2740 lines
1.6 MiB
2740 lines
1.6 MiB
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Project: California Equity Research\n",
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"### Data: postgis db `calif_equity` with california climate investment and california enviroscreen data\n",
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"#### Goal: Analyze the relationship between climate investment and environmental justice in California\n",
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"#### This notebook: second take \n",
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"##### Author: [dpadams](dpadams@fullerton.edu)\n",
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"##### Date: 2024-11-24"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Importing the necessary libraries\n",
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"import pandas as pd\n",
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"import seaborn as sns\n",
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"import os"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"## set directory\n",
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"import os\n",
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"os.chdir('/home/dadams/Repos/california_equity_git')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"# read in the data\n",
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"data = pd.read_csv('data_raw/cci_programs_data.csv', low_memory=False)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"Index(['Project IDNumber', 'Reporting Cycle Name', 'Agency Name',\n",
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" 'Program Name', 'Program Description', 'Sub Program Name',\n",
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" 'Record Type', 'Project Name', 'Project Type', 'Project Description',\n",
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" ...\n",
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" 'Net Density DUA', 'Applicants Assisted', 'Invasive Cover 12 Months',\n",
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" 'Invasive Cover 36 Months', 'Project Acreage', 'IS IAE',\n",
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" 'Intermediary Admin Expenses Calc', 'PRIMARY_FUNDING_RECIPIENT_TYPE',\n",
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" 'TRIBAL AFFILIATION', 'PROJECT PARTNERS'],\n",
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" dtype='object', length=127)"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"data.columns"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" Tract ZIP County ApproxLoc TotPop19 CIscore \\\n",
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"0 6.083002e+09 93454 Santa Barbara Santa Maria 4495 36.019653 \n",
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"1 6.083002e+09 93455 Santa Barbara Santa Maria 13173 37.030667 \n",
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"2 6.083002e+09 93454 Santa Barbara Santa Maria 2398 31.213140 \n",
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"3 6.083002e+09 93455 Santa Barbara Orcutt 4496 6.639331 \n",
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"4 6.083002e+09 93455 Santa Barbara Orcutt 4008 14.022852 \n",
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"\n",
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" CIscoreP Ozone OzoneP PM2_5 ... Elderly65 Hispanic \\\n",
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"0 69.162885 0.034190 10.566273 7.567724 ... 12.5028 68.9210 \n",
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"1 70.637922 0.035217 11.561917 7.624775 ... 5.3519 78.6229 \n",
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"2 61.069087 0.034190 10.566273 7.548835 ... 12.8857 65.7214 \n",
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"3 5.988401 0.036244 13.615432 7.660570 ... 14.4128 22.9537 \n",
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"4 23.121533 0.036244 13.615432 7.663210 ... 18.8872 33.4082 \n",
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"\n",
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" White AfricanAm NativeAm OtherMult Shape_Leng Shape_Area \\\n",
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"0 20.8899 0.4004 0.2670 1.3126 6999.357689 2.847611e+06 \n",
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"1 13.2240 2.5051 0.0000 0.9489 19100.578232 1.635292e+07 \n",
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"2 30.6088 0.9591 0.0000 2.1685 4970.985897 1.352329e+06 \n",
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"3 69.1948 0.9342 0.7117 2.5356 6558.956012 2.417717e+06 \n",
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"4 59.7804 0.6986 1.4721 1.3723 6570.368730 2.608422e+06 \n",
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"\n",
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" AAPI geometry \n",
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"0 8.2091 POLYGON ((-39795.07 -341919.191, -38126.384 -3... \n",
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"1 4.6990 POLYGON ((-39795.07 -341919.191, -39803.632 -3... \n",
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"2 0.5421 POLYGON ((-38115.747 -341130.248, -38126.384 -... \n",
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"3 3.6699 POLYGON ((-37341.662 -348530.437, -37252.307 -... \n",
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"4 3.2685 POLYGON ((-39465.107 -348499.262, -38244.305 -... \n",
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"\n",
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"[5 rows x 67 columns]\n"
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]
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}
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],
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"source": [
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"import geopandas as gpd\n",
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"\n",
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"# Load the shapefile\n",
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"shapefile_path = '/home/dadams/Repos/california_equity_git/california_enviroscreen/calif_enviroscreen_shape/CES4 Final Shapefile.shp'\n",
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"gdf = gpd.read_file(shapefile_path)\n",
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"\n",
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"# Print the head of the GeoDataFrame\n",
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"print(gdf.head())"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Total GGRF Funding: $8.13B\n",
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"Number of projects: 131428\n"
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]
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}
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],
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"source": [
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"import pandas as pd\n",
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"\n",
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"# Basic cleaning\n",
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"data['Date Operational'] = pd.to_datetime(data['Date Operational'])\n",
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"data = data[\n",
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" (data['Date Operational'] >= '2010-01-01') & \n",
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" (data['Date Operational'] <= '2024-11-01')\n",
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"].copy()\n",
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"\n",
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"# Remove rows with no GGRF funding\n",
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"data = data.dropna(subset=['Total Program GGRFFunding'])\n",
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"\n",
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"# Add derived columns\n",
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"data['Year'] = data['Date Operational'].dt.year\n",
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"data['is_multi_county'] = data['County'].str.contains(',', na=False)\n",
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"data['partnership_size'] = data['County'].str.count(',').fillna(0) + 1\n",
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"\n",
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"# Quick validation\n",
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"print(f\"Total GGRF Funding: ${data['Total Program GGRFFunding'].sum()/1e9:.2f}B\")\n",
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"print(f\"Number of projects: {len(data)}\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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"data": {
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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": 9,
|
|
"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": 10,
|
|
"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": 11,
|
|
"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": 12,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
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jjz+qX79+Zc4/29w+KSnJef3g8ccfV0BAgPbv3++8pnEmS5cu1cSJE50t/C+99FINGjTIuS3B6fr06aMvv/xSGRkZ8vPzO/8PAwAaKwMA0CjNmTPHkGSsX7/eiI2NNVxcXIwHHnjA+fjll19udOnSxXk/Pj7ekGTMmTOn3GtJMqZPn+68P336dEOSMWXKFOexoqIio2XLlobFYjFefPFF5/ETJ04Ynp6exoQJE5zHVq5caUgyWrRoYWRkZDiPL1q0yJBkvPbaa4ZhGIbD4TDat29vxMTEGA6Hw3leTk6O0bZtW+Oqq64qV9PYsWOr9PlMmzbNkGT8/PPPzmOZmZlG27ZtjTZt2hh2u73M+586dWqVXleSMXnyZCM5OdlISkoyfv31V2Pw4MGGJOPll18u8/6joqKMnJwc53MLCgqM0NBQo2vXrkZubq7z+FdffWVIMv72t7+Ve78l9u/fb9hsNuP5558vU8+2bdsMFxcX5/GioiKjbdu2RmRkpHHixIky55b+jKdOnWpU9GfCgw8+aPj5+RlFRUVV+jxK7Nu3z5BkvPHGG+UemzBhgiGpwv9iYmLKnDt79mxDkjFv3jzjl19+MWw2mzFt2jTn41V9f6d/ftUZ/6NGjTI8PDyMAwcOOI/t3LnTsNls5T6zyMjIMmO/5N/lkCFDytTz0EMPGTabzUhLSzMMwzCOHTtmuLi4GKNGjSrzejNmzDAklXnNypxt3L722muGJOPzzz8/62ud7qWXXjIkGfHx8ZWes3btWkOS8fHHH1f79QEAAICGYMOGDYYkY8WKFYZhFM85WrZsaTz44IPOc5YvX25IMpYsWVLmuVdffbURFRXlvP/hhx8aVqu1zBzVMAzj7bffNiQZa9ascR6TZFitVmPHjh3laio9xzSM4nlm165djSuvvNJ5bOPGjYakMnMpwzCMiRMnlpv/TJ482YiIiDBSUlLKnHvzzTcb/v7+5X7e6SIjI42hQ4caycnJRnJysrF161bj5ptvNiQZ999/v2EYp+Zjfn5+RlJSUpnn9+zZ0wgNDTWOHz/uPLZ161bDarUat912m/NYyVyrZI6SmZlpBAQEGHfeeWeZ1zt27Jjh7+9f5vhll11m+Pr6lpnjGUbZOWRV5kClVTbPvfzyyw3DOHVdYOXKlWWeV9HctOS1nnnmmTLn9urVy+jTp4/z/hdffGFIMv75z386jxUVFRmXXnppudc8fU5sGMXjys3Nzdi3b5/z2NatW8vN5UeOHGl4eXkZR44ccR7bu3ev4eLiUuF1hNMNHDiwTN0lSj6TTz75xPjqq68Mi8ViHDx40DAMw/jLX/7i/Pdy+vUswyg/967o850wYYIRGRlZ7j2fPt93c3MzYmNjnceOHj1q+Pr6GpdddpnzWFXn9p9//rnz2lx1hYWFGbfeequz9tPHyukWLFhgSDJ+/fXXav8sAGhKaKUOAE1AVFSUxo8fr3feeUcJCQk19rp33HGH87bNZlPfvn1lGIYmT57sPB4QEKAOHTooLi6u3PNvu+02+fr6Ou/fcMMNioiI0Ndffy1J2rJli/bu3atbbrlFx48fV0pKilJSUpSdna3Bgwfrp59+ksPhKPOale1Pdrqvv/5aF110UZl26z4+PpoyZYr279/vbNl2Lt5//32FhIQoNDRU/fr1c7bWOv2b9BMmTHCujJeK22slJSXp3nvvLbPP1YgRI9SxY8cybd5Pt3jxYjkcDo0ZM8b5OaWkpCg8PFzt27fXypUrJRV/szs+Pl7Tpk0rt/q8Ki3PAgIClJ2drRUrVlThkzjl+PHjkqRmzZpV+LiHh4dWrFhR7r/TtwCYMmWKYmJidP/992v8+PGKjo7W3//+d+fj5/v+zsZut2v58uUaNWqUWrdu7TzeqVMnxcTEVPl1pkyZUqaeSy+9VHa7XQcOHJAkff/99yoqKtK9995b5nn333//eb6DU0pa95f+N1iTSn7XFXUCAAAAABqD+fPnKywsTFdccYWk4jnHTTfdpIULFzpbXF955ZUKDg4u0x3qxIkTWrFihW666SbnsU8++USdOnVSx44dy8zprrzySklyzulKXH755ercuXO5mkrPMU+cOKH09HRdeuml2rRpk/N4SWvss803DMPQZ599ppEjR8owjDJ1xcTEKD09vczrVubbb79VSEiIQkJC1KNHD33yyScaP368swtZidGjR5dZdZyQkKAtW7Zo4sSJCgwMdB7v3r27rrrqKue1g4qsWLFCaWlpGjt2bJm6bTab+vXr5/w8k5OT9dNPP+n2228vM8eTzn8OWdE8t7Kt5qri9Osdl156aZlrLV9//bVcXFzKdGqz2WzVmkcOGTJE0dHRzvvdu3eXn5+f8+fY7XZ99913GjVqVJmOhO3atdPw4cOr9DOOHz9e6bWBEkOHDlVgYKAWLlwowzC0cOFCjR07tsrv41zY7XZ9++23GjVqlKKiopzHIyIidMstt2j16tXOeXSJs83tS65LfPXVVyosLKxWPZMmTXK2j9+5c6eOHj16xvOZgwNA1dBKHQCaiKeeekoffvihXnzxxSrtB10Vp08a/f395eHh4WwrVvp4STBaWvv27cvct1gsateunXOfrr1790rSGdt+paenl5lQtW3btkq1HzhwoFwLLKk44Cx5/FzbP1977bW67777ZLFY5Ovrqy5dujjbfJd2eq0lE6cOHTqUO7djx45avXp1pT9z7969Mgyj3GdawtXVVZIUGxsrSef83u69914tWrRIw4cPV4sWLTR06FCNGTNGw4YNq9LzjUra29tstkr3Fzvd+++/r+joaO3du1dr164tc+HnfN/f2SQnJys3N7fCz7lDhw5nvDBT2un/dkrG8IkTJySdGgunt98PDAw86wWEqipprZaZmVkjr3e6kt91TXwhAQAAAKhv7Ha7Fi5cqCuuuMK5V7Yk9evXTy+//LK+//57DR06VC4uLho9