e51-5557f8194e17",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:              PropObese   R-squared:                       0.264\n",
      "Model:                            OLS   Adj. R-squared:                  0.229\n",
      "Method:                 Least Squares   F-statistic:                     7.667\n",
      "Date:                Wed, 05 Feb 2025   Prob (F-statistic):           2.43e-21\n",
      "Time:                        11:06:52   Log-Likelihood:                 1319.5\n",
      "No. Observations:                 516   AIC:                            -2591.\n",
      "Df Residuals:                     492   BIC:                            -2489.\n",
      "Df Model:                          23                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "=========================================================================================\n",
      "                            coef    std err          t      P>|t|      [0.025      0.975]\n",
      "-----------------------------------------------------------------------------------------\n",
      "Intercept                 0.0953      0.007     13.921      0.000       0.082       0.109\n",
      "C(SchoolYear)[T.2002]     0.0046      0.010      0.478      0.633      -0.014       0.023\n",
      "C(SchoolYear)[T.2003]    -0.0019      0.009     -0.212      0.832      -0.019       0.015\n",
      "C(SchoolYear)[T.2004]     0.0217      0.009      2.553      0.011       0.005       0.038\n",
      "C(SchoolYear)[T.2005]     0.0059      0.008      0.709      0.479      -0.010       0.022\n",
      "C(SchoolYear)[T.2006]     0.0004      0.008      0.050      0.960      -0.016       0.016\n",
      "C(SchoolYear)[T.2007]    -0.0057      0.008     -0.711      0.478      -0.022       0.010\n",
      "C(SchoolYear)[T.2008]    -0.0063      0.008     -0.802      0.423      -0.022       0.009\n",
      "C(SchoolYear)[T.2009]     0.0039      0.008      0.508      0.612      -0.011       0.019\n",
      "C(SchoolYear)[T.2010]    -0.0006      0.008     -0.076      0.940      -0.016       0.015\n",
      "C(SchoolYear)[T.2011]     0.0031      0.008      0.403      0.687      -0.012       0.018\n",
      "C(SchoolYear)[T.2012]     0.0006      0.008      0.076      0.939      -0.015       0.016\n",
      "C(SchoolYear)[T.2013]     0.0062      0.008      0.799      0.425      -0.009       0.021\n",
      "C(SchoolYear)[T.2014]     0.0040      0.008      0.514      0.607      -0.011       0.019\n",
      "C(SchoolYear)[T.2015]     0.0002      0.008      0.024      0.981      -0.015       0.015\n",
      "C(SchoolYear)[T.2016]     0.0081      0.008      1.049      0.295      -0.007       0.023\n",
      "C(SchoolYear)[T.2017]     0.0045      0.008      0.581      0.562      -0.011       0.020\n",
      "C(SchoolYear)[T.2018]     0.0076      0.008      0.993      0.321      -0.007       0.023\n",
      "C(SchoolYear)[T.2019]     0.0048      0.008      0.599      0.550      -0.011       0.021\n",
      "C(SchoolYear)[T.2020]     0.0559      0.009      6.561      0.000       0.039       0.073\n",
      "C(SchoolYear)[T.2021]     0.0183      0.008      2.375      0.018       0.003       0.033\n",
      "C(SchoolYear)[T.2022]     0.0079      0.008      1.022      0.307      -0.007       0.023\n",
      "C(SchoolYear)[T.2023]     0.0071      0.008      0.921      0.358      -0.008       0.022\n",
      "C(Sex)[T.Male]            0.0091      0.002      5.397      0.000       0.006       0.012\n",
      "==============================================================================\n",
      "Omnibus:                      183.570   Durbin-Watson:                   1.702\n",
      "Prob(Omnibus):                  0.000   Jarque-Bera (JB):             1035.478\n",
      "Skew:                           1.449   Prob(JB):                    1.41e-225\n",
      "Kurtosis:                       9.306   Cond. No.                         45.2\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
     ]
    }
   ],
   "source": [
    "formula = \"PropObese ~ C(SchoolYear) + C(Sex)\"\n",
