california-equity-git/initial_view/secondtake.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Project: California Equity Research\n",
    "### Data: postgis db `calif_equity` with california climate investment and california enviroscreen data\n",
    "#### Goal: Analyze the relationship between climate investment and environmental justice in California\n",
    "#### This notebook: second take \n",
    "##### Author: [dpadams](dpadams@fullerton.edu)\n",
    "##### Date: 2024-11-24"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing the necessary libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "## set directory\n",
    "import os\n",
    "os.chdir('/home/dadams/Repos/california_equity_git')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# read in the data\n",
    "data = pd.read_csv('data_raw/cci_programs_data.csv', low_memory=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Project IDNumber', 'Reporting Cycle Name', 'Agency Name',\n",
       "       'Program Name', 'Program Description', 'Sub Program Name',\n",
       "       'Record Type', 'Project Name', 'Project Type', 'Project Description',\n",
       "       ...\n",
       "       'Net Density  DUA', 'Applicants  Assisted', 'Invasive Cover 12 Months',\n",
       "       'Invasive Cover 36 Months', 'Project Acreage', 'IS IAE',\n",
       "       'Intermediary Admin Expenses Calc', 'PRIMARY_FUNDING_RECIPIENT_TYPE',\n",
       "       'TRIBAL AFFILIATION', 'PROJECT PARTNERS'],\n",
       "      dtype='object', length=127)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          Tract    ZIP         County    ApproxLoc  TotPop19    CIscore  \\\n",
      "0  6.083002e+09  93454  Santa Barbara  Santa Maria      4495  36.019653   \n",
      "1  6.083002e+09  93455  Santa Barbara  Santa Maria     13173  37.030667   \n",
      "2  6.083002e+09  93454  Santa Barbara  Santa Maria      2398  31.213140   \n",
      "3  6.083002e+09  93455  Santa Barbara       Orcutt      4496   6.639331   \n",
      "4  6.083002e+09  93455  Santa Barbara       Orcutt      4008  14.022852   \n",
      "\n",
      "    CIscoreP     Ozone     OzoneP     PM2_5  ...  Elderly65  Hispanic  \\\n",
      "0  69.162885  0.034190  10.566273  7.567724  ...    12.5028   68.9210   \n",
      "1  70.637922  0.035217  11.561917  7.624775  ...     5.3519   78.6229   \n",
      "2  61.069087  0.034190  10.566273  7.548835  ...    12.8857   65.7214   \n",
      "3   5.988401  0.036244  13.615432  7.660570  ...    14.4128   22.9537   \n",
      "4  23.121533  0.036244  13.615432  7.663210  ...    18.8872   33.4082   \n",
      "\n",
      "     White  AfricanAm  NativeAm  OtherMult    Shape_Leng    Shape_Area  \\\n",
      "0  20.8899     0.4004    0.2670     1.3126   6999.357689  2.847611e+06   \n",
      "1  13.2240     2.5051    0.0000     0.9489  19100.578232  1.635292e+07   \n",
      "2  30.6088     0.9591    0.0000     2.1685   4970.985897  1.352329e+06   \n",
      "3  69.1948     0.9342    0.7117     2.5356   6558.956012  2.417717e+06   \n",
      "4  59.7804     0.6986    1.4721     1.3723   6570.368730  2.608422e+06   \n",
      "\n",
      "     AAPI                                           geometry  \n",
      "0  8.2091  POLYGON ((-39795.07 -341919.191, -38126.384 -3...  \n",
      "1  4.6990  POLYGON ((-39795.07 -341919.191, -39803.632 -3...  \n",
      "2  0.5421  POLYGON ((-38115.747 -341130.248, -38126.384 -...  \n",
      "3  3.6699  POLYGON ((-37341.662 -348530.437, -37252.307 -...  \n",
      "4  3.2685  POLYGON ((-39465.107 -348499.262, -38244.305 -...  \n",
      "\n",
      "[5 rows x 67 columns]\n"
     ]
    }
   ],
   "source": [
    "import geopandas as gpd\n",
    "\n",
    "# Load the shapefile\n",
    "shapefile_path = '/home/dadams/Repos/california_equity_git/california_enviroscreen/calif_enviroscreen_shape/CES4 Final Shapefile.shp'\n",
    "gdf = gpd.read_file(shapefile_path)\n",
    "\n",
    "# Print the head of the GeoDataFrame\n",
    "print(gdf.head())import geopandas as gpd\n",
    "\n",
    "# Load the shapefile\n",
    "shapefile_path = '/home/dadams/Repos/california_equity_git/california_enviroscreen/calif_enviroscreen_shape/CES4 Final Shapefile.shp'\n",
    "gdf = gpd.read_file(shapefile_path)\n",
    "\n",
    "# Print the head of the GeoDataFrame\n",
    "print(gdf.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total GGRF Funding: $8.13B\n",
      "Number of projects: 131428\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Basic cleaning\n",
    "data['Date Operational'] = pd.to_datetime(data['Date Operational'])\n",
    "data = data[\n",
    "    (data['Date Operational'] >= '2010-01-01') & \n",
    "    (data['Date Operational'] <= '2024-11-01')\n",