erQWLFig/Px8ubu7a/HixSosLCwTjO/du1e7du2qtB11UlJSmfuVzX2/+uorPffcc9qyZUuZvclL/11+4MABWa3Wcq9x+vwjOTlZaWlpeuedd/TOO+9Uqa6K9OvXT88995wsFou8vLzUqVOnCrcJq84cuVOnTlq+fLmys7MrnG+XXE8o+WLB6UrmQyWBb23MIaszzz0bDw+PcmOjWbNmzjmkVPx5RUREyMfHp8x5FX1+lTl9rnr6z0lKSlJubm65sSKVHz9nUtm1gRKurq668cYbtWDBAl100UU6dOiQbrnlliq//rlITk5WTk5OpePN4XDo0KFD6tKli/P42eb2l19+uUaPHq2ZM2fqlVde0aBBgzRq1Cjdcsstcnd3P2M9zz//vNq0aaP33ntPmzZt0q233qqHH35Yf/7zn/XnP/9ZVmvZNY/MwQGgagjGAaCJiIqK0rhx4/TOO+/o8ccfL/d4ZX84l3zLvSIV7Utc2V7FZ5v0VKRkNfhLL72knj17VnjO6RO+0iGpWVq2bFmlyW9N1upwOGSxWLRs2bIKfwenf07nKjQ0VFu2bNHy5cu1bNkyLVu2THPmzNFtt92mDz74oNLnlexFVnrSfq5WrVrlvMCzbds2DRgw4Lxf81zG//moyX8n56pjx46Sij/DUaNG1fjrl/yuT/+iDAAAANAY/PDDD0pISNDChQu1cOHCco/Pnz9fQ4cOlSTdfPPNmj17tpYtW6ZRo0Zp0aJF6tixo3r06OE83+FwqFu3bvq///u/Cn9eq1atytyvaD75888/65prrtFll12mN998UxEREXJ1ddWcOXO0YMGCar/Hkjn5uHHjKv3Cevfu3c/6OsHBwabMkaXifcbDw8PLPe7iYu5l8erOQSubQ9a0upirBgUFVenawC233KK3335bM2bMUI8ePSrskGC2s31eFotFn376qX755RctWbJEy5cv1+23366XX35Zv/zyyxmv1VitVt1111266667NHHiRHXs2FGbNm3So48+KrvdXu7aHnNwAKgagnEAaEKeeuopzZs3r1y7MunUt1rT0tLKHC/5hnZtKPkGdwnDMLRv3z7nxLqkfZefn1+Nfcu6RGRkpPbs2VPu+O7du52P17WSn7lnz55y32rfs2fPGWuKjo6WYRhq27atLrjggjOeJ0nbt28/42d6pm8Yu7m5aeTIkRo5cqQcDofuvfdezZ49W08//XSl3xBv3bq1PD09y6ykOBcJCQm6//77NXToULm5uemRRx5RTEyM87Op6vs7XVXHf0hIiDw9PcuNXUkVjqdzVfJ+9u3bV2bVxPHjx2vkywWSNHDgQDVr1kwfffSR/vrXv9b4hZaS33VJFwYAAACgMZk/f75CQ0M1a9asco8tXrxYn3/+ud5++215enrqsssuU0REhD7++GMNHDhQP/zwg5588skyz4mOjtbWrVs1ePDgc17x+dlnn8nDw0PLly8vsxp1zpw5Zc6LjIyUw+FQfHx8mW5Y+/btK3NeSEiIfH19Zbfba3xOXhWl58in2717t4KDgytcLS6dmhuGhoaesfaSltnbt28/Yy01vQq3Nq7BREZG6vvvv1dWVlaZwLUm56qhoaHy8PAoN1ak8uOnMh07dtRnn3121vMGDhyo1q1ba9WqVRVex6ppISEh8vLyqnS8Wa3Wcl9Qqar+/furf//+ev7557VgwQLdeuutWrhwYZktCqvyGo8//ri6d++uTz/9tFwwHh8fL6vVesZrQgAAiT3GAaAJiY6O1rhx4zR79mwdO3aszGN+fn4KDg7WTz/9VOb4m2++WWv1/Pe//y3TxvnTTz9VQkKCc1+qPn36KDo6Wv/617+UlZVV7vnJycnn/LOvvvpq/fbbb1q3bp3zWHZ2tt555x21adPGlG8i9+3bV6GhoXr77bfLtLxbtmyZdu3apREjRlT63Ouvv142m00zZ84s901uwzCcrex79+6ttm3b6tVXXy03AS/9vJKLC6efc3pLfKvV6vwiQ+maT+fq6qq+fftqw4YNlZ5TFXfeeaccDof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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()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"\n",
|
|
"1. **Project Volume Evolution**\n",
|
|
"- Growth phase: 2014-2019 (from ~0 to 5000+ projects)\n",
|
|
"- Plateau: 2019-2022 (~4000-5000 projects)\n",
|
|
"- Sharp decline: 2023-2024 (down to ~500 projects)\n",
|
|
"\n",
|
|
"2. **Average Project Size**\n",
|
|
"- Relatively stable 2014-2023 ($0.1-0.3M per project)\n",
|
|
"- Dramatic increase in 2024 (to ~$1.3M per project)\n",
|
|
"- Suggests shift to fewer but larger projects\n",
|
|
"\n",
|
|
"3. **Total GGRF Funding**\n",
|
|
"- Steady increase: 2014-2020 (reaching ~$1.1B)\n",
|
|
"- Recent decline: 2020-2024 (down to ~$0.67B)\n",
|
|
"- More stable pattern than project counts\n",
|
|
"\n",
|
|
"4. **Partnership Trends**\n",
|
|
"- Generally stable at 1.0-1.1 partners until 2020\n",
|
|
"- Spike in 2020 (~1.24 partners)\n",
|
|
"- New peak in 2024 (~1.32 partners)\n",
|
|
"- Suggests increasing regional collaboration\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 13,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Program Scale Distribution:\n",
|
|
"size_category\n",
|
|
"Small 21\n",
|
|
"Large 11\n",
|
|
"Medium 5\n",
|
|
"Mega 1\n",
|
|
"Name: count, dtype: int64\n",
|
|
"\n",
|
|
"Geographic Concentration:\n",
|
|
"Top 5 counties account for 39.3% of funding\n",
|
|
"\n",
|
|
"Program Categories by Total Funding (Billions $):\n",
|
|
"size_category\n",
|
|
"Large 2.19\n",
|
|
"Small 2.00\n",
|
|
"Mega 1.19\n",
|
|
"Medium 0.78\n",
|
|
"Name: total_funding, dtype: float64\n",
|
|
"\n",
|
|
"Largest Programs (by total funding):\n",
|
|
" total_funding \\\n",
|
|
"Program Name \n",
|
|
"Affordable Housing and Sustainable Communities ... 1192203125 \n",
|
|
"Low Carbon Transit Operations Program 775906434 \n",
|
|
"Transit and Intercity Rail Capital Program 771556000 \n",
|
|
"Fire Prevention Program 596274123 \n",
|
|
"Community Air Protection 529523228 \n",
|
|
"\n",
|
|
" project_count \\\n",
|
|
"Program Name \n",
|
|
"Affordable Housing and Sustainable Communities ... 93 \n",
|
|
"Low Carbon Transit Operations Program 766 \n",
|
|
"Transit and Intercity Rail Capital Program 135 \n",
|
|
"Fire Prevention Program 600 \n",
|
|
"Community Air Protection 5187 \n",
|
|
"\n",
|
|
" avg_funding dac_rate \\\n",
|
|
"Program Name \n",
|
|
"Affordable Housing and Sustainable Communities ... 12819388.44 0.16 \n",
|
|
"Low Carbon Transit Operations Program 1012932.68 0.09 \n",
|
|
"Transit and Intercity Rail Capital Program 5715229.63 0.19 \n",
|
|
"Fire Prevention Program 993790.20 0.00 \n",
|
|
"Community Air Protection 102086.61 0.00 \n",
|
|
"\n",
|
|
" ghg_per_dollar \n",
|
|
"Program Name \n",
|
|
"Affordable Housing and Sustainable Communities ... 0.00 \n",
|
|
"Low Carbon Transit Operations Program 0.01 \n",
|
|
"Transit and Intercity Rail Capital Program 0.01 \n",
|
|
"Fire Prevention Program 0.00 \n",
|
|
"Community Air Protection 0.00 \n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# 1. Program Scale Analysis\n",
|
|
"program_scale = data_filtered.groupby('Program Name').agg({\n",
|
|
" 'Total Program GGRFFunding': ['count', 'sum', 'mean'],\n",
|
|
" 'Is Benefit Disadvantaged Communities': 'mean',\n",
|
|
" 'Total Project GHGReductions': 'sum'\n",
|
|
"}).round(2)\n",
|
|
"\n",
|
|
"# Flatten column names\n",
|
|
"program_scale.columns = ['project_count', 'total_funding', 'avg_funding', \n",
|
|
" 'dac_rate', 'total_ghg']\n",
|
|
"\n",
|
|
"# Calculate GHG efficiency\n",
|
|
"program_scale['ghg_per_dollar'] = program_scale['total_ghg'] / program_scale['total_funding']\n",
|
|
"\n",
|
|
"# Categorize programs by size\n",
|
|
"def categorize_program_size(mean_funding):\n",
|
|
" if mean_funding > 10e6: # 10M\n",
|
|
" return 'Mega'\n",
|
|
" elif mean_funding > 1e6: # 1M\n",
|
|
" return 'Large'\n",
|
|
" elif mean_funding > 500e3: # 500K\n",
|
|
" return 'Medium'\n",
|
|
" else:\n",
|
|
" return 'Small'\n",
|
|
"\n",
|
|
"program_scale['size_category'] = program_scale['avg_funding'].apply(categorize_program_size)\n",
|
|
"\n",
|
|
"print(\"Program Scale Distribution:\")\n",
|
|
"print(program_scale['size_category'].value_counts())\n",
|
|
"\n",
|
|
"# 2. Geographic Analysis\n",
|
|
"geographic_dist = data_filtered.groupby('County').agg({\n",
|
|
" 'Total Program GGRFFunding': ['count', 'sum'],\n",
|
|
" 'Is Benefit Disadvantaged Communities': 'mean',\n",
|
|
" 'Total Project GHGReductions': 'sum'\n",
|
|
"})\n",
|
|
"\n",
|
|
"geographic_dist.columns = ['project_count', 'total_funding', 'dac_rate', 'total_ghg']\n",
|
|
"\n",
|
|
"# Calculate concentration metrics\n",
|
|
"total_funding = geographic_dist['total_funding'].sum()\n",
|
|
"top_5_counties = geographic_dist['total_funding'].nlargest(5)\n",
|
|
"concentration = (top_5_counties.sum() / total_funding) * 100\n",
|
|
"\n",
|
|
"print(\"\\nGeographic Concentration:\")\n",
|
|
"print(f\"Top 5 counties account for {concentration:.1f}% of funding\")\n",
|
|
"\n",
|
|
"# 3. Print key findings\n",
|
|
"print(\"\\nProgram Categories by Total Funding (Billions $):\")\n",
|
|
"size_summary = program_scale.groupby('size_category')['total_funding'].sum().sort_values(ascending=False)/1e9\n",
|
|
"print(size_summary.round(2))\n",
|
|
"\n",
|
|
"# Show largest programs\n",
|
|
"print(\"\\nLargest Programs (by total funding):\")\n",
|
|
"print(program_scale.nlargest(5, 'total_funding')[\n",
|
|
" ['total_funding', 'project_count', 'avg_funding', 'dac_rate', 'ghg_per_dollar']\n",
|
|
"].round(2))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"\n",
|
|
"1. **Program Scale Distribution**\n",
|
|
"- Most programs (21) are \"Small\" scale\n",
|
|
"- 11 \"Large\" programs\n",
|
|
"- Only 1 \"Mega\" program (Affordable Housing at $1.19B)\n",
|
|
"- More balanced distribution than when including transportation subsidies\n",
|
|
"\n",
|
|
"1. **Funding Allocation**\n",
|
|
"- Large programs: $2.19B total\n",
|
|
"- Small programs: $2.00B total\n",
|
|
"- Mega programs: $1.19B total\n",
|
|
"- Medium programs: $0.78B total\n",
|
|
"- Total GGRF funding: ~$6.16B\n",
|
|
"\n",
|
|
"1. **Top Programs by Funding**\n",
|
|
"- Affordable Housing: $1.19B (93 projects)\n",
|
|
"- Low Carbon Transit: $776M (766 projects)\n",
|
|
"- Transit/Rail Capital: $772M (135 projects)\n",
|
|
"- Fire Prevention: $596M (600 projects)\n",
|
|
"- Community Air Protection: $530M (5,187 projects)\n",
|
|
"\n",
|
|
"1. **Program Characteristics**\n",
|
|
"- Wide range in project counts (93 to 5,187)\n",
|
|
"- Average project sizes vary significantly:\n",
|
|
" * Affordable Housing: $12.8M/project\n",
|
|
" * Transit/Rail: $5.7M/project\n",
|
|
" * Community Air Protection: $102K/project\n",
|
|
"\n",
|
|
"1. **Geographic Distribution**\n",
|
|
"- Less concentrated than before\n",
|
|
"- Top 5 counties: 39.3% of funding (vs. previous 75.6%)\n",
|
|
"- Suggests more equitable geographic distribution\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 14,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"1. DAC Benefits by Program Size:\n",
|
|
" dac_rate total_funding project_count\n",
|
|
" mean min max sum sum\n",
|
|
"size_category \n",
|
|
"Large 0.087 0.00 0.67 2185763970 1314\n",
|
|
"Medium 0.036 0.00 0.18 779274523 831\n",
|
|
"Mega 0.160 0.16 0.16 1192203125 93\n",
|
|
"Small 0.084 0.00 0.92 2003043460 28913\n",
|
|
"\n",
|
|
"2. Regional Distribution:\n",
|
|
" total_funding project_count dac_rate total_ghg\n",
|
|
"region \n",
|
|
"Central Valley 1387932197 14496 0.104 25320641\n",
|
|
"Other 2289435192 9195 0.101 24839824\n",
|
|
"Urban 2482917689 7460 0.161 15727243\n",
|
|
"\n",
|
|
"4. Multi-County vs Single-County Projects:\n",
|
|
" Multi-County Single-County\n",
|
|
"project_count 7.520000e+02 3.039900e+04\n",
|
|
"total_funding 5.210746e+08 5.639210e+09\n",
|
|
"avg_funding 6.929184e+05 1.855064e+05\n",
|
|
"dac_rate 1.090000e-01 2.730000e-01\n",
|
|
"ghg_per_dollar 1.200000e-02 1.100000e-02\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
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",
|
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"text/plain": [
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"<Figure size 1200x800 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"# 1. DAC Benefits by Program Size\n",
|
|
"dac_by_size = program_scale.groupby('size_category').agg({\n",
|
|
" 'dac_rate': ['mean', 'min', 'max'],\n",
|
|
" 'total_funding': 'sum',\n",
|
|
" 'project_count': 'sum'\n",
|
|
"}).round(3)\n",
|
|
"\n",
|
|
"# 2. Geographic Analysis\n",
|
|
"# Add region classification\n",
|
|
"def classify_region(county):\n",
|
|
" if isinstance(county, str): # Handle multi-county cases\n",
|
|
" counties = county.split(',')\n",
|
|
" county = counties[0].strip()\n",
|
|
" \n",
|
|
" urban_counties = ['Los Angeles', 'San Francisco', 'Alameda', 'San Diego', 'Orange']\n",
|
|
" central_valley = ['Fresno', 'Kern', 'Kings', 'Madera', 'Merced', 'San Joaquin', 'Stanislaus', 'Tulare']\n",
|
|
" \n",
|
|
" if county in urban_counties:\n",
|
|
" return 'Urban'\n",
|
|
" elif county in central_valley:\n",
|
|
" return 'Central Valley'\n",
|
|
" else:\n",
|
|
" return 'Other'\n",
|
|
"\n",
|
|
"geographic_dist['region'] = geographic_dist.index.map(classify_region)\n",
|
|
"regional_metrics = geographic_dist.groupby('region').agg({\n",
|
|
" 'total_funding': 'sum',\n",
|
|
" 'project_count': 'sum',\n",
|
|
" 'dac_rate': 'mean',\n",
|
|
" 'total_ghg': 'sum'\n",
|
|
"}).round(3)\n",
|
|
"\n",
|
|
"# 3. Project Size vs GHG Efficiency\n",
|
|
"# Create scatter plot\n",
|
|
"plt.figure(figsize=(12, 8))\n",
|
|
"plt.scatter(program_scale['avg_funding']/1e6, \n",
|
|
" program_scale['ghg_per_dollar'],\n",
|
|
" alpha=0.6)\n",
|
|
"plt.xlabel('Average Project Size (Millions $)')\n",
|
|
"plt.ylabel('GHG Reduction per Dollar')\n",
|
|
"plt.title('Project Size vs. GHG Efficiency')\n",
|
|
"\n",
|
|
"# 4. Multi-county Analysis\n",
|
|
"multi_county_data = data_filtered[data_filtered['County'].str.contains(',', na=False)]\n",
|
|
"single_county_data = data_filtered[~data_filtered['County'].str.contains(',', na=False)]\n",
|
|
"\n",
|
|
"multi_vs_single = pd.DataFrame({\n",
|
|
" 'Multi-County': {\n",