    "model_linear = smf.ols(formula=formula, data=df).fit()\n",
    "print(model_linear.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38b721e0-4eae-45b9-9628-bd9e2b5796cd",
   "metadata": {},
   "source": [
    "A key finding is that obesity rates went up a lot in 2020 (5.59% higher than usual), with smaller but noticeable increases in 2004 and 2021. Additionally, males tend to have higher obesity rates than females (0.91% more). This suggests that certain years (especially 2020) and gender differences are important in understanding obesity trends."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84229ca0-64c1-4a8d-b3a0-eab73c34d965",
   "metadata": {},
   "source": [
    "## Binomial (Logistic) Regression on Aggregated Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "id": "c7dc7a50-50ce-40c2-9d81-b4aca23b1b2b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   ValidCounts  EpiObese  NonObese\n",
      "0          418        28       390\n",
      "1          411        42       369\n",
      "2          979       106       873\n",
      "3          936       114       822\n",
      "4         1764       155      1609\n"
     ]
    }
   ],
   "source": [
    "df['NonObese'] = df['ValidCounts'] - df['EpiObese']\n",
    "print(df[['ValidCounts', 'EpiObese', 'NonObese']].head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b97189cd-f219-4c51-a17c-f5501d5018e6",
   "metadata": {},
   "source": [
    "## Step 1: Fit a Binomial Regression Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "id": "82eb2c33-1233-4483-81ad-e442e2a7af50",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                 Generalized Linear Model Regression Results                  \n",
      "==============================================================================\n",
      "Dep. Variable:               EpiObese   No. Observations:                  516\n",
      "Model:                            GLM   Df Residuals:                      492\n",
      "Model Family:                Binomial   Df Model:                           23\n",
      "Link Function:                  Logit   Scale:                          1.0000\n",
      "Method:                          IRLS   Log-Likelihood:                   -inf\n",
      "Date:                Wed, 05 Feb 2025   Deviance:                   7.4942e+06\n",
      "Time:                        11:06:52   Pearson chi2:                 1.22e+23\n",
      "No. Iterations:                     2   Pseudo R-squ. (CS):                nan\n",
      "Covariance Type:            nonrobust                                         \n",
      "=========================================================================================\n",
      "                            coef    std err          z      P>|z|      [0.025      0.975]\n",
      "-----------------------------------------------------------------------------------------\n",
      "Intercept              9.667e+17   2.39e+07   4.04e+10      0.000    9.67e+17    9.67e+17\n",
      "C(SchoolYear)[T.2002]  2.677e+17   3.36e+07   7.98e+09      0.000    2.68e+17    2.68e+17\n",
      "C(SchoolYear)[T.2003] -7.206e+16   3.06e+07  -2.35e+09      0.000   -7.21e+16   -7.21e+16\n",
      "C(SchoolYear)[T.2004]  1.057e+17   2.97e+07   3.55e+09      0.000    1.06e+17    1.06e+17\n",
      "C(SchoolYear)[T.2005]  1.039e+17   2.91e+07   3.57e+09      0.000    1.04e+17    1.04e+17\n",
      "C(SchoolYear)[T.2006] -1.032e+17   2.85e+07  -3.62e+09      0.000   -1.03e+17   -1.03e+17\n",
      "C(SchoolYear)[T.2007] -1.571e+17   2.81e+07  -5.59e+09      0.000   -1.57e+17   -1.57e+17\n",
      "C(SchoolYear)[T.2008] -1.424e+17   2.74e+07   -5.2e+09      0.000   -1.42e+17   -1.42e+17\n",
      "C(SchoolYear)[T.2009]  1.016e+17   2.71e+07   3.74e+09      0.000    1.02e+17    1.02e+17\n",
      "C(SchoolYear)[T.2010] -7.889e+16   2.69e+07  -2.93e+09      0.000   -7.89e+16   -7.89e+16\n",
      "C(SchoolYear)[T.2011]  2.048e+17   2.69e+07   7.61e+09      0.000    2.05e+17    2.05e+17\n",
      "C(SchoolYear)[T.2012]  1.892e+17   2.69e+07   7.03e+09      0.000    1.89e+17    1.89e+17\n",