    "].copy()\n",
    "\n",
    "# Remove rows with no GGRF funding\n",
    "data = data.dropna(subset=['Total Program GGRFFunding'])\n",
    "\n",
    "# Add derived columns\n",
    "data['Year'] = data['Date Operational'].dt.year\n",
    "data['is_multi_county'] = data['County'].str.contains(',', na=False)\n",
    "data['partnership_size'] = data['County'].str.count(',').fillna(0) + 1\n",
    "\n",
    "# Quick validation\n",
    "print(f\"Total GGRF Funding: ${data['Total Program GGRFFunding'].sum()/1e9:.2f}B\")\n",
    "print(f\"Number of projects: {len(data)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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nJ+uee+6RxWLR//73P9188836559/HKPMly1bphEjRqhly5Z66aWXFB8frzvvvFO1atUq8uvs3btXI0aM0L333qvbbrtNs2fP1rBhw7RixQrdeOONkqTU1FRdf/31io6O1j333KM6derot99+0+TJk3X06FFNnz7d6Tkv9/jNlY7xC/Pbb7+pevXqCgsLK/D+ypUra9CgQVqwYIHuu+8+SdK2bdv0119/6cMPP9T27duL8YkWz19//aUuXbrI29tbjz/+uNzd3fX++++rW7duWrt2bb7lCx588EH5+flpypQpOnjwoKZPn64HHnhAn332maSc0fG9evVSQECAnnjiCfn6+urgwYMFXoBxvmXLlmn8+PGOaeq7dOmibt26OabeP1/btm31zTffKCkpSd7e3pf/YQBAURkAAJxn9uzZhiTjjz/+MPbv32+4ubkZDz30kOP+66+/3mjevLlj+8CBA4YkY/bs2fmeS5IxZcoUx/aUKVMMScaECRMc+7KysozatWsbFovFmDZtmmN/fHy8UalSJeO2225z7Fu9erUhyahVq5aRlJTk2L9o0SJDkvHmm28ahmEYdrvduOqqq4zevXsbdrvd0S41NdWoV6+eceONN+bLNGrUqCJ9PhMnTjQkGT///LNjX3JyslGvXj2jbt26RnZ2ttP7v//++y/6nEOGDDEkGQkJCU77z5w5Y8TFxTn+xcfHO+4LDw83fH198z3X6dOnnR6TmJjouC/38/v444+NuLg4IyYmxlixYoXRsGFDw2KxGL///rvTc912222GpHz/rr/++ou+p7CwMKNXr16OHNu2bTNGjhxpSDIefPBBwzDO9R1vb28jNjbW6fFt2rQxAgMDjZMnTzr2bdu2zbBarca4ceMc+3L764EDBwzDyPkufH19jbvvvtvp+Y4dO2b4+Pg47e/atatRrVo149ChQ05t8/aZV155xen5c73xxhuGJCMuLu6in8X5cj/HTZs2OfYdOnTI8PLyMoYMGeLYN3nyZMPT09OpX8TGxhpubm5Of1cX8uqrrxqSDH9/f6NTp06O93bnnXcawcHBxokTJ5zajxw50vDx8TFSU1MNw8j5+0xPT3dqEx8fb9SsWdO44447HPsu9F0CAAAAxbVp0yZDkrFq1SrDMHJ+o9euXdt4+OGHHW1WrlxpSDKWLFni9NibbrrJqF+/vmN77ty5htVqdTqGMwzDmDlzpiHJ+PXXXx37JBlWq9X466+/8mXK/Y2cKyMjw2jRooXRvXt3x77NmzcbkoyJEyc6tR0/fny+4+Oi/iYvyCOPPGJIMiIjI532p6enOx0P5n3uSznuzP2dP3XqVCMuLs44duyY8fPPPxvXXHONIcn4/PPPnZ4r9/j6/H9hYWGFvpdc119/fYGPzT0ncP6xX67c49zVq1fne645c+Y4fTZBQUHGLbfc4tg3ffp0Q5KxaNEix76UlBSjYcOG+Z7ztttuc3ofuZ9N9erVjVOnTjn2f/PNN/n6ZcuWLY3atWsbycnJjn1r1qwp8mcTFhZmSDK++OILx77ExEQjODjYCA8Pd+x77rnnjCpVqhh79uxxevwTTzxh2Gw24/Dhw07Zi3P85urH+IXp3Lmz0bZt23z7c/vd559/bixdutSwWCyOz/exxx5z/D/o/HNohpHzWRZ0rutC/c0w8p9jGzx4sOHh4WHs37/fsS8mJsaoVq2a0bVrV8e+3M+0Z8+eTp/FI488YthsNsf/E7766ivH+cDiqlmzpjF69GhH9rzvpSDz5883JBkbN24s9msBwOVgKnUAwAXVr19fY8eO1axZs3T06NESe9677rrLcdtms6ldu3YyDEN33nmnY7+vr68aN26sf/75J9/jx40bp2rVqjm2hw4dquDgYC1fvlySFBkZqb179+rWW2/VyZMndeLECZ04cUIpKSnq0aOH1q1b5zSNmKRC18M63/Lly9W+fXun6darVq2qCRMm6ODBg5c0dXRSUpLjefKaOXOmAgICHP/yvmZSUlKBV80/+eSTTo+59dZb87W54447FBAQoJCQEPXp00eJiYmaO3eurrnmmnxtvby8tGrVKqd/hU1xf77vv//ekaN169b6/PPPNXbsWL388stO7W655RanK7SPHj2qyMhIjR8/3umK9VatWunGG290fM8FWbVqlRISEjRq1CjH937ixAnZbDZde+21jinA4+LitG7dOt1xxx2qU6eO03NcaNr7XLnrY33zzTf5+lJRdOzYUW3btnVs16lTR4MGDdLKlSsd68KPGzdO6enpTtMzfvbZZ8rKyiryKI+JEyeqVatWSkhI0Pvvv++Y4v+LL77QgAEDZBiG0+fUu3dvJSYmasuWLZJy/j5zR9/Y7XadOnVKWVlZateunaNNXud/lwAAAMCliIiIUM2aNXXDDTdIyvmNPmLECC1cuNDxe7l79+6qUaOGY7SjlDNKeNWqVRoxYoRj3+eff66mTZuqSZMmTr99u3fvLkn5lgm6/vrr1axZs3yZcmcny32dxMREdenSxel3ce6063mnMJdyRmrmVZzf5AUp7Bhy+fLlTseDeUe5XspxZ64pU6YoICBAQUFB6tKli3bt2qXXXntNQ4cOLTDfF1984XQMmXca/AupW7duvuPPxx9/vEiPPV/VqlWdjps8PDzUvn17p3MMy5cvV3BwsNP7qFy5siZMmFDk1xkxYoTTaPjcaeZzXycmJkZ//vmnxo0b5/TZX3/99WrZsmWRXyckJMRpNjFvb2+NGzdOW7du1bFjxyTl9PUuXbrIz8/PqU/17NlT2dnZTst3ScU/fnPlY/zCnDx58qKzHfTq1Uv+/v5auHChDMPQwoULNWrUqEt+zaLIzs7W999/r8GDB6t+/fqO/cHBwbr11lv1yy+/OP7mc02YMMHps+jSpYuys7N16NAhSefOcyxdulSZmZnFynP77bc7po/fuXOnYmJiLtg+9zM9f4YIAChtTKUOALiop556SnPnztW0adMcaxNfrvMPUnx8fOTl5eWYxirv/pMnT+Z7/FVXXeW0bbFY1LBhQ8d0bnv37pUk3XbbbYVmSExMdDq4qVevXpGyHzp0KN90VJLUtGlTx/0tWrQo0nPlyi3ynz592mmK8ltuucXxXI8++qjjBFDuYwr6bP71r3+pf//+kgqfIu/pp59Wly5ddPr0aX311VdauHChrNaCr5ez2WyFrqV1Mddee62ef/55WSwWVa5cWU2bNnUcaOV1/mefe1DWuHHjfG2bNm2qlStXKiUlRVWqVMl3f+53n3uS63y5U3TlnqQo7neVa8SIEfrwww9111136YknnlCPHj108803a+jQoYV+lnmd34clqVGjRkpNTVVcXJyCgoLUpEkTXXPNNYqIiHBcNBIREaEOHTqoYcOGRcpps9kUHh6u/fv3q3nz5pJyThgkJCRo1qxZmjVrVoGPy12XXJI+/fRTvfbaa9q9e7fTwXFBfzNF/TsCAAAACpOdna2FCxfqhhtucKxdLOUcX7z22mv68ccf1atXL7m5uemWW27R/PnzlZ6eLk9PT3355ZfKzMx0Kozv3btXu3btKrQAmPe3r1T4b9qlS5fq+eefV2RkpNMa1HkLTYcOHZLVas33HOf/fi/ub/Lz5T2GzKtTp05atWqVJOmVV15xWurpUo47c02YMEHDhg1TWlqafvrpJ7311lsFtsvVtWvXfMf3RVGlSpVLPv48X+3atfMVRP38/Jymtj506JAaNmyYr11Bx6KFOf/8Ru55hvj4eMdrSPn7QO6+C10AcX7b83M2atRIUs7U9kFBQdq7d6+2b99+2X29MK58jH8hxgWW25NylpsbNmyY5s+fr/bt2ysqKqrAQQolKS4uTqmpqYV+pna7XVFRUY7zANLF++r111+vW265RVOnTtUbb7yhbt26afDgwbr11lvl6el5wTwvvPCC6tatqw8//FBbtmzR6NGjNWnSJD366KN69NFH850nyf1ML+eiBQC4FBTGAQAXVb9+fY0ZM0azZs3SE088ke/+wn7EXugg2WazFWmfdPEDkILkjuB95ZVX8q2BnOv8q+TzXv1/pTVp0kSStGPHDnXq1MmxPzQ0VKGhoZLkuOI772MiIyMVHR3ttC5Zo0aNHAfHXl5eBb5ey5YtHScbBg8erNTUVN19993q3Lmz4/VKQo0aNYp0UqMkP/vc737u3LkKCgrKd7+bW8n8/KlUqZLWrVun1atXa9myZVqxYoU+++wzde/eXd9//32h/bm4xo0bp4cfflhHjhxRenq6NmzYoHfeeeeynjP3MxozZkyhF4+0atVKkjRv3jyNHz9egwcP1mOPPabAwEDZbDa99NJL2r9/f77Hmfl3BAAAANfw008/6ejRo1q4cKEWLlyY7/6IiAj16tVLkjRy5Ei9//77+u677zR48GAtWrRITZo0UevWrR3t7Xa7WrZsqddff73A1zv/GKig37Q///yzBg4cqK5du2rGjBkKDg6Wu7u7Zs+erfnz5xf7PRbnN3lB8h5D5n2vAQEBjmOwefPmFfqYoh535rrqqqscz9u/f3/ZbDY98cQTuuGGG9SuXbsLv9kSUtxzDyV5juFCrtTrFIXdbteNN95Y6Cj73HMFuYp7/ObKx/iFqV69uqNwfCG33nqrZs6cqWeeeUatW7cucNYJs12sr1osFi1evFgbNmzQkiVLtHLlSt1xxx167bXXtGHDhgJnLcxltVp1zz336J577tH48ePVpEkTbdmyRY8//riys7PznU/M/Uwv5QIaALgcFMYBAEXy1FNPad68efmmx5LOXWGakJDgtD/3iuDSkHvFcC7DMLRv3z7HiYMGDRpIyrlyuKSuNs8VFhamv//+O9/+3bt3O+4vrv79+2vatGmKiIhwOkFxsccsXLhQERERlzy1XK5p06bpq6++0gsvvKCZM2de1nOVhNzPsLDPuUaNGgVeSS6d++4DAwMv+N3nTjW2Y8eOC2a50NXLVqtVPXr0UI8ePfT666/rxRdf1JN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      "text/plain": [
       "<Figure size 2000x1500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Key metrics by period:\n",
      "     Total Program GGRFFunding                          \\\n",
      "                         count         sum        mean   \n",
      "Year                                                     \n",
      "2011                         1       11500    11500.00   \n",
      "2012                        98     2328417    23759.36   \n",
      "2013                      3379    50726172    15012.18   \n",
      "2014                      7281    76042854    10444.01   \n",
      "2015                      6235    61034095     9788.95   \n",
      "2016                      8001   105685277    13209.01   \n",
      "2017                     12745   368260901    28894.54   \n",
      "2018                     18071   641426028    35494.77   \n",
      "2019                     21131  1131373505    53540.94   \n",
      "2020                     18281  1555581678    85092.81   \n",
      "2021                     15957  1147697486    71924.39   \n",
      "2022                     12906  1187728536    92029.18   \n",
      "2023                      6825  1114799921   163340.65   \n",
      "2024                       517   686268968  1327406.13   \n",
      "\n",
      "     Is Benefit Disadvantaged Communities is_multi_county        \\\n",
      "                                     mean           count  mean   \n",
      "Year                                                              \n",
      "2011                                 1.00               1  0.00   \n",
      "2012                                 0.29              98  0.00   \n",
      "2013                                 0.28            3379  0.00   \n",
      "2014                                 0.40            7281  0.00   \n",
      "2015                                 0.48            6235  0.01   \n",
      "2016                                 0.59            8001  0.00   \n",
      "2017                                 0.45           12745  0.00   \n",
      "2018                                 0.44           18071  0.00   \n",
      "2019                                 0.35           21131  0.00   \n",
      "2020                                 0.30           18281  0.01   \n",
      "2021                                 0.27           15957  0.01   \n",
      "2022                                 0.23           12906  0.01   \n",
      "2023                                 0.00            6825  0.01   \n",
      "2024                                 0.00             517  0.07   \n",
      "\n",
      "     partnership_size  \n",
      "                 mean  \n",
      "Year                   \n",
      "2011             1.00  \n",
      "2012             1.00  \n",
      "2013             1.00  \n",
      "2014             1.00  \n",
      "2015             1.02  \n",
      "2016             1.00  \n",
      "2017             1.01  \n",
      "2018             1.01  \n",
      "2019             1.01  \n",
      "2020             1.06  \n",
      "2021             1.02  \n",
      "2022             1.03  \n",
      "2023             1.03  \n",
      "2024             1.32  \n"
     ]
    }
   ],
   "source": [
    "# Temporal analysis of GGRF funding\n",
    "temporal = data.groupby('Year').agg({\n",
    "   'Total Program GGRFFunding': ['count', 'sum', 'mean'],\n",
    "   'Is Benefit Disadvantaged Communities': 'mean',\n",
    "   'is_multi_county': ['count', 'mean'],\n",
    "   'partnership_size': 'mean'\n",
    "}).round(2)\n",
    "\n",
    "# Visualize key metrics\n",
    "fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(20, 15))\n",
    "\n",