|
|
" 'project_count': len(multi_county_data),\n",
|
|
" 'total_funding': multi_county_data['Total Program GGRFFunding'].sum(),\n",
|
|
" 'avg_funding': multi_county_data['Total Program GGRFFunding'].mean(),\n",
|
|
" 'dac_rate': multi_county_data['Is Benefit Disadvantaged Communities'].mean(),\n",
|
|
" 'ghg_per_dollar': (multi_county_data['Total Project GHGReductions'].sum() / \n",
|
|
" multi_county_data['Total Program GGRFFunding'].sum())\n",
|
|
" },\n",
|
|
" 'Single-County': {\n",
|
|
" 'project_count': len(single_county_data),\n",
|
|
" 'total_funding': single_county_data['Total Program GGRFFunding'].sum(),\n",
|
|
" 'avg_funding': single_county_data['Total Program GGRFFunding'].mean(),\n",
|
|
" 'dac_rate': single_county_data['Is Benefit Disadvantaged Communities'].mean(),\n",
|
|
" 'ghg_per_dollar': (single_county_data['Total Project GHGReductions'].sum() / \n",
|
|
" single_county_data['Total Program GGRFFunding'].sum())\n",
|
|
" }\n",
|
|
"})\n",
|
|
"\n",
|
|
"print(\"1. DAC Benefits by Program Size:\")\n",
|
|
"print(dac_by_size)\n",
|
|
"\n",
|
|
"print(\"\\n2. Regional Distribution:\")\n",
|
|
"print(regional_metrics)\n",
|
|
"\n",
|
|
"print(\"\\n4. Multi-County vs Single-County Projects:\")\n",
|
|
"print(multi_vs_single.round(3))\n",
|
|
"\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"\n",
|
|
"1. **Efficiency Sweet Spot**\n",
|
|
"- Highest GHG efficiency (0.12-0.13 reduction per dollar) occurs in projects around $2M\n",
|
|
"- Secondary peak (0.06) in smaller projects under $1M\n",
|
|
"- Suggests optimal scale for GHG reduction isn't necessarily larger projects\n",
|
|
"\n",
|
|
"1. **Size-Efficiency Relationship**\n",
|
|
"- No clear linear relationship\n",
|
|
"- Most projects cluster in lower ranges (both size and efficiency)\n",
|
|
"- Largest projects ($12M+) show relatively low GHG efficiency\n",
|
|
"- Suggests diminishing returns as projects scale up\n",
|
|
"\n",
|
|
"1. **Distribution Pattern**\n",
|
|
"- Dense cluster of projects under $2M with varying efficiency\n",
|
|
"- Sparse distribution in higher project sizes\n",
|
|
"- Few projects achieve both large scale and high efficiency\n",
|
|
"\n",
|
|
"Let's identify:\n",
|
|
"1. What programs occupy that sweet spot around $2M with high efficiency?\n",
|
|
"2. What characteristics do those efficient projects share?\n",
|
|
"3. Are there geographic patterns in the more efficient projects?\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 15,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"1. Most GHG-Efficient Programs:\n",
|
|
" total_funding \\\n",
|
|
"Program Name \n",
|
|
"Sustainable Agricultural Lands Conservation Pro... 122424176 \n",
|
|
"Climate Smart Agriculture 338161549 \n",
|
|
"Fluorinated Gases Emission Reduction Incentives 1000001 \n",
|
|
"Low-Carbon Fuels Production Program 12500000 \n",
|
|
"Food Production Investment Program 117791478 \n",
|
|
"Wetlands and Watershed Restoration 16171301 \n",
|
|
"Forest Health Program 207621340 \n",
|
|
"Waste Diversion 118571417 \n",
|
|
"Renewable Energy for Agriculture Program 9500000 \n",
|
|
"Woodsmoke Reduction Program 7895909 \n",
|
|
"\n",
|
|
" avg_funding \\\n",
|
|
"Program Name \n",
|
|
"Sustainable Agricultural Lands Conservation Pro... 1275251.83 \n",
|
|
"Climate Smart Agriculture 257941.68 \n",
|
|
"Fluorinated Gases Emission Reduction Incentives 66666.73 \n",
|
|
"Low-Carbon Fuels Production Program 3125000.00 \n",
|
|
"Food Production Investment Program 2103419.25 \n",
|
|
"Wetlands and Watershed Restoration 2021412.62 \n",
|
|
"Forest Health Program 1701814.26 \n",
|
|
"Waste Diversion 463169.60 \n",
|
|
"Renewable Energy for Agriculture Program 211111.11 \n",
|
|
"Woodsmoke Reduction Program 8233.48 \n",
|
|
"\n",
|
|
" ghg_per_dollar dac_rate \n",
|
|
"Program Name \n",
|
|
"Sustainable Agricultural Lands Conservation Pro... 0.123 0.01 \n",
|
|
"Climate Smart Agriculture 0.062 0.05 \n",
|
|
"Fluorinated Gases Emission Reduction Incentives 0.037 0.00 \n",
|
|
"Low-Carbon Fuels Production Program 0.036 0.00 \n",
|
|
"Food Production Investment Program 0.025 0.00 \n",
|
|
"Wetlands and Watershed Restoration 0.025 0.00 \n",
|
|
"Forest Health Program 0.023 0.00 \n",
|
|
"Waste Diversion 0.016 0.09 \n",
|
|
"Renewable Energy for Agriculture Program 0.013 0.00 \n",
|
|
"Woodsmoke Reduction Program 0.013 0.00 \n",
|
|
"\n",
|
|
"2. Characteristics of High-Efficiency Programs:\n",
|
|
"\n",
|
|
"Size Distribution:\n",
|
|
"size_category\n",
|
|
"Large 5\n",
|
|
"Small 5\n",
|
|
"Name: count, dtype: int64\n",
|
|
"\n",
|
|
"3. Geographic Distribution of High-Efficiency Projects:\n",
|
|
" Total Program GGRFFunding \\\n",
|
|
" count sum \n",
|
|
"County \n",
|
|
"Sierra 5 485667 \n",
|
|
"Mono 10 2946879 \n",
|
|
"Lassen 28 5510913 \n",
|
|
"Calaveras 32 9678108 \n",
|
|
"Los Angeles, Solano 1 212629 \n",
|
|
"\n",
|
|
" Total Project GHGReductions ghg_per_dollar \n",
|
|
" sum \n",
|
|
"County \n",
|
|
"Sierra 730033 1.503155 \n",
|
|
"Mono 1570341 0.532883 \n",
|
|
"Lassen 2089977 0.379243 \n",
|
|
"Calaveras 1857223 0.191899 \n",
|
|
"Los Angeles, Solano 23680 0.111368 \n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
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",
|
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"text/plain": [
|
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"<Figure size 1500x800 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Let's identify the most GHG-efficient projects and analyze their characteristics\n",
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|
"\n",
|
|
"# Add efficiency metric to original program data\n",
|
|
"program_scale['efficiency_tier'] = pd.qcut(program_scale['ghg_per_dollar'], \n",
|
|
" q=4, \n",
|
|
" labels=['Low', 'Medium-Low', 'Medium-High', 'High'])\n",
|
|
"\n",
|
|
"print(\"1. Most GHG-Efficient Programs:\")\n",
|
|
"high_efficiency = program_scale[program_scale['efficiency_tier'] == 'High'].sort_values('ghg_per_dollar', ascending=False)\n",
|
|
"print(high_efficiency[['total_funding', 'avg_funding', 'ghg_per_dollar', 'dac_rate']].round(3))\n",
|
|
"\n",
|
|
"# Analyze characteristics of high-efficiency programs\n",
|
|
"print(\"\\n2. Characteristics of High-Efficiency Programs:\")\n",
|
|
"print(\"\\nSize Distribution:\")\n",
|
|
"print(high_efficiency['size_category'].value_counts())\n",
|
|
"\n",
|
|
"# Geographic analysis of high-efficiency programs\n",
|
|
"print(\"\\n3. Geographic Distribution of High-Efficiency Projects:\")\n",
|
|
"# Filter original data for these programs\n",
|
|
"high_eff_projects = data_filtered[\n",
|
|
" data_filtered['Program Name'].isin(high_efficiency.index)\n",
|
|
"]\n",
|
|
"geographic_dist = high_eff_projects.groupby('County').agg({\n",
|
|
" 'Total Program GGRFFunding': ['count', 'sum'],\n",
|
|
" 'Total Project GHGReductions': 'sum'\n",
|
|
"}).round(2)\n",
|
|
"\n",
|
|
"# Calculate efficiency by region\n",
|
|
"geographic_dist['ghg_per_dollar'] = (\n",
|
|
" geographic_dist[('Total Project GHGReductions', 'sum')] / \n",
|
|
" geographic_dist[('Total Program GGRFFunding', 'sum')]\n",
|
|
")\n",
|
|
"\n",
|
|
"print(geographic_dist.nlargest(5, 'ghg_per_dollar'))\n",
|
|
"\n",
|
|
"# Create visualization of efficiency patterns\n",
|
|
"plt.figure(figsize=(15, 8))\n",
|
|
"\n",
|
|
"plt.subplot(1, 2, 1)\n",
|
|
"# Size vs Efficiency for high performers\n",
|
|
"plt.scatter(high_efficiency['avg_funding']/1e6, \n",
|
|
" high_efficiency['ghg_per_dollar'],\n",
|
|
" alpha=0.6,\n",
|
|
" s=100)\n",
|
|
"plt.xlabel('Average Project Size (Millions $)')\n",
|
|
"plt.ylabel('GHG Reduction per Dollar')\n",
|
|
"plt.title('High-Efficiency Programs: Size vs Performance')\n",
|
|
"\n",
|
|
"# Add program labels\n",
|
|
"for idx, row in high_efficiency.iterrows():\n",
|
|
" plt.annotate(idx[:20] + '...' if len(idx) > 20 else idx,\n",
|
|
" (row['avg_funding']/1e6, row['ghg_per_dollar']),\n",
|
|
" xytext=(5, 5), textcoords='offset points')\n",
|
|
"\n",
|
|
"plt.subplot(1, 2, 2)\n",
|
|
"# DAC Rate vs Efficiency\n",
|
|
"plt.scatter(high_efficiency['dac_rate'], \n",
|
|
" high_efficiency['ghg_per_dollar'],\n",
|
|
" alpha=0.6,\n",
|
|
" s=100)\n",
|
|
"plt.xlabel('DAC Benefit Rate')\n",
|
|
"plt.ylabel('GHG Reduction per Dollar')\n",
|
|
"plt.title('High-Efficiency Programs: Equity vs Performance')\n",
|
|
"\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 16,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Urban/Rural Analysis Summary:\n",
|
|
" Project Count Total Funding (B) Avg Project Size (M) \\\n",
|
|
"region_type \n",
|
|
"Central Valley 14496 1.388 0.096 \n",
|
|
"Rural 8474 2.183 0.258 \n",
|
|
"Urban 8181 2.589 0.316 \n",
|
|
"\n",
|
|
" GHG Efficiency DAC Rate \n",
|
|
"region_type \n",
|
|
"Central Valley 0.018 0.181 \n",
|
|
"Rural 0.011 0.233 \n",
|
|
"Urban 0.007 0.462 \n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1500x1200 with 4 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
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"text": [
|
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"\n",
|
|
"Top Programs by Region (Funding in Millions $):\n",
|
|
"region_type Central Valley Rural \\\n",
|
|
"Program Name \n",
|
|
"Transit and Intercity Rail Capital Program 18.28 86.89 \n",
|
|
"Affordable Housing and Sustainable Communities ... 205.61 321.80 \n",
|
|
"Low Carbon Transit Operations Program 52.88 178.45 \n",
|
|
"Community Air Protection 144.75 145.80 \n",
|
|
"Transformative Climate Communities 69.17 62.67 \n",
|
|
"Urban Greening Program 18.91 58.50 \n",
|
|
"Fire Prevention Program 51.09 493.55 \n",
|
|
"Waste Diversion 22.71 50.54 \n",
|
|
"Low-Income Weatherization Program 62.87 57.02 \n",
|
|
"Urban and Community Forestry Program 7.55 13.80 \n",
|
|
"\n",
|
|
"region_type Urban \n",
|
|
"Program Name \n",
|
|
"Transit and Intercity Rail Capital Program 666.38 \n",
|
|
"Affordable Housing and Sustainable Communities ... 664.79 \n",
|
|
"Low Carbon Transit Operations Program 544.58 \n",
|
|
"Community Air Protection 238.97 \n",
|
|
"Transformative Climate Communities 70.89 \n",
|
|
"Urban Greening Program 61.36 \n",
|
|
"Fire Prevention Program 51.63 \n",
|
|
"Waste Diversion 45.32 \n",
|
|
"Low-Income Weatherization Program 39.08 \n",
|
|
"Urban and Community Forestry Program 37.84 \n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# Define urban/rural classification\n",
|
|
"def classify_urban_rural(county):\n",
|
|
" if isinstance(county, str): # Handle multi-county cases\n",
|
|
" counties = county.split(',')\n",
|
|
" county = counties[0].strip()\n",
|
|
" \n",
|
|
" urban_counties = ['Los Angeles', 'San Francisco', 'Alameda', 'San Diego', 'Orange', 'Santa Clara']\n",
|
|
" central_valley = ['Fresno', 'Kern', 'Kings', 'Madera', 'Merced', 'San Joaquin', 'Stanislaus', 'Tulare']\n",
|
|
" \n",
|
|
" if county in urban_counties:\n",
|
|
" return 'Urban'\n",
|
|
" elif county in central_valley:\n",
|
|
" return 'Central Valley'\n",
|
|
" else:\n",
|
|
" return 'Rural'\n",
|
|
"\n",
|
|
"# Add classification to data\n",
|
|
"data_filtered['region_type'] = data_filtered['County'].map(classify_urban_rural)\n",
|
|
"\n",
|
|
"# Analyze by region type\n",
|
|
"region_analysis = data_filtered.groupby('region_type').agg({\n",
|
|
" 'Total Program GGRFFunding': ['count', 'sum', 'mean'],\n",
|
|
" 'Total Project GHGReductions': ['sum', 'mean'],\n",
|
|
" 'Is Benefit Disadvantaged Communities': 'mean'\n",
|
|
"}).round(3)\n",
|
|
"\n",
|
|
"# Calculate GHG efficiency by region\n",
|
|
"ghg_efficiency = (region_analysis[('Total Project GHGReductions', 'sum')] / \n",
|
|
" region_analysis[('Total Program GGRFFunding', 'sum')])\n",
|
|
"\n",
|
|
"print(\"Urban/Rural Analysis Summary:\")\n",
|
|
"summary_df = pd.DataFrame({\n",
|
|
" 'Project Count': region_analysis[('Total Program GGRFFunding', 'count')],\n",
|
|
" 'Total Funding (B)': region_analysis[('Total Program GGRFFunding', 'sum')]/1e9,\n",
|
|
" 'Avg Project Size (M)': region_analysis[('Total Program GGRFFunding', 'mean')]/1e6,\n",
|
|
" 'GHG Efficiency': ghg_efficiency,\n",
|
|
" 'DAC Rate': region_analysis[('Is Benefit Disadvantaged Communities', 'mean')]\n",
|
|
"})\n",
|
|
"print(summary_df.round(3))\n",
|
|
"\n",
|
|
"# Visualize key metrics\n",
|
|
"fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(15, 12))\n",
|
|
"\n",
|
|
"# 1. Total Funding by Region\n",
|
|
"ax1.bar(summary_df.index, summary_df['Total Funding (B)'], color='skyblue')\n",
|
|
"ax1.set_title('Total Funding by Region (Billions $)')\n",
|
|
"ax1.set_ylabel('Funding (Billions $)')\n",
|
|
"\n",
|
|
"# 2. Average Project Size\n",
|
|
"ax2.bar(summary_df.index, summary_df['Avg Project Size (M)'], color='skyblue')\n",
|
|
"ax2.set_title('Average Project Size by Region (Millions $)')\n",
|
|
"ax2.set_ylabel('Average Size (Millions $)')\n",
|
|
"\n",
|
|
"# 3. GHG Efficiency\n",
|
|
"ax3.bar(summary_df.index, summary_df['GHG Efficiency'], color='skyblue')\n",
|
|
"ax3.set_title('GHG Reduction Efficiency by Region')\n",
|
|
"ax3.set_ylabel('GHG Reduction per Dollar')\n",
|
|
"\n",
|
|
"# 4. DAC Benefit Rate\n",
|
|
"ax4.bar(summary_df.index, summary_df['DAC Rate'], color='skyblue')\n",
|
|
"ax4.set_title('DAC Benefit Rate by Region')\n",
|
|
"ax4.set_ylabel('Proportion Benefiting DACs')\n",
|
|
"\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.show()\n",
|
|
"\n",
|
|
"# Look at program distribution by region\n",
|
|
"print(\"\\nTop Programs by Region (Funding in Millions $):\")\n",
|
|
"program_by_region = pd.crosstab(\n",
|
|
" data_filtered['Program Name'], \n",
|
|
" data_filtered['region_type'], \n",
|
|
" values=data_filtered['Total Program GGRFFunding'],\n",
|
|
" aggfunc='sum'\n",
|
|
")/1e6\n",
|
|
"\n",
|
|
"print(program_by_region.sort_values('Urban', ascending=False).head(10).round(2))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"\n",
|
|
"1. **GHG Efficiency Gap**\n",
|
|
"- Central Valley is ~3x more efficient than Urban areas (0.0175 vs 0.0065 GHG reduction per dollar)\n",
|
|
"- Rural areas also outperform Urban (0.010 vs 0.0065)\n",
|
|
"- Suggests climate dollars go further in non-urban areas\n",
|
|
"\n",
|
|
"1. **Inverse DAC Pattern**\n",
|
|
"- Urban areas have highest DAC benefit rate (~0.45)\n",
|
|
"- Rural areas at ~0.23 DAC rate\n",
|
|
"- Central Valley lowest at ~0.18\n",
|
|
"\n",
|
|
"1. **Investment Distribution**\n",
|
|
"- Urban areas get most funding ($2.5B)\n",
|
|
"- Rural second ($2.2B)\n",
|
|
"- Central Valley least ($1.4B)\n",
|
|
"- Average project sizes follow same pattern\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 17,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Program Types and Efficiency by Region:\n",
|
|
"\n",
|
|
"Urban Most Efficient Programs:\n",
|
|
" Program Name \\\n",
|
|
"100 Woodsmoke Reduction Program \n",
|
|
"29 Fluorinated Gases Emission Reduction Incentives \n",
|
|
"61 Renewable Energy for Agriculture Program \n",
|
|
"89 Waste Diversion \n",
|
|
"32 Food Production Investment Program \n",
|
|
"\n",
|
|
" Total Program GGRFFunding efficiency \n",
|
|
"100 808 0.1027 \n",
|
|
"29 530239 0.0380 \n",
|
|
"61 42551 0.0290 \n",
|
|
"89 45316021 0.0203 \n",
|
|
"32 13221462 0.0129 \n",
|
|
"\n",
|
|
"Rural Most Efficient Programs:\n",
|
|
" Program Name \\\n",
|
|
"69 Sustainable Agricultural Lands Conservation Pr... \n",
|
|
"49 Low-Carbon Fuels Production Program \n",
|
|
"28 Fluorinated Gases Emission Reduction Incentives \n",
|
|
"31 Food Production Investment Program \n",
|
|
"37 Forest Health Program \n",
|
|
"\n",
|
|
" Total Program GGRFFunding efficiency \n",
|
|
"69 108577417 0.1273 \n",
|
|
"49 5000000 0.0905 \n",
|
|
"28 469762 0.0352 \n",
|
|
"31 32710900 0.0298 \n",
|
|
"37 163034942 0.0285 \n",
|
|
"\n",
|
|
"Central Valley Most Efficient Programs:\n",
|
|
" Program Name \\\n",
|
|
"68 Sustainable Agricultural Lands Conservation Pr... \n",
|
|
"14 Climate Smart Agriculture \n",
|
|
"30 Food Production Investment Program \n",
|
|
"87 Waste Diversion \n",
|
|
"59 Renewable Energy for Agriculture Program \n",
|
|
"\n",
|
|
" Total Program GGRFFunding efficiency \n",
|
|
"68 9744397 0.1253 \n",
|
|
"14 274120208 0.0751 \n",
|
|
"30 71859116 0.0255 \n",
|
|
"87 22712521 0.0252 \n",
|
|
"59 3761222 0.0180 \n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# Calculate efficiency ratios and examine program types\n",
|
|
"print(\"Program Types and Efficiency by Region:\")\n",
|
|
"program_efficiency = data_filtered.groupby(['Program Name', 'region_type']).agg({\n",
|
|
" 'Total Program GGRFFunding': 'sum',\n",
|
|
" 'Total Project GHGReductions': 'sum'\n",
|
|
"}).reset_index()\n",
|
|
"\n",
|
|
"program_efficiency['efficiency'] = (program_efficiency['Total Project GHGReductions'] / \n",
|
|
" program_efficiency['Total Program GGRFFunding'])\n",
|
|
"\n",
|
|
"# Show top efficient programs by region\n",
|
|
"for region in ['Urban', 'Rural', 'Central Valley']:\n",
|
|
" print(f\"\\n{region} Most Efficient Programs:\")\n",
|
|
" region_data = program_efficiency[program_efficiency['region_type'] == region]\n",
|
|
" print(region_data.nlargest(5, 'efficiency')[\n",
|
|
" ['Program Name', 'Total Program GGRFFunding', 'efficiency']\n",
|
|
" ].round(4))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"This breakdown is really revealing about what works where:\n",
|
|
"\n",
|
|
"1. **Urban Efficiency Leaders**\n",
|
|
"- Woodsmoke Reduction (0.1027)\n",
|
|
"- Fluorinated Gases (0.0380)\n",
|
|
"- Renewable Energy for Agriculture (0.0290)\n",
|
|
"- But notice: Top performers have relatively small funding amounts (except Waste Diversion at $45M)\n",
|
|
"\n",
|
|
"2. **Rural Efficiency Champions**\n",
|
|
"- Sustainable Agricultural Lands (0.1273, $108M)\n",
|
|
"- Low-Carbon Fuels (0.0905)\n",
|
|
"- Larger programs achieving high efficiency\n",
|
|
"- Strong agriculture and land-use focus\n",
|
|
"\n",
|
|
"3. **Central Valley Success Stories**\n",
|
|
"- Sustainable Agricultural Lands (0.1253)\n",
|
|
"- Climate Smart Agriculture (0.0751, $274M)\n",
|
|
"- High efficiency with substantial funding amounts\n",
|
|
"\n",
|
|
"**Key Patterns:**\n",
|
|
"1. Agricultural and land-use programs dominate efficiency in rural/CV\n",
|
|
"2. Urban areas achieve efficiency through smaller, targeted programs\n",
|
|
"3. Central Valley shows ability to maintain efficiency at scale\n",
|
|
"4. Similar program types (e.g., Food Production) perform differently by region\n",
|
|
"\n",
|
|
"Would you like to:\n",
|
|
"1. Analyze the characteristics of the most efficient programs in each region?\n",
|
|
"2. Look at how program size relates to efficiency within each region?\n",
|
|
"3. Examine whether these patterns change over time?\n",
|
|
"4. Investigate if multi-county collaborations affect these regional differences?"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 18,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Multi-County vs Single-County by Region:\n",
|
|
" Total Program GGRFFunding \\\n",
|
|
" count sum \n",
|
|
"region_type is_multi_county \n",
|
|
"Central Valley False 14312 1314145988 \n",
|
|
" True 184 73786209 \n",
|
|
"Rural False 8194 2060718991 \n",
|
|
" True 280 122681272 \n",
|
|
"Urban False 7893 2264345480 \n",
|
|
" True 288 324607138 \n",
|
|
"\n",
|
|
" Total Project GHGReductions \\\n",
|
|
" mean sum \n",
|
|
"region_type is_multi_county \n",
|
|
"Central Valley False 91821.268 24949448 \n",
|
|
" True 401012.005 371193 \n",
|
|
"Rural False 251491.212 22645122 \n",
|
|
" True 438147.400 906509 \n",
|
|
"Urban False 286880.208 12069861 \n",
|
|
" True 1127108.118 4945575 \n",
|
|
"\n",
|
|
" Is Benefit Disadvantaged Communities \\\n",
|
|
" mean \n",
|
|
"region_type is_multi_county \n",
|
|
"Central Valley False 0.182 \n",
|
|
" True 0.103 \n",
|
|
"Rural False 0.238 \n",
|
|
" True 0.086 \n",
|
|
"Urban False 0.474 \n",
|
|
" True 0.135 \n",
|
|
"\n",
|
|
" ghg_per_dollar \n",
|
|
" \n",
|
|
"region_type is_multi_county \n",
|
|
"Central Valley False 0.018985 \n",
|
|
" True 0.005031 \n",
|
|
"Rural False 0.010989 \n",
|
|
" True 0.007389 \n",
|
|
"Urban False 0.005330 \n",
|
|
" True 0.015236 \n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# Analyze multi-county projects by region type\n",
|
|
"data_filtered['is_multi_county'] = data_filtered['County'].str.contains(',', na=False)\n",
|
|
"\n",
|
|
"regional_collab = data_filtered.groupby(['region_type', 'is_multi_county']).agg({\n",
|
|
" 'Total Program GGRFFunding': ['count', 'sum', 'mean'],\n",
|
|
" 'Total Project GHGReductions': 'sum',\n",
|
|
" 'Is Benefit Disadvantaged Communities': 'mean'\n",
|
|
"}).round(3)\n",
|
|
"\n",
|
|
"# Calculate efficiency\n",
|
|
"regional_collab['ghg_per_dollar'] = (\n",
|
|
" regional_collab[('Total Project GHGReductions', 'sum')] / \n",
|
|
" regional_collab[('Total Program GGRFFunding', 'sum')]\n",
|
|
")\n",
|
|
"\n",
|
|
"print(\"Multi-County vs Single-County by Region:\")\n",
|
|
"print(regional_collab)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"This intersection of multi-county and regional patterns reveals:\n",
|
|
"\n",
|
|
"1. **Project Size Patterns**\n",
|
|
"- Average project size is consistently larger in multi-county projects across all regions:\n",
|
|
" * Urban: $1.13M vs $287K\n",
|
|
" * Rural: $438K vs $251K\n",
|
|
" * Central Valley: $401K vs $92K\n",
|
|
"\n",
|
|
"1. **GHG Efficiency Varies By Region**\n",
|
|
"- Single-county efficiency:\n",
|
|
" * Central Valley leads (0.019)\n",
|
|
" * Rural second (0.011)\n",
|
|
" * Urban lowest (0.005)\n",
|
|
"- Multi-county efficiency shows different pattern:\n",
|
|
" * Urban leads (0.015)\n",
|
|
" * Rural and Central Valley lower (0.007 and 0.005)\n",
|
|
"\n",
|
|
"1. **DAC Benefits Trade-off**\n",
|
|
"- Single-county DAC rates:\n",
|
|
" * Urban highest (47.4%)\n",
|
|
" * Rural (23.8%)\n",
|
|
" * Central Valley (18.2%)\n",
|
|
"- Multi-county shows lower DAC rates across all regions:\n",
|
|
" * Urban (13.5%)\n",
|
|
" * Central Valley (10.3%)\n",
|
|
" * Rural lowest (8.6%)\n",
|
|
"\n",
|
|
"Key Findings:\n",
|
|
"1. Multi-county collaborations most successful in urban areas for GHG efficiency\n",
|
|
"2. Single-county projects better at reaching DACs across all regions\n",
|
|
"3. Central Valley efficiency advantage disappears in multi-county projects\n",
|
|
"4. Urban areas seem to benefit most from regional coordination\n",
|
|
"\n",
|
|
"This suggests different collaboration strategies might be needed for different regions."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 19,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Index(['Tract', 'ZIP', 'County', 'ApproxLoc', 'TotPop19', 'CIscore',\n",
|
|
" 'CIscoreP', 'Ozone', 'OzoneP', 'PM2_5', 'PM2_5_P', 'DieselPM',\n",
|
|
" 'DieselPM_P', 'Pesticide', 'PesticideP', 'Tox_Rel', 'Tox_Rel_P',\n",
|
|
" 'Traffic', 'TrafficP', 'DrinkWat', 'DrinkWatP', 'Lead', 'Lead_P',\n",
|
|
" 'Cleanup', 'CleanupP', 'GWThreat', 'GWThreatP', 'HazWaste', 'HazWasteP',\n",
|
|
" 'ImpWatBod', 'ImpWatBodP', 'SolWaste', 'SolWasteP', 'PollBurd',\n",
|
|
" 'PolBurdSc', 'PolBurdP', 'Asthma', 'AsthmaP', 'LowBirtWt', 'LowBirWP',\n",
|
|
" 'Cardiovas', 'CardiovasP', 'Educatn', 'EducatP', 'Ling_Isol',\n",
|
|
" 'Ling_IsolP', 'Poverty', 'PovertyP', 'Unempl', 'UnemplP', 'HousBurd',\n",
|
|
" 'HousBurdP', 'PopChar', 'PopCharSc', 'PopCharP', 'Child_10',\n",
|
|
" 'Pop_10_64', 'Elderly65', 'Hispanic', 'White', 'AfricanAm', 'NativeAm',\n",
|
|
" 'OtherMult', 'Shape_Leng', 'Shape_Area', 'AAPI', 'geometry'],\n",
|
|
" dtype='object')"
|
|
]
|
|
},
|
|
"execution_count": 19,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"gdf.columns"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 22,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"\n",
|
|
"CES Tract Examples:\n",
|
|
"0 6083002103\n",
|
|
"1 6083002402\n",
|
|
"2 6083002102\n",
|
|
"3 6083002010\n",
|
|
"4 6083002009\n",
|
|
"Name: Tract, dtype: object\n",
|
|
"\n",
|
|
"CCI Tract Examples:\n",
|
|
"16067 NaN\n",
|
|
"25098 6.001402e+09\n",
|
|
"25099 6.001402e+09\n",
|
|
"25100 6.001406e+09\n",
|
|
"25101 6.001406e+09\n",
|
|
"Name: Census Tract, dtype: float64\n",
|
|
"\n",
|
|
"Missing Tract Counts:\n",
|
|
"CES missing tracts: 0\n",
|
|
"CCI missing tracts: 17967\n",
|
|
"\n",
|
|
"Merged Data Summary:\n",
|
|
"Total rows: 13184\n",
|
|
"Unique tracts: 3665\n",
|
|
"\n",
|
|
"Funding Distribution by CalEnviroScreen Score Quintiles:\n",
|
|
" Total Program GGRFFunding \\\n",
|
|
" count sum mean \n",
|
|
"CES_quintile \n",
|
|
"Lowest Burden 2638 39278353 14889.44 \n",
|
|