      "C(SchoolYear)[T.2013]  3.161e+17   2.69e+07   1.17e+10      0.000    3.16e+17    3.16e+17\n",
      "C(SchoolYear)[T.2014]  2.615e+17   2.69e+07   9.72e+09      0.000    2.62e+17    2.62e+17\n",
      "C(SchoolYear)[T.2015]  2.507e+17   2.69e+07   9.32e+09      0.000    2.51e+17    2.51e+17\n",
      "C(SchoolYear)[T.2016]  2.919e+17   2.69e+07   1.09e+10      0.000    2.92e+17    2.92e+17\n",
      "C(SchoolYear)[T.2017]   2.62e+17   2.69e+07   9.74e+09      0.000    2.62e+17    2.62e+17\n",
      "C(SchoolYear)[T.2018]  7.648e+16   2.69e+07   2.84e+09      0.000    7.65e+16    7.65e+16\n",
      "C(SchoolYear)[T.2019] -2.993e+17   2.81e+07  -1.07e+10      0.000   -2.99e+17   -2.99e+17\n",
      "C(SchoolYear)[T.2020]  5.274e+17   2.97e+07   1.77e+10      0.000    5.27e+17    5.27e+17\n",
      "C(SchoolYear)[T.2021]  5.286e+17   2.69e+07   1.96e+10      0.000    5.29e+17    5.29e+17\n",
      "C(SchoolYear)[T.2022]  2.297e+17   2.69e+07   8.54e+09      0.000     2.3e+17     2.3e+17\n",
      "C(SchoolYear)[T.2023]   1.51e+17   2.69e+07   5.61e+09      0.000    1.51e+17    1.51e+17\n",
      "C(Sex)[T.Male]         1.359e+17   5.91e+06    2.3e+10      0.000    1.36e+17    1.36e+17\n",
      "=========================================================================================\n"
     ]
    }
   ],
   "source": [
    "model_binom = smf.glm(\n",
    "    formula=\"EpiObese ~ C(SchoolYear) + C(Sex)\", \n",
    "    data=df,\n",
    "    family=sm.families.Binomial(),\n",
    "    weights=df['ValidCounts']  \n",
    ").fit()\n",
    "print(model_binom.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54f23e71-b60f-4e91-bcfa-763d71ad6a7b",
   "metadata": {},
   "source": [
    "## Diagnostic Checking"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8432b47b-b5e9-4865-9755-c263ffa53a34",
   "metadata": {},
   "source": [
    "## Step 1: Residuals vs. Fitted Values Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "id": "43532a23-6410-4147-ae03-8931473a244b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fitted_vals = model_linear.fittedvalues\n",
    "residuals = model_linear.resid\n",
    "plt.figure(figsize=(8, 5))\n",
    "sns.residplot(x=fitted_vals, y=residuals, lowess=True, \n",
    "              line_kws={'color': 'red', 'lw': 1, 'alpha': 0.8})\n",
    "plt.xlabel('Fitted values')\n",
    "plt.ylabel('Residuals')\n",
    "plt.title('Residuals vs Fitted Values')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7ad4343-e370-4bf8-bad2-66160e1be383",
   "metadata": {},
   "source": [
    "## Step 2: Q-Q Plot of Residuals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "id": "972690c2-20d7-48e8-9a3d-0ad4820f4c29",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 600x500 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6, 5))\n",
    "sm.qqplot(residuals, line='45', fit=True)\n",
    "plt.title('Normal Q-Q Plot')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72e7e54d-e2bb-4a96-b140-a202ab50cc78",
   "metadata": {},
   "source": [
    "Residuals lie along the 45-degree line, they are approximately normally distributed. Deviations might indicate skewness or heavy tails."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc336d62-0ad3-47cb-b473-e9ab82f8dc6a",
   "metadata": {},
   "source": [
    "## Step 3: Spread-Location Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "id": "11a8ac59-eeb4-402e-a55c-63747c119899",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "influence = model_linear.get_influence()\n",
    "standardized_residuals = influence.resid_studentized_internal\n",
    "plt.figure(figsize=(8, 5))\n",
    "sns.scatterplot(x=fitted_vals, y=np.sqrt(np.abs(standardized_residuals)))\n",
    "sns.regplot(x=fitted_vals, y=np.sqrt(np.abs(standardized_residuals)),\n",
    "            scatter=False, lowess=True, line_kws={'color': 'red', 'lw': 1})\n",
    "plt.xlabel('Fitted values')\n",
    "plt.ylabel('Sqrt(|Standardized Residuals|)')\n",
    "plt.title('Scale-Location Plot')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ddf9b270-2ddb-46e7-a7b7-d431dd4af2c6",