    "# Projects per year\n",
    "ax1.plot(temporal.index, temporal[('Total Program GGRFFunding', 'count')], \n",
    "        marker='o', linewidth=2)\n",
    "ax1.set_title('Number of GGRF Projects by Year')\n",
    "ax1.grid(True, alpha=0.3)\n",
    "\n",
    "# Average funding per project\n",
    "ax2.plot(temporal.index, temporal[('Total Program GGRFFunding', 'mean')]/1e6,\n",
    "        marker='o', linewidth=2)\n",
    "ax2.set_title('Average GGRF Funding per Project (Millions $)')\n",
    "ax2.grid(True, alpha=0.3)\n",
    "\n",
    "# DAC benefit rate\n",
    "ax3.plot(temporal.index, temporal[('Is Benefit Disadvantaged Communities', 'mean')],\n",
    "        marker='o', linewidth=2)\n",
    "ax3.set_title('DAC Benefit Rate')\n",
    "ax3.grid(True, alpha=0.3)\n",
    "\n",
    "# Multi-county projects\n",
    "ax4.plot(temporal.index, temporal[('partnership_size', 'mean')],\n",
    "        marker='o', linewidth=2)\n",
    "ax4.set_title('Average Number of Partner Counties')\n",
    "ax4.grid(True, alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(\"Key metrics by period:\")\n",
    "print(temporal)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2024 Projects by Program:\n",
      "                                                   Total Program GGRFFunding  \\\n",
      "                                                                       count   \n",
      "Program Name                                                                   \n",
      "Affordable Housing and Sustainable Communities ...                         8   \n",
      "Climate Adaptation and Resiliency Program                                  1   \n",
      "Community Air Protection                                                 220   \n",
      "Fire Prevention Program                                                   12   \n",
      "Fluorinated Gases Emission Reduction Incentives                           15   \n",
      "Food Production Investment Program                                        30   \n",
      "Forest Carbon Plan Implementation                                          5   \n",
      "Forest Health Program                                                     20   \n",
      "Low Carbon Transit Operations Program                                     18   \n",
      "Low Carbon Transportation                                                  4   \n",
      "Safe and Affordable Drinking Water Fund                                   10   \n",
      "Transformative Climate Communities                                        10   \n",
      "Transit and Intercity Rail Capital Program                                29   \n",
      "Urban and Community Forestry Program                                     132   \n",
      "Waste Diversion                                                            1   \n",
      "Wetlands and Watershed Restoration                                         2   \n",
      "\n",
      "                                                                            \n",
      "                                                          sum         mean  \n",
      "Program Name                                                                \n",
      "Affordable Housing and Sustainable Communities ...  176615877  22076984.62  \n",
      "Climate Adaptation and Resiliency Program              299000    299000.00  \n",
      "Community Air Protection                             80955408    367979.13  \n",
      "Fire Prevention Program                               7806649    650554.08  \n",
      "Fluorinated Gases Emission Reduction Incentives       1000001     66666.73  \n",
      "Food Production Investment Program                   70824290   2360809.67  \n",
      "Forest Carbon Plan Implementation                     1108131    221626.20  \n",
      "Forest Health Program                                57230331   2861516.55  \n",
      "Low Carbon Transit Operations Program                11165512    620306.22  \n",
      "Low Carbon Transportation                            10744732   2686183.00  \n",
      "Safe and Affordable Drinking Water Fund              10457866   1045786.60  \n",
      "Transformative Climate Communities                   38277301   3827730.10  \n",
      "Transit and Intercity Rail Capital Program          189696000   6541241.38  \n",
      "Urban and Community Forestry Program                 18561997    140621.19  \n",
      "Waste Diversion                                       3950527   3950527.00  \n",
      "Wetlands and Watershed Restoration                    7575346   3787673.00  \n",
      "\n",
      "Largest 2024 Projects:\n",
      "                                             Program Name         County  \\\n",