"Low 2642 39059436 14784.04 \n",
|
|
"Medium 2636 61809955 23448.39 \n",
|
|
"High 2643 50317266 19037.94 \n",
|
|
"Highest Burden 2625 37787591 14395.27 \n",
|
|
"\n",
|
|
" Total Project GHGReductions \\\n",
|
|
" sum \n",
|
|
"CES_quintile \n",
|
|
"Lowest Burden 2270359 \n",
|
|
"Low 202457 \n",
|
|
"Medium 265818 \n",
|
|
"High 210633 \n",
|
|
"Highest Burden 159776 \n",
|
|
"\n",
|
|
" Is Benefit Disadvantaged Communities \n",
|
|
" mean \n",
|
|
"CES_quintile \n",
|
|
"Lowest Burden 0.04 \n",
|
|
"Low 0.55 \n",
|
|
"Medium 0.84 \n",
|
|
"High 0.87 \n",
|
|
"Highest Burden 0.72 \n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"/tmp/ipykernel_30782/1664997265.py:41: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
|
|
" ces_analysis = merged_data.groupby('CES_quintile').agg({\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# Clean census tract IDs in both dataframes\n",
|
|
"def standardize_tract(tract):\n",
|
|
" if pd.isna(tract):\n",
|
|
" return None\n",
|
|
" if isinstance(tract, (int, float)):\n",
|
|
" return str(int(tract))\n",
|
|
" return str(tract).strip()\n",
|
|
"\n",
|
|
"# Check the data first\n",
|
|
"print(\"\\nCES Tract Examples:\")\n",
|
|
"print(gdf['Tract'].head())\n",
|
|
"print(\"\\nCCI Tract Examples:\")\n",
|
|
"print(data_filtered['Census Tract'].head())\n",
|
|
"\n",
|
|
"# Clean and standardize\n",
|
|
"gdf['Tract_clean'] = gdf['Tract'].apply(standardize_tract)\n",
|
|
"data_filtered['Tract_clean'] = data_filtered['Census Tract'].apply(standardize_tract)\n",
|
|
"\n",
|
|
"# Check for missing tracts\n",
|
|
"print(\"\\nMissing Tract Counts:\")\n",
|
|
"print(\"CES missing tracts:\", gdf['Tract_clean'].isna().sum())\n",
|
|
"print(\"CCI missing tracts:\", data_filtered['Tract_clean'].isna().sum())\n",
|
|
"\n",
|
|
"# Merge datasets, excluding null tracts\n",
|
|
"merged_data = pd.merge(\n",
|
|
" data_filtered[data_filtered['Tract_clean'].notna()], \n",
|
|
" gdf[['Tract_clean', 'CIscore', 'CIscoreP', 'PollBurd', 'Poverty', 'TotPop19']], \n",
|
|
" on='Tract_clean',\n",
|
|
" how='inner'\n",
|
|
")\n",
|
|
"\n",
|
|
"print(\"\\nMerged Data Summary:\")\n",
|
|
"print(\"Total rows:\", len(merged_data))\n",
|
|
"print(\"Unique tracts:\", merged_data['Tract_clean'].nunique())\n",
|
|
"\n",
|
|
"# Basic analysis of funding by CES score\n",
|
|
"print(\"\\nFunding Distribution by CalEnviroScreen Score Quintiles:\")\n",
|
|
"merged_data['CES_quintile'] = pd.qcut(merged_data['CIscore'], q=5, \n",
|
|
" labels=['Lowest Burden', 'Low', 'Medium', 'High', 'Highest Burden'])\n",
|
|
"\n",
|
|
"ces_analysis = merged_data.groupby('CES_quintile').agg({\n",
|
|
" 'Total Program GGRFFunding': ['count', 'sum', 'mean'],\n",
|
|
" 'Total Project GHGReductions': 'sum',\n",
|
|
" 'Is Benefit Disadvantaged Communities': 'mean'\n",
|
|
"}).round(2)\n",
|
|
"\n",
|
|
"print(ces_analysis)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 23,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"/tmp/ipykernel_30782/541290860.py:6: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
|
|
" merged_data.groupby('CES_quintile')['Total Program GGRFFunding'].mean().plot(\n",
|
|
"/tmp/ipykernel_30782/541290860.py:12: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
|
|
" merged_data.groupby('CES_quintile')['Total Project GHGReductions'].sum().plot(\n",
|
|
"/tmp/ipykernel_30782/541290860.py:18: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
|
|
" merged_data.groupby('CES_quintile')['Is Benefit Disadvantaged Communities'].mean().plot(\n",
|
|
"/tmp/ipykernel_30782/541290860.py:24: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
|
|
" merged_data.groupby('CES_quintile')['Total Program GGRFFunding'].count().plot(\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
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"text/plain": [
|
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"<Figure size 1500x1200 with 4 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"\n",
|
|
"Program Types by Environmental Burden:\n",
|
|
"Program Name Low-Income Weatherization Program \\\n",
|
|
"CES_quintile \n",
|
|
"Lowest Burden 3.69 \n",
|
|
"Low 28.77 \n",
|
|
"Medium 50.45 \n",
|
|
"High 45.19 \n",
|
|
"Highest Burden 30.88 \n",
|
|
"\n",
|
|
"Program Name Sustainable Agricultural Lands Conservation Program \\\n",
|
|
"CES_quintile \n",
|
|
"Lowest Burden 22.05 \n",
|
|
"Low 0.00 \n",
|
|
"Medium 0.00 \n",
|
|
"High 0.00 \n",
|
|
"Highest Burden 0.00 \n",
|
|
"\n",
|
|
"Program Name Transformative Climate Communities Waste Diversion \\\n",
|
|
"CES_quintile \n",
|
|
"Lowest Burden 0.00 0.34 \n",
|
|
"Low 0.48 0.23 \n",
|
|
"Medium 0.94 0.15 \n",
|
|
"High 0.33 0.12 \n",
|
|
"Highest Burden 3.14 0.14 \n",
|
|
"\n",
|
|
"Program Name Water-Energy Efficiency Woodsmoke Reduction Program \\\n",
|
|
"CES_quintile \n",
|
|
"Lowest Burden 7.13 6.00 \n",
|
|
"Low 8.02 1.50 \n",
|
|
"Medium 9.63 0.36 \n",
|
|
"High 4.31 0.01 \n",
|
|
"Highest Burden 3.38 0.03 \n",
|
|
"\n",
|
|
"Program Name Workforce Training and Development \n",
|
|
"CES_quintile \n",
|
|
"Lowest Burden 0.07 \n",
|
|
"Low 0.07 \n",
|
|
"Medium 0.29 \n",
|
|
"High 0.36 \n",
|
|
"Highest Burden 0.21 \n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import matplotlib.pyplot as plt\n",
|
|
"\n",
|
|
"fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(15, 12))\n",
|
|
"\n",
|
|
"# Average Funding by CES Score\n",
|
|
"merged_data.groupby('CES_quintile')['Total Program GGRFFunding'].mean().plot(\n",
|
|
" kind='bar', ax=ax1, color='skyblue')\n",
|
|
"ax1.set_title('Average Funding by Environmental Burden')\n",
|
|
"ax1.set_ylabel('Average Funding ($)')\n",
|
|
"\n",
|
|
"# GHG Reductions\n",
|
|
"merged_data.groupby('CES_quintile')['Total Project GHGReductions'].sum().plot(\n",
|
|
" kind='bar', ax=ax2, color='skyblue')\n",
|
|
"ax2.set_title('Total GHG Reductions by Environmental Burden')\n",
|
|
"ax2.set_ylabel('GHG Reductions')\n",
|
|
"\n",
|
|
"# DAC Benefit Rate\n",
|
|
"merged_data.groupby('CES_quintile')['Is Benefit Disadvantaged Communities'].mean().plot(\n",
|
|
" kind='bar', ax=ax3, color='skyblue')\n",
|
|
"ax3.set_title('DAC Benefit Rate by Environmental Burden')\n",
|
|
"ax3.set_ylabel('Proportion Benefiting DACs')\n",
|
|
"\n",
|
|
"# Project Counts\n",
|
|
"merged_data.groupby('CES_quintile')['Total Program GGRFFunding'].count().plot(\n",
|
|
" kind='bar', ax=ax4, color='skyblue')\n",
|
|
"ax4.set_title('Number of Projects by Environmental Burden')\n",
|
|
"ax4.set_ylabel('Number of Projects')\n",
|
|
"\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.show()\n",
|
|
"\n",
|
|
"# Also examine program types by CES quintile\n",
|
|
"print(\"\\nProgram Types by Environmental Burden:\")\n",
|
|
"program_dist = pd.crosstab(\n",
|
|
" merged_data['CES_quintile'], \n",
|
|
" merged_data['Program Name'], \n",
|
|
" values=merged_data['Total Program GGRFFunding'],\n",
|
|
" aggfunc='sum'\n",
|
|
")/1e6 # Convert to millions\n",
|
|
"\n",
|
|
"print(program_dist.round(2))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 24,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Distribution using CES Percentile Thresholds:\n",
|
|
" Total Program GGRFFunding \\\n",
|
|
" count sum mean \n",
|
|
"CES_category \n",
|
|
"High Burden (50-75%) 2932 42831569 14608.31 \n",
|
|
"Highest Burden (75-100%) 7661 146493459 19121.98 \n",
|
|
"Low Burden (0-25%) 1182 7475213 6324.21 \n",
|
|
"Moderate Burden (25-50%) 1409 31452360 22322.47 \n",
|
|
"\n",
|
|
" Total Project GHGReductions \\\n",
|
|
" sum \n",
|
|
"CES_category \n",
|
|
"High Burden (50-75%) 218725 \n",
|
|
"Highest Burden (75-100%) 622363 \n",
|
|
"Low Burden (0-25%) 163482 \n",
|
|
"Moderate Burden (25-50%) 2104473 \n",
|
|
"\n",
|
|
" Is Benefit Disadvantaged Communities \n",
|
|
" mean \n",
|
|
"CES_category \n",
|
|
"High Burden (50-75%) 0.56 \n",
|
|
"Highest Burden (75-100%) 0.81 \n",
|
|
"Low Burden (0-25%) 0.01 \n",
|
|
"Moderate Burden (25-50%) 0.07 \n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
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",
|
|
"text/plain": [
|
|
"<Figure size 1500x1200 with 4 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Create meaningful CES score categories\n",
|
|
"def categorize_ces(score):\n",
|
|
" if score >= 75: # Top 25% - most burdened\n",
|
|
" return 'Highest Burden (75-100%)'\n",
|
|
" elif score >= 50:\n",
|
|
" return 'High Burden (50-75%)'\n",
|
|
" elif score >= 25:\n",
|
|
" return 'Moderate Burden (25-50%)'\n",
|
|
" else: # Bottom 25% - least burdened\n",
|
|
" return 'Low Burden (0-25%)'\n",
|
|
"\n",
|
|
"# Add new categorization\n",
|
|
"merged_data['CES_category'] = merged_data['CIscoreP'].apply(categorize_ces)\n",
|
|
"\n",
|
|
"# Analyze distribution with new categories\n",
|
|
"ces_analysis_new = merged_data.groupby('CES_category').agg({\n",
|
|
" 'Total Program GGRFFunding': ['count', 'sum', 'mean'],\n",
|
|
" 'Total Project GHGReductions': 'sum',\n",
|
|
" 'Is Benefit Disadvantaged Communities': 'mean'\n",
|
|
"}).round(2)\n",
|
|
"\n",
|
|
"print(\"Distribution using CES Percentile Thresholds:\")\n",
|
|
"print(ces_analysis_new)\n",
|
|
"\n",
|
|
"# Visualize with new categories\n",
|
|
"fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(15, 12))\n",
|
|
"\n",
|
|
"# Average Funding\n",
|
|
"merged_data.groupby('CES_category')['Total Program GGRFFunding'].mean().plot(\n",
|
|
" kind='bar', ax=ax1, color='skyblue')\n",
|
|
"ax1.set_title('Average Funding by Environmental Burden')\n",
|
|
"ax1.set_ylabel('Average Funding ($)')\n",
|
|
"\n",
|
|
"# GHG Reductions\n",
|
|
"merged_data.groupby('CES_category')['Total Project GHGReductions'].sum().plot(\n",
|
|
" kind='bar', ax=ax2, color='skyblue')\n",
|
|
"ax2.set_title('Total GHG Reductions by Environmental Burden')\n",
|
|
"ax2.set_ylabel('GHG Reductions')\n",
|
|
"\n",
|
|
"# DAC Benefit Rate\n",
|
|
"merged_data.groupby('CES_category')['Is Benefit Disadvantaged Communities'].mean().plot(\n",
|
|
" kind='bar', ax=ax3, color='skyblue')\n",
|
|
"ax3.set_title('DAC Benefit Rate by Environmental Burden')\n",
|
|
"ax3.set_ylabel('Proportion Benefiting DACs')\n",
|
|
"\n",
|
|
"# Project Counts\n",
|
|
"merged_data.groupby('CES_category')['Total Program GGRFFunding'].count().plot(\n",
|
|
" kind='bar', ax=ax4, color='skyblue')\n",
|
|
"ax4.set_title('Number of Projects by Environmental Burden')\n",
|
|
"ax4.set_ylabel('Number of Projects')\n",
|
|
"\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 25,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1500x1200 with 4 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Define category order\n",
|
|
"category_order = [\n",
|
|
" 'Low Burden (0-25%)', \n",
|
|
" 'Moderate Burden (25-50%)', \n",
|
|
" 'High Burden (50-75%)', \n",
|
|
" 'Highest Burden (75-100%)'\n",
|
|
"]\n",
|
|
"\n",
|
|
"# Create visualizations with ordered categories\n",
|
|
"fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(15, 12))\n",
|
|
"\n",
|
|
"# Average Funding\n",
|
|
"merged_data.groupby('CES_category')['Total Program GGRFFunding'].mean()[category_order].plot(\n",
|
|
" kind='bar', ax=ax1, color='skyblue')\n",
|
|
"ax1.set_title('Average Funding by Environmental Burden')\n",
|
|
"ax1.set_ylabel('Average Funding ($)')\n",
|
|
"\n",
|
|
"# GHG Reductions\n",
|
|
"merged_data.groupby('CES_category')['Total Project GHGReductions'].sum()[category_order].plot(\n",
|
|
" kind='bar', ax=ax2, color='skyblue')\n",
|
|
"ax2.set_title('Total GHG Reductions by Environmental Burden')\n",
|
|
"ax2.set_ylabel('GHG Reductions')\n",
|
|
"\n",
|
|
"# DAC Benefit Rate\n",
|
|
"merged_data.groupby('CES_category')['Is Benefit Disadvantaged Communities'].mean()[category_order].plot(\n",
|
|
" kind='bar', ax=ax3, color='skyblue')\n",
|
|
"ax3.set_title('DAC Benefit Rate by Environmental Burden')\n",
|
|
"ax3.set_ylabel('Proportion Benefiting DACs')\n",
|
|
"\n",
|
|
"# Project Counts\n",
|
|
"merged_data.groupby('CES_category')['Total Program GGRFFunding'].count()[category_order].plot(\n",
|
|
" kind='bar', ax=ax4, color='skyblue')\n",
|
|
"ax4.set_title('Number of Projects by Environmental Burden')\n",
|
|
"ax4.set_ylabel('Number of Projects')\n",
|
|
"\n",
|
|
"# Rotate x-labels for better readability\n",
|
|
"for ax in [ax1, ax2, ax3, ax4]:\n",
|
|
" ax.set_xticklabels(ax.get_xticklabels(), rotation=45, ha='right')\n",