   "metadata": {},
   "source": [
    "A horizontal line suggests constant variance. An upward or downward trend indicates non-constant variance (heteroscedasticity)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "267e8f63-928a-4253-88a7-2efeefd0b389",
   "metadata": {},
   "source": [
    "## Step 4: Residuals vs. Leverage Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "id": "c106bd01-ce4f-4c47-adbd-da2f6185d177",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "leverage = influence.hat_matrix_diag\n",
    "cooks = influence.cooks_distance[0]\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.scatterplot(x=leverage, y=standardized_residuals)\n",
    "sns.regplot(x=leverage, y=standardized_residuals, scatter=False, lowess=True, \n",
    "            line_kws={'color': 'red', 'lw': 1})\n",
    "plt.xlabel('Leverage')\n",
    "plt.ylabel('Standardized Residuals')\n",
    "plt.title('Residuals vs Leverage')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "id": "a3a927de-def5-4648-ba20-fbe75cc5dcfd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 4))\n",
    "plt.stem(np.arange(len(cooks)), cooks, markerfmt=\",\")\n",
    "plt.xlabel('Observation Index')\n",
    "plt.ylabel(\"Cook's Distance\")\n",
    "plt.title(\"Cook's Distance for Each Observation\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f34701e5-eee1-4f67-bb69-809082f7c545",
   "metadata": {},
   "source": [
    "Points with high leverage and large standardized residuals (or high Cook’s distance) may be influential and warrant further investigation."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa69220a-742c-47dc-8268-34cc08883cf4",
   "metadata": {},
   "source": [
    "## Final Takeaways"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6de60aac-6f93-44bc-8bc0-eb4be07f0806",
   "metadata": {},
   "source": [
    "### Overall BMI Distribution: <br>\n",
    "\n",
    "Most children (about 70–80%) are at a healthy weight, while around 10% are overweight and another 10% are obese. Very few children (less than 2%) are underweight. This shows that while the majority of kids have a healthy BMI, a significant number are overweight or obese, which is a concern.\n",
    "\n",
    "### Hospital Comparisons:<br>\n",
    "When hospitals were grouped based on the proportion of BMI data (to avoid bias from hospital size), they didn’t form very different clusters. This means most hospitals have similar BMI patterns. However, a few hospitals showed higher rates of overweight or obesity compared to others, which might need more attention or specific actions to address the issue.\n",
    "\n",
    "### Time Trends & Gender Differences: <br>\n",
    "\n",
    "Linear regression shows that obesity rates noticeably increased in 2020, with men consistently having slightly higher rates than women.\n",
    "While some years and gender differences stand out, the model’s moderate R-squared (~26%) suggests that other factors, like income levels and eating habits, likely play a role in obesity trends.\n",
    "\n",
    "### Actionable Insights:<br>\n",
    "\n",
    "Target interventions at specific years or hospitals with higher obesity rates. Look into the reasons behind the sharp increase in 2020, such as potential policy changes or wider societal factors. Consider adding more data (like information on nutrition programs or physical education availability) or using different analysis methods (like mixed-effects or Poisson/Negative Binomial models) to gain a clearer and more accurate picture of these trends.\n",
    "\n",
    "**Overall,** the analysis shows key trends most children have a healthy weight, but a significant number face overweight or obesity, especially in certain years and among boys. These insights can help shape better public health strategies and allocate resources more effectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b4a27f9b-be50-4e8b-a6ab-57880a875783",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "pygments_lexer": "ipython3",
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