      "117879         Transit and Intercity Rail Capital Program        Alameda   \n",
      "90922          Transit and Intercity Rail Capital Program    Los Angeles   \n",
      "136661  Affordable Housing and Sustainable Communities...    Los Angeles   \n",
      "141400  Affordable Housing and Sustainable Communities...  San Francisco   \n",
      "100763  Affordable Housing and Sustainable Communities...  San Francisco   \n",
      "\n",
      "        Total Program GGRFFunding Date Operational  \n",
      "117879                  107100000       2024-03-01  \n",
      "90922                    40000000       2024-09-23  \n",
      "136661                   29889806       2024-04-01  \n",
      "141400                   29269952       2024-08-01  \n",
      "100763                   25424799       2024-01-01  \n"
     ]
    }
   ],
   "source": [
    "print(\"2024 Projects by Program:\")\n",
    "print(data[data['Year'] == 2024].groupby('Program Name').agg({\n",
    "    'Total Program GGRFFunding': ['count', 'sum', 'mean']\n",
    "}).round(2))\n",
    "\n",
    "print(\"\\nLargest 2024 Projects:\")\n",
    "print(data[data['Year'] == 2024].nlargest(5, 'Total Program GGRFFunding')[\n",
    "    ['Program Name', 'County', 'Total Program GGRFFunding', 'Date Operational']\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2023 vs 2024 Program Comparison:\n",
      "                                                        Total Program GGRFFunding  \\\n",
      "                                                                            count   \n",
      "Year Program Name                                                                   \n",
      "2023 Affordable Housing and Sustainable Communities ...                        20   \n",
      "     Climate Adaptation and Resiliency Program                                  6   \n",
      "     Climate Change Research Program                                            3   \n",
      "     Climate Ready Program                                                      4   \n",
      "     Climate Resilience Planning                                               36   \n",
      "     Climate Smart Agriculture                                                363   \n",
      "     Community Air Protection                                                1926   \n",
      "     Fire Prevention Program                                                   11   \n",
      "     Food Production Investment Program                                        20   \n",
      "     Forest Carbon Plan Implementation                                         83   \n",
      "     Forest Health Program                                                     27   \n",
      "     Funding Agricultural Replacement Measures for E...                       539   \n",
      "     Low Carbon Transit Operations Program                                     99   \n",
      "     Low Carbon Transportation                                               3187   \n",
      "     Low-Income Weatherization Program                                         26   \n",
      "     SB 1383 Local Assistance Grant Program                                    12   \n",
      "     Safe and Affordable Drinking Water Fund                                   22   \n",
      "     Sustainable Agricultural Lands Conservation Pro...                        15   \n",
      "     Training and Workforce Development Program                               136   \n",
      "     Transformative Climate Communities                                       142   \n",
      "     Transit and Intercity Rail Capital Program                                14   \n",
      "     Urban Greening Program                                                    42   \n",
      "     Waste Diversion                                                           18   \n",
      "     Water-Energy Efficiency                                                   51   \n",
      "     Wetlands and Watershed Restoration                                         1   \n",
      "     Woodsmoke Reduction Program                                               22   \n",
      "2024 Affordable Housing and Sustainable Communities ...                         8   \n",
      "     Climate Adaptation and Resiliency Program                                  1   \n",
      "     Community Air Protection                                                 220   \n",
      "     Fire Prevention Program                                                   12   \n",
      "     Fluorinated Gases Emission Reduction Incentives                           15   \n",
      "     Food Production Investment Program                                        30   \n",