|
|
"\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 26,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Agency Performance Overview:\n",
|
|
" Total Program GGRFFunding \\\n",
|
|
" count \n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 12329 \n",
|
|
"California Coastal Commission 17 \n",
|
|
"California Conservation Corps 766 \n",
|
|
"California Department of Community Services and... 6331 \n",
|
|
"California Department of Fish and Wildlife 8 \n",
|
|
"California Department of Food and Agriculture 1311 \n",
|
|
"California Department of Forestry and Fire Prot... 2047 \n",
|
|
"California Department of Resources Recycling an... 723 \n",
|
|
"California Department of Transportation 769 \n",
|
|
"California Department of Water Resources 4887 \n",
|
|
"California Energy Commission 119 \n",
|
|
"California Environmental Protection Agency 2 \n",
|
|
"California Governors Office of Emergency Services 63 \n",
|
|
"California Natural Resources Agency 213 \n",
|
|
"California State Coastal Conservancy 10 \n",
|
|
"California State Transportation Agency 135 \n",
|
|
"California State Water Resources Control Board 100 \n",
|
|
"California Strategic Growth Council 1200 \n",
|
|
"California Wildlife Conservation Board 17 \n",
|
|
"California Workforce Development Board 30 \n",
|
|
"San Francisco Bay Conservation and Development ... 74 \n",
|
|
"\n",
|
|
" \\\n",
|
|
" sum mean \n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 796368463 64593.111 \n",
|
|
"California Coastal Commission 2667413 156906.647 \n",
|
|
"California Conservation Corps 47161363 61568.359 \n",
|
|
"California Department of Community Services and... 158967758 25109.423 \n",
|
|
"California Department of Fish and Wildlife 16171301 2021412.625 \n",
|
|
"California Department of Food and Agriculture 338161549 257941.685 \n",
|
|
"California Department of Forestry and Fire Prot... 967562562 472673.455 \n",
|
|
"California Department of Resources Recycling an... 175129441 242226.059 \n",
|
|
"California Department of Transportation 785906434 1021984.960 \n",
|
|
"California Department of Water Resources 52470432 10736.737 \n",
|
|
"California Energy Commission 140791478 1183121.664 \n",
|
|
"California Environmental Protection Agency 2560940 1280470.000 \n",
|
|
"California Governors Office of Emergency Services 31037358 492656.476 \n",
|
|
"California Natural Resources Agency 145023190 680860.047 \n",
|
|
"California State Coastal Conservancy 7218244 721824.400 \n",
|
|
"California State Transportation Agency 771556000 5715229.630 \n",
|
|
"California State Water Resources Control Board 118601405 1186014.050 \n",
|
|
"California Strategic Growth Council 1557246299 1297705.249 \n",
|
|
"California Wildlife Conservation Board 12574800 739694.118 \n",
|
|
"California Workforce Development Board 24428357 814278.567 \n",
|
|
"San Francisco Bay Conservation and Development ... 8680291 117301.230 \n",
|
|
"\n",
|
|
" Total Project GHGReductions \\\n",
|
|
" sum \n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 509888 \n",
|
|
"California Coastal Commission 0 \n",
|
|
"California Conservation Corps 292164 \n",
|
|
"California Department of Community Services and... 583978 \n",
|
|
"California Department of Fish and Wildlife 405413 \n",
|
|
"California Department of Food and Agriculture 21019827 \n",
|
|
"California Department of Forestry and Fire Prot... 5176685 \n",
|
|
"California Department of Resources Recycling an... 1884352 \n",
|
|
"California Department of Transportation 5709880 \n",
|
|
"California Department of Water Resources 373494 \n",
|
|
"California Energy Commission 3553812 \n",
|
|
"California Environmental Protection Agency 0 \n",
|
|
"California Governors Office of Emergency Services 0 \n",
|
|
"California Natural Resources Agency 53327 \n",
|
|
"California State Coastal Conservancy 0 \n",
|
|
"California State Transportation Agency 9076036 \n",
|
|
"California State Water Resources Control Board -3620 \n",
|
|
"California Strategic Growth Council 17127711 \n",
|
|
"California Wildlife Conservation Board 124761 \n",
|
|
"California Workforce Development Board 0 \n",
|
|
"San Francisco Bay Conservation and Development ... 0 \n",
|
|
"\n",
|
|
" Is Benefit Disadvantaged Communities \n",
|
|
" mean \n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 0.000 \n",
|
|
"California Coastal Commission 0.000 \n",
|
|
"California Conservation Corps 0.000 \n",
|
|
"California Department of Community Services and... 0.917 \n",
|
|
"California Department of Fish and Wildlife 0.000 \n",
|
|
"California Department of Food and Agriculture 0.053 \n",
|
|
"California Department of Forestry and Fire Prot... 0.084 \n",
|
|
"California Department of Resources Recycling an... 0.032 \n",
|
|
"California Department of Transportation 0.095 \n",
|
|
"California Department of Water Resources 0.441 \n",
|
|
"California Energy Commission 0.000 \n",
|
|
"California Environmental Protection Agency 0.000 \n",
|
|
"California Governors Office of Emergency Services 0.000 \n",
|
|
"California Natural Resources Agency 0.150 \n",
|
|
"California State Coastal Conservancy 0.000 \n",
|
|
"California State Transportation Agency 0.193 \n",
|
|
"California State Water Resources Control Board 0.000 \n",
|
|
"California Strategic Growth Council 0.016 \n",
|
|
"California Wildlife Conservation Board 0.000 \n",
|
|
"California Workforce Development Board 0.000 \n",
|
|
"San Francisco Bay Conservation and Development ... 0.000 \n",
|
|
"\n",
|
|
"Agency Performance in Multi-County Projects:\n",
|
|
" Total Program GGRFFunding \\\n",
|
|
" count \n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 25 \n",
|
|
"California Conservation Corps 9 \n",
|
|
"California Department of Food and Agriculture 41 \n",
|
|
"California Department of Forestry and Fire Prot... 339 \n",
|
|
"California Department of Resources Recycling an... 23 \n",
|
|
"California Department of Transportation 158 \n",
|
|
"California Energy Commission 9 \n",
|
|
"California Natural Resources Agency 7 \n",
|
|
"California State Transportation Agency 57 \n",
|
|
"California State Water Resources Control Board 45 \n",
|
|
"California Strategic Growth Council 32 \n",
|
|
"California Wildlife Conservation Board 7 \n",
|
|
"\n",
|
|
" \\\n",
|
|
" sum mean \n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 2104048 84161.920 \n",
|
|
"California Conservation Corps 1248353 138705.889 \n",
|
|
"California Department of Food and Agriculture 6296871 153582.220 \n",
|
|
"California Department of Forestry and Fire Prot... 32351508 95432.177 \n",
|
|
"California Department of Resources Recycling an... 6962204 302704.522 \n",
|
|
"California Department of Transportation 162505329 1028514.741 \n",
|
|
"California Energy Commission 12379666 1375518.444 \n",
|
|
"California Natural Resources Agency 2879148 411306.857 \n",
|
|
"California State Transportation Agency 232590000 4080526.316 \n",
|
|
"California State Water Resources Control Board 46265001 1028111.133 \n",
|
|
"California Strategic Growth Council 11948291 373384.094 \n",
|
|
"California Wildlife Conservation Board 3544200 506314.286 \n",
|
|
"\n",
|
|
" Total Project GHGReductions \\\n",
|
|
" sum \n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board -413 \n",
|
|
"California Conservation Corps 842 \n",
|
|
"California Department of Food and Agriculture 42951 \n",
|
|
"California Department of Forestry and Fire Prot... 185424 \n",
|
|
"California Department of Resources Recycling an... 35434 \n",
|
|
"California Department of Transportation 2460280 \n",
|
|
"California Energy Commission 501007 \n",
|
|
"California Natural Resources Agency 1191 \n",
|
|
"California State Transportation Agency 2748646 \n",
|
|
"California State Water Resources Control Board -3234 \n",
|
|
"California Strategic Growth Council 251149 \n",
|
|
"California Wildlife Conservation Board 0 \n",
|
|
"\n",
|
|
" Is Benefit Disadvantaged Communities \n",
|
|
" mean \n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 0.000 \n",
|
|
"California Conservation Corps 0.000 \n",
|
|
"California Department of Food and Agriculture 0.000 \n",
|
|
"California Department of Forestry and Fire Prot... 0.168 \n",
|
|
"California Department of Resources Recycling an... 0.130 \n",
|
|
"California Department of Transportation 0.089 \n",
|
|
"California Energy Commission 0.000 \n",
|
|
"California Natural Resources Agency 0.000 \n",
|
|
"California State Transportation Agency 0.105 \n",
|
|
"California State Water Resources Control Board 0.000 \n",
|
|
"California Strategic Growth Council 0.062 \n",
|
|
"California Wildlife Conservation Board 0.000 \n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"/home/dadams/Repos/california_equity_git/.venv/lib/python3.12/site-packages/matplotlib/text.py:1465: FutureWarning: Calling float on a single element Series is deprecated and will raise a TypeError in the future. Use float(ser.iloc[0]) instead\n",
|
|
" x = float(self.convert_xunits(x))\n"
|
|
]
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},
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{
|
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"data": {
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",
|
|
"text/plain": [
|
|
"<Figure size 1500x1000 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Agency Performance Analysis\n",
|
|
"agency_performance = data_filtered.groupby('Agency Name').agg({\n",
|
|
" 'Total Program GGRFFunding': ['count', 'sum', 'mean'],\n",
|
|
" 'Total Project GHGReductions': 'sum',\n",
|
|
" 'Is Benefit Disadvantaged Communities': 'mean'\n",
|
|
"}).round(3)\n",
|
|
"\n",
|
|
"print(\"Agency Performance Overview:\")\n",
|
|
"print(agency_performance)\n",
|
|
"\n",
|
|
"# Add efficiency metrics\n",
|
|
"agency_performance['ghg_per_dollar'] = (\n",
|
|
" agency_performance[('Total Project GHGReductions', 'sum')] / \n",
|
|
" agency_performance[('Total Program GGRFFunding', 'sum')]\n",
|
|
")\n",
|
|
"\n",
|
|
"# Look at agency patterns in multi-county projects\n",
|
|
"multi_county = data_filtered[data_filtered['County'].str.contains(',', na=False)]\n",
|
|
"multi_agency_patterns = multi_county.groupby('Agency Name').agg({\n",
|
|
" 'Total Program GGRFFunding': ['count', 'sum', 'mean'],\n",
|
|
" 'Total Project GHGReductions': 'sum',\n",
|
|
" 'Is Benefit Disadvantaged Communities': 'mean'\n",
|
|
"}).round(3)\n",
|
|
"\n",
|
|
"print(\"\\nAgency Performance in Multi-County Projects:\")\n",
|
|
"print(multi_agency_patterns)\n",
|
|
"\n",
|
|
"# Visualize agency performance metrics\n",
|
|
"plt.figure(figsize=(15, 10))\n",
|
|
"\n",
|
|
"# Plot GHG efficiency vs DAC benefit rate by agency\n",
|
|
"plt.scatter(\n",
|
|
" agency_performance['ghg_per_dollar'],\n",
|
|
" agency_performance[('Is Benefit Disadvantaged Communities', 'mean')],\n",
|
|
" s=agency_performance[('Total Program GGRFFunding', 'sum')]/1e6, # Size by total funding\n",
|
|
" alpha=0.6\n",
|
|
")\n",
|
|
"\n",
|
|
"# Add agency labels\n",
|
|
"for idx, row in agency_performance.iterrows():\n",
|
|
" plt.annotate(idx[:20] + '...' if len(idx) > 20 else idx,\n",
|
|
" (row['ghg_per_dollar'], \n",
|
|
" row[('Is Benefit Disadvantaged Communities', 'mean')]),\n",
|
|
" xytext=(5, 5), textcoords='offset points')\n",
|
|
"\n",
|
|
"plt.xlabel('GHG Reduction per Dollar')\n",
|
|
"plt.ylabel('DAC Benefit Rate')\n",
|
|
"plt.title('Agency Performance: Climate Impact vs Equity\\nSize = Total Funding')\n",
|
|
"\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 27,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1500x1000 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure(figsize=(15, 10))\n",
|
|
"\n",
|
|
"# Create shorter but still meaningful agency names\n",
|
|
"agency_shortnames = {\n",
|
|
" 'California Air Resources Board': 'CARB',\n",
|
|
" 'California Department of Community Services and...': 'Community Services',\n",
|
|
" 'California Department of Food and Agriculture': 'CDFA',\n",
|
|
" 'California Department of Forestry and Fire Prot...': 'CalFire',\n",
|
|
" 'California Department of Resources Recycling an...': 'CalRecycle',\n",
|
|
" 'California Department of Transportation': 'Caltrans',\n",
|
|
" 'California Department of Water Resources': 'Water Resources',\n",
|
|