      "     Forest Carbon Plan Implementation                                          5   \n",
      "     Forest Health Program                                                     20   \n",
      "     Low Carbon Transit Operations Program                                     18   \n",
      "     Low Carbon Transportation                                                  4   \n",
      "     Safe and Affordable Drinking Water Fund                                   10   \n",
      "     Transformative Climate Communities                                        10   \n",
      "     Transit and Intercity Rail Capital Program                                29   \n",
      "     Urban and Community Forestry Program                                     132   \n",
      "     Waste Diversion                                                            1   \n",
      "     Wetlands and Watershed Restoration                                         2   \n",
      "\n",
      "                                                                    \\\n",
      "                                                               sum   \n",
      "Year Program Name                                                    \n",
      "2023 Affordable Housing and Sustainable Communities ...  334283890   \n",
      "     Climate Adaptation and Resiliency Program             3374200   \n",
      "     Climate Change Research Program                        396119   \n",
      "     Climate Ready Program                                 4368244   \n",
      "     Climate Resilience Planning                           5041046   \n",
      "     Climate Smart Agriculture                            43068601   \n",
      "     Community Air Protection                             45727103   \n",
      "     Fire Prevention Program                               9456431   \n",
      "     Food Production Investment Program                   42815128   \n",
      "     Forest Carbon Plan Implementation                    22524961   \n",
      "     Forest Health Program                                37902075   \n",
      "     Funding Agricultural Replacement Measures for E...   40805691   \n",
      "     Low Carbon Transit Operations Program               114507056   \n",
      "     Low Carbon Transportation                           169989768   \n",
      "     Low-Income Weatherization Program                     4226240   \n",
      "     SB 1383 Local Assistance Grant Program                5969666   \n",
      "     Safe and Affordable Drinking Water Fund              11621901   \n",
      "     Sustainable Agricultural Lands Conservation Pro...   24711311   \n",
      "     Training and Workforce Development Program            7332437   \n",
      "     Transformative Climate Communities                   40263894   \n",
      "     Transit and Intercity Rail Capital Program          118568000   \n",
      "     Urban Greening Program                               26722800   \n",
      "     Waste Diversion                                        213843   \n",
      "     Water-Energy Efficiency                                 73165   \n",
      "     Wetlands and Watershed Restoration                     743216   \n",
      "     Woodsmoke Reduction Program                             93135   \n",
      "2024 Affordable Housing and Sustainable Communities ...  176615877   \n",
      "     Climate Adaptation and Resiliency Program              299000   \n",
      "     Community Air Protection                             80955408   \n",
      "     Fire Prevention Program                               7806649   \n",
      "     Fluorinated Gases Emission Reduction Incentives       1000001   \n",
      "     Food Production Investment Program                   70824290   \n",
      "     Forest Carbon Plan Implementation                     1108131   \n",
      "     Forest Health Program                                57230331   \n",
      "     Low Carbon Transit Operations Program                11165512   \n",
      "     Low Carbon Transportation                            10744732   \n",
      "     Safe and Affordable Drinking Water Fund              10457866   \n",
      "     Transformative Climate Communities                   38277301   \n",
      "     Transit and Intercity Rail Capital Program          189696000   \n",
      "     Urban and Community Forestry Program                 18561997   \n",
      "     Waste Diversion                                       3950527   \n",
      "     Wetlands and Watershed Restoration                    7575346   \n",
      "\n",
      "                                                        Is Benefit Disadvantaged Communities  \n",
      "                                                                                        mean  \n",
      "Year Program Name                                                                             \n",
      "2023 Affordable Housing and Sustainable Communities ...                                 0.00  \n",
      "     Climate Adaptation and Resiliency Program                                          0.00  \n",
      "     Climate Change Research Program                                                    0.00  \n",
      "     Climate Ready Program                                                              0.00  \n",
      "     Climate Resilience Planning                                                        0.00  \n",
      "     Climate Smart Agriculture                                                          0.00  \n",
      "     Community Air Protection                                                           0.00  \n",
      "     Fire Prevention Program                                                            0.00  \n",
      "     Food Production Investment Program                                                 0.00  \n",
      "     Forest Carbon Plan Implementation                                                  0.00  \n",
      "     Forest Health Program                                                              0.00  \n",
      "     Funding Agricultural Replacement Measures for E...                                 0.00  \n",
      "     Low Carbon Transit Operations Program                                              0.00  \n",
      "     Low Carbon Transportation                                                          0.00  \n",
      "     Low-Income Weatherization Program                                                  0.00  \n",
      "     SB 1383 Local Assistance Grant Program                                             0.00  \n",
      "     Safe and Affordable Drinking Water Fund                                            0.00  \n",
      "     Sustainable Agricultural Lands Conservation Pro...                                 0.00  \n",
      "     Training and Workforce Development Program                                         0.00  \n",
      "     Transformative Climate Communities                                                 0.00  \n",
      "     Transit and Intercity Rail Capital Program                                         0.36  \n",
      "     Urban Greening Program                                                             0.00  \n",
      "     Waste Diversion                                                                    0.00  \n",
      "     Water-Energy Efficiency                                                            0.06  \n",
      "     Wetlands and Watershed Restoration                                                 0.00  \n",
      "     Woodsmoke Reduction Program                                                        0.00  \n",
      "2024 Affordable Housing and Sustainable Communities ...                                 0.00  \n",
      "     Climate Adaptation and Resiliency Program                                          0.00  \n",
      "     Community Air Protection                                                           0.00  \n",
      "     Fire Prevention Program                                                            0.00  \n",
      "     Fluorinated Gases Emission Reduction Incentives                                    0.00  \n",
      "     Food Production Investment Program                                                 0.00  \n",
      "     Forest Carbon Plan Implementation                                                  0.00  \n",
      "     Forest Health Program                                                              0.00  \n",
      "     Low Carbon Transit Operations Program                                              0.00  \n",
      "     Low Carbon Transportation                                                          0.00  \n",
      "     Safe and Affordable Drinking Water Fund                                            0.00  \n",
      "     Transformative Climate Communities                                                 0.00  \n",
      "     Transit and Intercity Rail Capital Program                                         0.00  \n",
      "     Urban and Community Forestry Program                                               0.00  \n",
      "     Waste Diversion                                                                    0.00  \n",
      "     Wetlands and Watershed Restoration                                                 0.00  \n",
      "\n",
      "Percent Changes 2023-2024:\n",
      "       Total Program GGRFFunding  Is Benefit Disadvantaged Communities\n",
      "count                     -92.42                                   NaN\n",
      "sum                       -38.44                                   NaN\n",
      "mean                      712.66                                -100.0\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# Compare 2023 vs 2024 by program\n",
    "years_comparison = data[data['Year'].isin([2023, 2024])].groupby(['Year', 'Program Name']).agg({\n",
    "    'Total Program GGRFFunding': ['count', 'sum'],\n",
    "    'Is Benefit Disadvantaged Communities': 'mean'\n",
    "}).round(2)\n",
    "\n",
    "print(\"2023 vs 2024 Program Comparison:\")\n",
    "print(years_comparison)\n",
    "\n",
    "# Calculate percent changes in key metrics\n",
    "print(\"\\nPercent Changes 2023-2024:\")\n",
    "metrics_2023 = data[data['Year'] == 2023].agg({\n",
    "    'Total Program GGRFFunding': ['count', 'sum', 'mean'],\n",
    "    'Is Benefit Disadvantaged Communities': 'mean'\n",
    "})\n",
    "\n",
    "metrics_2024 = data[data['Year'] == 2024].agg({\n",
    "    'Total Program GGRFFunding': ['count', 'sum', 'mean'],\n",
    "    'Is Benefit Disadvantaged Communities': 'mean'\n",
    "})\n",
    "\n",
    "pct_change = ((metrics_2024 - metrics_2023) / metrics_2023 * 100).round(2)\n",
    "print(pct_change)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2023-2024 Changes (excluding Low Carbon Transportation):\n",
      "                                                    2023          2024\n",
      "Total Program GGRFFunding            count  3.638000e+03  5.130000e+02\n",
      "                                     sum    9.448102e+08  6.755242e+08\n",
      "                                     mean   2.597059e+05  1.316811e+06\n",
      "Is Benefit Disadvantaged Communities mean   0.000000e+00  0.000000e+00\n",
      "is_multi_county                      count  3.638000e+03  5.130000e+02\n",
      "                                     mean   2.000000e-02  7.000000e-02\n",
      "partnership_size                     mean   1.050000e+00  1.320000e+00\n"
     ]
    }
   ],
   "source": [
    "# Filter out Low Carbon Transportation\n",
    "data_filtered = data[data['Program Name'] != 'Low Carbon Transportation'].copy()\n",
    "\n",
    "# Recalculate temporal analysis\n",
    "temporal_filtered = data_filtered.groupby('Year').agg({\n",
    "   'Total Program GGRFFunding': ['count', 'sum', 'mean'],\n",
    "   'Is Benefit Disadvantaged Communities': 'mean',\n",
    "   'is_multi_county': ['count', 'mean'],\n",
    "   'partnership_size': 'mean'\n",
    "}).round(2)\n",
    "\n",
    "# Compare 2023-2024 without LCT\n",
    "years_comparison = data_filtered[data_filtered['Year'].isin([2023, 2024])].groupby(['Year', 'Program Name']).agg({\n",
    "   'Total Program GGRFFunding': ['count', 'sum'],\n",
    "   'Is Benefit Disadvantaged Communities': 'mean'\n",
    "}).round(2)\n",
    "\n",
    "print(\"2023-2024 Changes (excluding Low Carbon Transportation):\")\n",
    "changes = pd.DataFrame({\n",
    "   '2023': temporal_filtered.loc[2023],\n",
    "   '2024': temporal_filtered.loc[2024]\n",
    "})\n",
    "print(changes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 2000x1500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(20, 15))\n",
    "\n",
    "# Projects count \n",
    "ax1.plot(temporal_filtered.index, \n",
    "         temporal_filtered[('Total Program GGRFFunding', 'count')],\n",
    "         marker='o', linewidth=2)\n",
    "ax1.set_title('Number of Projects (Excluding LCT)')\n",
    "ax1.grid(True, alpha=0.3)\n",
    "\n",
    "# Average funding\n",
    "ax2.plot(temporal_filtered.index,\n",
    "         temporal_filtered[('Total Program GGRFFunding', 'mean')]/1e6,\n",
    "         marker='o', linewidth=2)\n",
    "ax2.set_title('Average Project Funding (Millions $)')\n",
    "ax2.grid(True, alpha=0.3)\n",
    "\n",
    "# Total funding\n",
    "ax3.plot(temporal_filtered.index,\n",
    "         temporal_filtered[('Total Program GGRFFunding', 'sum')]/1e9,\n",
    "         marker='o', linewidth=2)\n",
    "ax3.set_title('Total GGRF Funding (Billions $)')\n",
    "ax3.grid(True, alpha=0.3)\n",
    "\n",
    "# Partnership size\n",
    "ax4.plot(temporal_filtered.index,\n",
    "         temporal_filtered[('partnership_size', 'mean')],\n",
    "         marker='o', linewidth=2)\n",
    "ax4.set_title('Average Number of Partner Counties')\n",
    "ax4.grid(True, alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "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": "3.12.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}