" 'California Energy Commission': 'Energy Commission',\n",
|
|
" 'California State Transportation Agency': 'CalSTA',\n",
|
|
" 'California Strategic Growth Council': 'SGC',\n",
|
|
" # Add other agencies as needed\n",
|
|
"}\n",
|
|
"\n",
|
|
"# Plot GHG efficiency vs DAC benefit rate by agency\n",
|
|
"plt.scatter(\n",
|
|
" agency_performance['ghg_per_dollar'],\n",
|
|
" agency_performance[('Is Benefit Disadvantaged Communities', 'mean')],\n",
|
|
" s=agency_performance[('Total Program GGRFFunding', 'sum')]/1e6, # Size by total funding\n",
|
|
" alpha=0.6\n",
|
|
")\n",
|
|
"\n",
|
|
"# Add agency labels with shorter names\n",
|
|
"for idx, row in agency_performance.iterrows():\n",
|
|
" short_name = agency_shortnames.get(idx, idx[:15] + '...')\n",
|
|
" plt.annotate(short_name,\n",
|
|
" (row['ghg_per_dollar'], \n",
|
|
" row[('Is Benefit Disadvantaged Communities', 'mean')]),\n",
|
|
" xytext=(5, 5), textcoords='offset points')\n",
|
|
"\n",
|
|
"plt.xlabel('GHG Reduction per Dollar')\n",
|
|
"plt.ylabel('DAC Benefit Rate')\n",
|
|
"plt.title('Agency Performance: Climate Impact vs Equity\\nSize = Total Funding')\n",
|
|
"\n",
|
|
"# Add legend for bubble size\n",
|
|
"legend_elements = [plt.scatter([], [], s=s, label=f'${l}B', alpha=0.6, color='blue') \n",
|
|
" for s, l in zip([100, 500, 1000], ['0.1', '0.5', '1.0'])]\n",
|
|
"plt.legend(handles=legend_elements, title='Total Funding', \n",
|
|
" bbox_to_anchor=(1.05, 1), loc='upper left')\n",
|
|
"\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"\n",
|
|
"1. **Strong GHG Performers**\n",
|
|
"- California Department of Food and Agriculture shows highest GHG efficiency (~0.06 reductions per dollar)\n",
|
|
"- California Energy Commission also performs well (~0.03)\n",
|
|
"- However, both show low DAC benefit rates (0-5%)\n",
|
|
"\n",
|
|
"1. **Strong Equity Performers**\n",
|
|
"- California Department of Community Services leads in DAC benefits (91.7%)\n",
|
|
"- Department of Water Resources shows good equity performance (44.1%)\n",
|
|
"- But these have lower GHG efficiency\n",
|
|
"\n",
|
|
"1. **Large Scale Implementers** (shown by bubble size)\n",
|
|
"- Strategic Growth Council ($1.56B)\n",
|
|
"- CalSTA ($772M)\n",
|
|
"- CARB ($796M)\n",
|
|
"- Department of Forestry and Fire Protection ($968M)\n",
|
|
"\n",
|
|
"1. **Multi-County Implementation**\n",
|
|
"- Transportation agencies lead in multi-county projects (CalSTA: 57 projects, $233M)\n",
|
|
"- CalFire shows significant multi-county work (339 projects)\n",
|
|
"- Strategic Growth Council's multi-county projects show lower DAC rates than their overall portfolio\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 28,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Percentage of Agency Funding by Environmental Burden Category:\n",
|
|
"CES_category High Burden (50-75%) \\\n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 20.81 \n",
|
|
"California Department of Community Services and... 19.77 \n",
|
|
"California Department of Resources Recycling an... 26.02 \n",
|
|
"California Department of Water Resources 27.36 \n",
|
|
"California Energy Commission 14.29 \n",
|
|
"California Strategic Growth Council 1.78 \n",
|
|
"\n",
|
|
"CES_category Highest Burden (75-100%) \\\n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 4.92 \n",
|
|
"California Department of Community Services and... 77.98 \n",
|
|
"California Department of Resources Recycling an... 41.17 \n",
|
|
"California Department of Water Resources 50.91 \n",
|
|
"California Energy Commission 78.57 \n",
|
|
"California Strategic Growth Council 16.38 \n",
|
|
"\n",
|
|
"CES_category Low Burden (0-25%) \\\n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 36.65 \n",
|
|
"California Department of Community Services and... 0.29 \n",
|
|
"California Department of Resources Recycling an... 21.83 \n",
|
|
"California Department of Water Resources 9.21 \n",
|
|
"California Energy Commission 7.14 \n",
|
|
"California Strategic Growth Council 3.15 \n",
|
|
"\n",
|
|
"CES_category Moderate Burden (25-50%) \n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 37.63 \n",
|
|
"California Department of Community Services and... 1.96 \n",
|
|
"California Department of Resources Recycling an... 10.98 \n",
|
|
"California Department of Water Resources 12.51 \n",
|
|
"California Energy Commission 0.00 \n",
|
|
"California Strategic Growth Council 78.69 \n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<Figure size 1500x800 with 0 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
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"text/plain": [
|
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"<Figure size 640x480 with 1 Axes>"
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]
|
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},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
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"name": "stdout",
|
|
"output_type": "stream",
|
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"text": [
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"\n",
|
|
"Average Project Size (Millions $) by Environmental Burden Category:\n",
|
|
"CES_category High Burden (50-75%) \\\n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 0.01 \n",
|
|
"California Department of Community Services and... 0.03 \n",
|
|
"California Department of Resources Recycling an... 0.01 \n",
|
|
"California Department of Water Resources 0.01 \n",
|
|
"California Energy Commission 0.07 \n",
|
|
"California Strategic Growth Council 0.00 \n",
|
|
"\n",
|
|
"CES_category Highest Burden (75-100%) \\\n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 0.01 \n",
|
|
"California Department of Community Services and... 0.02 \n",
|
|
"California Department of Resources Recycling an... 0.01 \n",
|
|
"California Department of Water Resources 0.01 \n",
|
|
"California Energy Commission 0.07 \n",
|
|
"California Strategic Growth Council 0.01 \n",
|
|
"\n",
|
|
"CES_category Low Burden (0-25%) \\\n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 0.01 \n",
|
|
"California Department of Community Services and... 0.07 \n",
|
|
"California Department of Resources Recycling an... 0.01 \n",
|
|
"California Department of Water Resources 0.00 \n",
|
|
"California Energy Commission 0.07 \n",
|
|
"California Strategic Growth Council 0.85 \n",
|
|
"\n",
|
|
"CES_category Moderate Burden (25-50%) \n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 0.01 \n",
|
|
"California Department of Community Services and... 0.03 \n",
|
|
"California Department of Resources Recycling an... 0.01 \n",
|
|
"California Department of Water Resources 0.00 \n",
|
|
"California Energy Commission NaN \n",
|
|
"California Strategic Growth Council 1.93 \n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# Analyze agency performance across CES score categories\n",
|
|
"merged_agency_ces = merged_data.groupby(['Agency Name', 'CES_category']).agg({\n",
|
|
" 'Total Program GGRFFunding': ['count', 'sum', 'mean'],\n",
|
|
" 'Total Project GHGReductions': 'sum',\n",
|
|
" 'Is Benefit Disadvantaged Communities': 'mean'\n",
|
|
"}).round(3)\n",
|
|
"\n",
|
|
"# Calculate percentage of agency funding going to each CES category\n",
|
|
"agency_funding = pd.pivot_table(\n",
|
|
" merged_data,\n",
|
|
" values='Total Program GGRFFunding',\n",
|
|
" index='Agency Name',\n",
|
|
" columns='CES_category',\n",
|
|
" aggfunc='sum'\n",
|
|
").fillna(0)\n",
|
|
"\n",
|
|
"# Calculate percentages\n",
|
|
"agency_funding_pct = agency_funding.div(agency_funding.sum(axis=1), axis=0) * 100\n",
|
|
"\n",
|
|
"print(\"Percentage of Agency Funding by Environmental Burden Category:\")\n",
|
|
"print(agency_funding_pct.round(2))\n",
|
|
"\n",
|
|
"# Visualize distribution patterns\n",
|
|
"plt.figure(figsize=(15, 8))\n",
|
|
"agency_funding_pct.plot(kind='barh', stacked=True)\n",
|
|
"plt.title('Distribution of Agency Funding Across Environmental Burden Categories')\n",
|
|
"plt.xlabel('Percentage of Agency Funding')\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.show()\n",
|
|
"\n",
|
|
"# Look at average project size by burden category for each agency\n",
|
|
"avg_project_size = merged_data.groupby(['Agency Name', 'CES_category'])['Total Program GGRFFunding'].mean()/1e6\n",
|
|
"avg_project_size = avg_project_size.unstack()\n",
|
|
"print(\"\\nAverage Project Size (Millions $) by Environmental Burden Category:\")\n",
|
|
"print(avg_project_size.round(2))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"This data reveals fascinating patterns in how different agencies serve communities with varying environmental burdens:\n",
|
|
"\n",
|
|
"1. **Strong Environmental Justice Focus**\n",
|
|
"- Community Services: 78% of funding to highest burden areas\n",
|
|
"- Energy Commission: 79% to highest burden areas\n",
|
|
"- Water Resources: 51% to highest burden areas\n",
|
|
"- CalRecycle: 41% to highest burden areas\n",
|
|
"\n",
|
|
"2. **More Dispersed Distribution**\n",
|
|
"- CARB shows relatively even distribution:\n",
|
|
" * 37.6% Moderate burden\n",
|
|
" * 36.7% Low burden\n",
|
|
" * 20.8% High burden\n",
|
|
" * Only 4.9% to highest burden areas\n",
|
|
"\n",
|
|
"3. **Unique Strategic Growth Council Pattern**\n",
|
|
"- Heavy focus on moderate burden areas (78.7%)\n",
|
|
"- Limited focus on highest burden areas (16.4%)\n",
|
|
"- Largest average project sizes:\n",
|
|
" * $1.93M in moderate burden areas\n",
|
|
" * $0.85M in low burden areas\n",
|
|
" * Much smaller in high burden areas\n",
|
|
"\n",
|
|
"4. **Project Size Variations**\n",
|
|
"- Most agencies maintain consistent project sizes across burden categories\n",
|
|
"- Notable exceptions:\n",
|
|
" * Strategic Growth Council: Much larger projects in moderate burden areas\n",
|
|
" * Community Services: Larger projects in low burden areas\n",
|
|
"\n",
|
|
"This suggests:\n",
|
|
"1. Different agency missions lead to different environmental justice approaches\n",
|
|
"2. Some agencies specifically target high-burden areas\n",
|
|
"3. Project size might be influenced by community capacity\n",
|
|
"4. Need for better coordination in highest burden areas\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 29,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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ooVdeeUXnz5/XzJkzFRgYqD/++EPZsmWLd5vGJfp+v3LlirU7yK+//vqJ2ovSokUL5cuXT6NGjbLelJTQ4//27dsKDAzU6dOn9fbbbytXrlzatm2bBg4cqLNnz8Z6n+P8+fN148YNvf3227JYLBo3bpxee+01/fXXX/F2X7lixQqlSZMmwT0nzJkzR56ennrvvffk6empH3/8UYMGDdL169f16aefSlK855vIyEg1btxYv/zyi7p27apChQrp4MGD+uyzz/Tnn3/avAOtY8eOWrRokdq3b68KFSpoy5YtatCgQayYEntcdO/eXZkyZdKgQYN069atZDt/AACA5w/5p2Pmn49jL+dzcXGRt7e3XnvtNaVNm1bvvvuuWrdurfr168vT01NZsmRR9uzZNWrUKOsrmqLyFHuGDh2qIUOGqFKlSho2bJhcXFz022+/6ccff1TdunXtzpOYv5Wlx+elknTmzBmVK1dO165dU9euXVWwYEGdPn1a3333nW7fvq08efKocuXKCgkJ0bvvvmvTflRBrkmTJo/dpiNHjpTFYtF//vMfXbhwQZMmTVLt2rW1b98+pUmTRu3bt9ewYcO0cOFCm27r79+/r++++07NmzdPUM8C9o7L1KlTx3qqf8yYMXJyclL//v0VHh6ucePGqW3btvrtt98kSa1atdLUqVO1atUqtWjRwjrf7du39cMPP6hjx4423e7bM3z4cLm4uKh///66d++eXFxcrMdk2bJlNXr0aJ0/f16TJ0/W1q1btXfvXps4IyIiFBQUpPLly2v8+PHauHGjJkyYoLx58+qdd96xWVZISIju37+vXr166cqVKxo3bpxatmypmjVravPmzfrPf/6jY8eOacqUKerfv79NMXPevHkKDg5WUFCQxo4dq9u3b2v69OmqUqWK9u7da3N8PS6mTJkyafr06XrnnXfUrFkz601BxYoVk/TowYi//vpLnTp1UtasWfX777/ryy+/1O+//65ff/3V7o0kCRG13yMjI3X69GkNHz5cbm5uatmy5RO1Jz16vVq9evX0xhtvqF27dsqSJYuMMWrSpIl++eUXdevWTYUKFdL333+v4ODgWPMn97UQe27fvq1NmzapWrVqypUrV4LWa/LkyWrcuLHatm2r+/fv69tvv1WLFi20cuVKaz4d33Xg8+fPq0KFCtabcDJlyqQ1a9aoc+fOun79uvW1Gbdu3VLNmjV19uxZ9enTR1mzZtX8+fMVGhoaK6bEHBcPHz5UUFCQqlSpovHjx8vd3V0VK1ZMlvNHLAYAALw0evToYaL/975s2TIjyYwYMcJmutdff91YLBZz7Ngx6zAPDw8THBwcq83bt2/HGrZ9+3Yjyfzvf/+zDgsNDTWSTGhoaJzxhYeHG0mmadOmscZdvXrVXLx40fqJvtzBgwcbSfF+GjRoYJ2+WbNmRpK5du2azTLu3Lljs4yrV6/GGWsUPz8/U7duXes8Bw8eNO3btzeSTI8ePazT/fzzz0aSCQkJsZl/7dq1NsMvXLhgXFxcTIMGDUxkZKR1ug8//NBIstkHUesd0+zZs40kc+LECWOMMdeuXTNeXl6mfPny5s6dOzbTRl9GgwYNjJ+fX6z2Tpw4YSSZ2bNnW4eVKFHCZM6c2Vy+fNk6bP/+/cbJycl06NAhVoxvvvmmTZvNmjUzGTJksH7/7LPPjCRz8eLFWMt/nKh9vGvXLuuwv//+27i5uZlmzZpZhw0cONC4urra7PcLFy6Y1KlTm8GDB8e7jKjfb1yfs2fP2sTj4uJic/zs37/fSDJTpkyxDmvdurXJnDmzefjwoXXY2bNnjZOTkxk2bJh1mL39LMk4OTmZ33//3WZ406ZNjYuLizl+/Lh12JkzZ4yXl5epVq2adVjUb6R27do2v4F3333XpEqVymYb+fn5GUlm27Zt1mHr1q0zkkyaNGnM33//bR0+c+bMWMd5rVq1TEBAgLl79651WGRkpKlUqZLJly/fE8VUpEgRExgYaGK6e/euiYiIsBl24sQJ4+rqarNN7f2m7Ylrvzs5OZmRI0fGWk5cbUqy+Y1F7dPWrVvbTJeY43/48OHGw8PD/PnnnzZtDBgwwKRKlcr8888/NnFlyJDBXLlyxTrd8uXLjSTzww8/xLsN0qVLZ4oXLx7vNNHZ+z/h7bffNu7u7ja/gbjON/PmzTNOTk7m559/thk+Y8YMI8ls3brVGGPM7t27jSTTt29fm+k6duwYa3sn9rioUqWKzXFpTNLOHwAA4PlE/um4+WdcgoOD49ynQUFBsWL89NNPbeaPyh8WL15sMzzmtjt69KhxcnIyzZo1i5W/RN9GgYGBNnlPQv9WNibheWmHDh2Mk5OT2blzZ6ztERVLVJ4XFhZmHXf//n2TMWNGu9eJoovaJtmzZzfXr1+3Dl+0aJGRZCZPnmwdVrFiRVO+fHmb+ZcuXfrYa0nGxH9cFihQIFY8hQoVMvfu3bMOnzx5spFkDh48aF337Nmzm+bNm9ssJyrun376yTos5n6KWkaePHlszh337983mTNnNkWLFrU5NlauXGkkmUGDBlmHRf0Wo+exxhhTsmRJU7p0aev3qN9ipkyZbM4xAwcONJJM8eLFzYMHD6zDW7dubVxcXKy52Y0bN0zatGlNly5dbJZz7tw54+PjYzM8oTFdvHgxVk4WxV6+uGDBgljbNOZ5JS5x7fe0adOatWvX2kwbV5v2rlcGBgYaSWbGjBk200ZdRx03bpx12MOHD03VqlVjnbdS4lpITFHHdJ8+feLbTDZi7oP79++bokWLmpo1a9oMj+s6cOfOnY2vr6+5dOmSzfA33njD+Pj4WNufMGGCkWSWLVtmnebOnTumYMGCNtv7SY6LAQMGxIorKeePuNDFOgAAL7HVq1crVapU6t27t83wfv36yRijNWvWPLaNNGnSWP/94MEDXb58Wf7+/kqbNq327NmTqHiiupuyd+d49erVlSlTJutn6tSpsaZZsmSJNmzYEOsT867tuJYzY8YMm2VEdXn8OOvXr7fOExAQoHnz5qlTp07WpyWlR10F+fj4qE6dOrp06ZL1U7p0aXl6elrvoNy4caP1rt/od85G3YH5JDZs2KAbN25owIABse6YfJK7c8+ePat9+/apY8eOSp8+vXV4sWLFVKdOHa1evTrWPN26dbP5XrVqVV2+fNm6L6LuBl2+fHmsJy4SomLFiipdurT1e65cudSkSROtW7fO2tVXhw4ddO/ePZuuoxYuXKiHDx8m+GmOQYMG2f2NRd8OklS7dm3r3bXSo23j7e2tv/76yzqsVatWunDhgk23Ut99950iIyPVqlWrx8YSGBiowoULW79HRERo/fr1atq0qfLkyWMd7uvrqzZt2uiXX36xbu8oXbt2tfkNVK1aVREREfr7779tpitcuLDNE7JRT9jUrFnT5i7lqOFR63nlyhX9+OOPatmypfUp7EuXLuny5csKCgrS0aNHY3WZldCY7HF1dbU+uR4REaHLly9bu+tP7Pkouuj7feHChWrdurU++ugjTZ48+YnblGIfF4k5/hcvXqyqVasqXbp0NueU2rVrKyIiwuYVA9Kj31v0p4qqVq0qSTa/SXuuX79ut5u2uET/PyFqn1etWlW3b9/W4cOHHzv/4sWLVahQIRUsWNBmvWrWrClJ1nNlVNeQUb0XROnVq5fN9yc5Lrp06RLraZDkOH8AAIDnC/mn4+af8XFzc7O7X8eMGZPo2OOybNkyRUZGatCgQbHeSR3fNkro38pRHpeXRkZGatmyZWrUqJHKlCkTa3lRsbRs2VJubm4KCQmxjlu3bp0uXbqU4L+FO3ToYJNXvP766/L19bXZfx06dNBvv/1m87qAkJAQ5cyZM1bPa3Gxd1zOnj071nSdOnWyeXd4zPzIYrGoRYsWWr16tW7evGmdbuHChcqePXuCjtfg4GCb/GjXrl26cOGCunfvbnNsNGjQQAULFtSqVatitWHvt2wvh2vRooV8fHys36Ny83bt2tl0M16+fHndv3/fmodv2LBB165dU+vWrW1+U6lSpVL58uXtPu2b0Jjsib497t69q0uXLqlChQqSlKScPWq/r1+/XrNnz1b+/PnVvHlzbdu27YnbdHV1VadOnWyGrV69WqlTp7Z5gj9VqlSx8tCndS0k6pz2pDn71atXFR4erqpVqyZo+xtjtGTJEjVq1EjGGJvfTFBQkMLDw63trF27VtmzZ1fjxo2t87u5ualLly42bT7JcRGzBwUpec4fMdHFOgAAL7G///5b2bJli/WHVKFChazjH+fOnTsaPXq0Zs+erdOnT9u8uzw8PDxR8UTFET35iDJz5kzduHFD58+fjzMBq1atmjJmzBhreMykPPpyoicQzZs3t3Zr3a9fP5v3OsWnfPnyGjFihCIiInTo0CGNGDFCV69etUm2jh49qvDwcGXOnNluGxcuXJD0/9s8X758NuMzZcoUq8u8hIr64/BxXXYnVFSMBQoUiDWuUKFCWrdunW7duiUPDw/r8JhdPUWty9WrV+Xt7a1WrVpp1qxZeuuttzRgwADVqlVLr732ml5//fVYFwzsibm9JCl//vy6ffu2Ll68qKxZs6pgwYIqW7asQkJC1LlzZ0mP/liuUKGC/P39E7TuAQEBql279mOns9e1Vbp06Wze9/fqq6/Kx8dHCxcuVK1atSQ9SrZLlCih/PnzP3YZr7zyis33ixcv6vbt23Hul8jISJ06dUpFihSJM87o+yW+9Yk6bmK+izFqeNT8x44dkzFGn3zyiT755BO763HhwgVlz5490THZExkZqcmTJ2vatGk6ceKEzTEc1YXgk4i531u2bKnw8HANGDBAbdq0sb5jLbFi7sPEHP9Hjx7VgQMH4lx21DklypNuV29vb924cSPeaaL7/fff9fHHH+vHH3+MdQEyIf8nHD16VGFhYY9dr7///ltOTk6xtmHMY/lJjouYbUpKlvMHAAB4vpB/Om7+GZ9UqVIlKOdLiuPHj8vJycnmhueESOjfylEel5devHhR169ff+y+Sps2rRo1aqT58+dr+PDhkh79LZw9e3Zrcf5xYv7GLBaL/P39bd4H3apVK/Xt21chISEaNGiQwsPDtXLlSr377rsJvrkiruMypoTkR61atdKkSZO0YsUKtWnTRjdv3tTq1autr616nLjyPXu/5YIFC+qXX36xGebm5hZrX8e8rhDX+iQ0Zz969KgkxbkfYx4viYnJnitXrmjo0KH69ttvY/1eE3sNMbqY+/31119Xvnz51KtXL+3evfuJ2syePbvNeVV6tA99fX1j3fAUc58+rWshUfsnMTn7ypUrNWLECO3bt0/37t2zDk/Ib/rixYu6du2avvzyS3355Zd2p4n+/0vevHljtRszf07scZE6dWrlyJEj1rTJcf6IiQI5AACIV69evTR79mz17dtXFStWlI+PjywWi954441EPwns4+MjX19fHTp0KNa4qLtfoydPT6pgwYKSpEOHDqly5crW4Tlz5rQmD1FPZSZExowZrQl0UFCQChYsqIYNG2ry5Ml67733JD0q3GXOnNnmjuvonqTAFtcfeAm9sPI0xfVurqgbKtKkSaOffvpJoaGhWrVqldauXauFCxeqZs2aWr9+/WPf7ZVQHTp0UJ8+ffTvv//q3r17+vXXX/XFF18kS9vRPW59pUd3Izdt2lTff/+9pk2bpvPnz2vr1q0aNWpUgpYR/a7flIwzvukeN3/UOaB///4KCgqyO23M5CihMdkzatQoffLJJ3rzzTc1fPhwpU+fXk5OTurbt+8T9UwQn1q1amnlypXasWOHGjRo8ETHY1L2YWRkpOrUqaMPPvjA7viYN1k86XYtWLCg9u3bp/v378e6OBDTtWvXFBgYKG9vbw0bNkx58+aVm5ub9uzZo//85z8J2geRkZEKCAjQxIkT7Y6PeYEnJcS1X57W+QMAADwd5J+J8zLlny+qxP6tnJzboUOHDlq8eLG2bdumgIAArVixQt27d0/QDe0JlS5dOjVs2NBa4Pruu+907969FOmxKSHbpkKFCsqdO7cWLVqkNm3a6IcfftCdO3cS1OOblPScPTHXQZKas8+bN09Zs2aNNV30p88TG5M9LVu21LZt2/T++++rRIkS8vT0VGRkpF599dVkzdk9PT1Vvnx5LV++3HoDTWLPYUnN16WUvxbi7++v1KlT6+DBgwmK6+eff1bjxo1VrVo1TZs2Tb6+vnJ2dtbs2bM1f/78x84ftV7t2rWz+9516f/fN59SovccGF1KnD8okAMA8BLz8/PTxo0bdePGDZunyKO6wfXz87MOi+sPye+++07BwcGaMGGCddjdu3d17dq1J4qpQYMGmjVrlnbs2KFy5co9URuP07BhQ40ZM0YhISE2FyiSS4MGDRQYGKhRo0bp7bffloeHh/LmzauNGzeqcuXK8f6RHbXNjx49atMd8MWLF2PdNRp1N+m1a9esXZRLsZ/8j+pS7dChQ/E+6ZjQOyqjYjxy5EiscYcPH1bGjBlt7t5PKCcnJ9WqVUu1atXSxIkTNWrUKH300UcKDQ197B38UXc9R/fnn3/K3d3d5uLPG2+8offee08LFizQnTt35OzsnODkNiW0atVKc+fO1aZNmxQWFiZjzBPHkylTJrm7u8e5X5ycnJ5KcTG6qN+ws7Nzsj6FEd/5qEaNGvr6669thl+7di1BTxEkxsOHDyX9/xNH0Y/H6BLSE0eUxBz/efPm1c2bN1P86ZZGjRpp+/btWrJkiVq3bh3vtJs3b9bly5e1dOlSVatWzTr8xIkTsaaNax/mzZtX+/fvV61ateI9J/n5+SkyMlInTpyweRrl2LFjNtMl53HxvJ0/AABA0pF/Om7++SzlzZtXkZGR+uOPP1SiRIlEzZeQv5UTKlOmTPL29rZ7k0hMr776qjJlyqSQkBCVL19et2/fVvv27RO8rJg5uzFGx44di1VM69Chg5o0aaKdO3cqJCREJUuWtOnt6Wlr2bKlJk+erOvXr2vhwoXKnTu3tUvwxIr+W475xPaRI0dsrsE9LVHHa+bMmZMtt4zrt3n16lVt2rRJQ4cO1aBBg6zD7V3PSQ7Rc3YPD49ky9k3bdqkmzdv2jxFHvP8lFLXQmJyd3dXzZo19eOPP+rUqVOPzW2XLFkiNzc3rVu3Tq6urtbh9l5DYG8/ZsqUSV5eXoqIiHjsevn5+emPP/6QMcamrZg5e3IeF8l9/uAd5AAAvMTq16+viIiIWE/AffbZZ7JYLKpXr551mIeHh92id6pUqWLdzThlypQnvov8gw8+kLu7u958802dP38+1vjkuOO7cuXKqlOnjr788kstX77c7jRJXc5//vMfXb58WV999ZWkR0lVRESEtTuy6B4+fGjdtrVr15azs7OmTJliE8OkSZNizReVyER/1/CtW7c0d+5cm+nq1q0rLy8vjR49Wnfv3rUZF30ZHh4eCerSytfXVyVKlNDcuXNtfhOHDh3S+vXrVb9+/ce2EdOVK1diDYu6UBC9y6e4bN++3eZ9SadOndLy5ctVt25dm7twM2bMqHr16umbb75RSEiIXn311WQvnCZG7dq1lT59ei1cuFALFy5UuXLl7HbvnBCpUqVS3bp1tXz5cpsnXc6fP6/58+erSpUqj+1OMLllzpxZ1atX18yZM3X27NlY4y9evPhE7SbmfLR48eJY7/ZKDitXrpQkFS9eXNKjrs0yZswY693f06ZNS3CbiTn+W7Zsqe3bt2vdunWxxl27ds16MSCpunXrJl9fX/Xr109//vlnrPEXLlzQiBEjJP3/He/RY79//77dbRDX+aZly5Y6ffq09dwZ3Z07d3Tr1i1Jst6FH7PtKVOm2HxPzuPieTt/AACApCP/dMz881lr2rSpnJycNGzYsFhPzcb3W0jo38oJ5eTkpKZNm+qHH37Qrl27Yo2PHkvq1KnVunVrLVq0SHPmzFFAQECinhT93//+Z9MN9HfffaezZ8/aXHeSpHr16iljxowaO3astmzZkiJPjydGq1atdO/ePc2dO1dr165Vy5Ytn7itMmXKKHPmzJoxY4bNdY41a9YoLCxMDRo0SI6QEyUoKEje3t4aNWqUHjx4EGv8k+Ts7u7ukmIXou3li5L9801SXblyRdu2bVPWrFmtr5qwdw6LiIiIs6twe+rXr6+HDx9q+vTpNm3EzENT6lqIPYMHD5YxRu3bt7f7ypDdu3dbz9OpUqWSxWKxuWZ78uRJLVu2LNZ89q67pEqVSs2bN9eSJUvs3lgTfb2CgoJ0+vRprVixwjrs7t27sc5fyXlcJPf5gyfIAQB4iTVq1Eg1atTQRx99pJMnT6p48eJav369li9frr59+1r/eJSk0qVLa+PGjZo4caKyZcumV155ReXLl1fDhg01b948+fj4qHDhwtq+fbs2btz4xO/7zZcvn+bPn6/WrVurQIECatu2rYoXLy5jjE6cOKH58+fLycnJ7vtmEuObb77Rq6++qqZNm6pevXqqXbu20qVLp3Pnzmnjxo366aefYiVqiVGvXj0VLVpUEydOVI8ePRQYGKi3335bo0eP1r59+1S3bl05Ozvr6NGjWrx4sSZPnqzXX39dmTJlUv/+/TV69Gg1bNhQ9evX1969e7VmzZpYhZi6desqV65c6ty5s95//32lSpVK//3vf5UpUyb9888/1um8vb312Wef6a233lLZsmXVpk0bpUuXTvv379ft27etfyiXLl1aCxcu1HvvvaeyZcvK09NTjRo1srt+n376qerVq6eKFSuqc+fOunPnjqZMmSIfHx8NGTIk0dtr2LBh+umnn9SgQQP5+fnpwoULmjZtmnLkyKEqVao8dv6iRYsqKChIvXv3lqurq7VoNnTo0FjTdujQQa+//rok2b1gFJ+ff/451kUe6VEXUk/SjZSzs7Nee+01ffvtt7p165bGjx+f6DaiGzFihDZs2KAqVaqoe/fuSp06tWbOnKl79+5p3LhxSWr7SU2dOlVVqlRRQECAunTpojx58uj8+fPavn27/v33X+3fvz/RbZYuXVrTp0/XiBEj5O/vr8yZM6tmzZpq2LChhg0bpk6dOqlSpUo6ePCgQkJCbJ6GeRLR9/uVK1e0YsUKbdmyRW+88Ya1y0xJeuuttzRmzBi99dZbKlOmjH766Se7ReW4JOb4f//997VixQo1bNhQHTt2VOnSpXXr1i0dPHhQ3333nU6ePJksxdt06dLp+++/V/369VWiRAm1a9dOpUuXliTt2bNHCxYsUMWKFSVJlSpVUrp06RQcHKzevXvLYrFo3rx5di/yxXW+ad++vRYtWqRu3bopNDRUlStXVkREhA4fPqxFixZp3bp1KlOmjEqXLq3mzZtr0qRJunz5sipUqKAtW7ZYt3f0O9ST87hIyvkDAAA8f8g/HTP/jM/Dhw/1zTff2B3XrFmzZHla3d/fXx999JGGDx+uqlWr6rXXXpOrq6t27typbNmyafTo0XbnS+jfyokxatQorV+/XoGBgeratasKFSqks2fPavHixfrll19segvo0KGDPv/8c4WGhmrs2LGJWk769OlVpUoVderUSefPn9ekSZPk7++vLl262Ezn7OysN954Q1988YVSpUr12F6sYvruu+9ivR9akurUqaMsWbIkqi1JKlWqlHV/3bt3L0k9SDk7O2vs2LHq1KmTAgMD1bp1a50/f16TJ09W7ty59e677z5x20/K29tb06dPV/v27VWqVCm98cYb1mN61apVqly5cqJfK5UmTRoVLlxYCxcuVP78+ZU+fXoVLVpURYsWVbVq1TRu3Dg9ePBA2bNn1/r16+32OJZYUfvdGKMzZ87o66+/1tWrVzVjxgxrblikSBFVqFBBAwcO1JUrV5Q+fXp9++23ibq5vFGjRqpcubIGDBigkydPqnDhwlq6dKndm31S4lqIPZUqVdLUqVPVvXt3FSxYUO3bt1e+fPl048YNbd68WStWrLDe1N6gQQNNnDhRr776qtq0aaMLFy5o6tS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",
|
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"text/plain": [
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"<Figure size 2000x1500 with 4 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
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"text": [
|
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"\n",
|
|
"Outcome Analysis by Environmental Burden Category:\n",
|
|
"\n",
|
|
"GHG Efficiency (Reductions per Dollar):\n",
|
|
"CES_category High Burden (50-75%) \\\n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 0.0092 \n",
|
|
"California Department of Community Services and... 0.0034 \n",
|
|
"California Department of Resources Recycling an... 0.0023 \n",
|
|
"California Department of Water Resources 0.0106 \n",
|
|
"California Energy Commission 0.0000 \n",
|
|
"California Strategic Growth Council 0.0021 \n",
|
|
"\n",
|
|
"CES_category Highest Burden (75-100%) \\\n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 0.0084 \n",
|
|
"California Department of Community Services and... 0.0037 \n",
|
|
"California Department of Resources Recycling an... 0.0026 \n",
|
|
"California Department of Water Resources 0.0088 \n",
|
|
"California Energy Commission 0.0000 \n",
|
|
"California Strategic Growth Council 0.0022 \n",
|
|
"\n",
|
|
"CES_category Low Burden (0-25%) \\\n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 0.0163 \n",
|
|
"California Department of Community Services and... 0.0034 \n",
|
|
"California Department of Resources Recycling an... 0.0013 \n",
|
|
"California Department of Water Resources 0.0122 \n",
|
|
"California Energy Commission 0.0000 \n",
|
|
"California Strategic Growth Council 0.0918 \n",
|
|
"\n",
|
|
"CES_category Moderate Burden (25-50%) \n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 0.0114 \n",
|
|
"California Department of Community Services and... 0.0038 \n",
|
|
"California Department of Resources Recycling an... 0.0017 \n",
|
|
"California Department of Water Resources 0.0148 \n",
|
|
"California Energy Commission NaN \n",
|
|
"California Strategic Growth Council 0.0943 \n",
|
|
"\n",
|
|
"DAC Benefit Rate:\n",
|
|
"CES_category High Burden (50-75%) \\\n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 0.0000 \n",
|
|
"California Department of Community Services and... 0.8851 \n",
|
|
"California Department of Resources Recycling an... 0.0000 \n",
|
|
"California Department of Water Resources 0.4012 \n",
|
|
"California Energy Commission 0.0000 \n",
|
|
"California Strategic Growth Council 0.0000 \n",
|
|
"\n",
|
|
"CES_category Highest Burden (75-100%) \\\n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 0.0000 \n",
|
|
"California Department of Community Services and... 0.9344 \n",
|
|
"California Department of Resources Recycling an... 0.0000 \n",
|
|
"California Department of Water Resources 0.8456 \n",
|
|
"California Energy Commission 0.0000 \n",
|
|
"California Strategic Growth Council 0.0000 \n",
|
|
"\n",
|
|
"CES_category Low Burden (0-25%) \\\n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 0.0000 \n",
|
|
"California Department of Community Services and... 0.1429 \n",
|
|
"California Department of Resources Recycling an... 0.0000 \n",
|
|
"California Department of Water Resources 0.0147 \n",
|
|
"California Energy Commission 0.0000 \n",
|
|
"California Strategic Growth Council 0.0000 \n",
|
|
"\n",
|
|
"CES_category Moderate Burden (25-50%) \n",
|
|
"Agency Name \n",
|
|
"California Air Resources Board 0.0000 \n",
|
|
"California Department of Community Services and... 0.4835 \n",
|
|
"California Department of Resources Recycling an... 0.0000 \n",
|
|
"California Department of Water Resources 0.0565 \n",
|
|
"California Energy Commission NaN \n",
|
|
"California Strategic Growth Council 0.0000 \n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# Analyze outcomes (GHG and equity) across environmental burden categories by agency\n",
|
|
"outcome_analysis = merged_data.groupby(['Agency Name', 'CES_category']).agg({\n",
|
|
" 'Total Program GGRFFunding': ['count', 'sum'],\n",
|
|
" 'Total Project GHGReductions': ['sum', 'mean'],\n",
|
|
" 'Is Benefit Disadvantaged Communities': 'mean'\n",
|
|
"}).round(3)\n",
|
|
"\n",
|
|
"# Calculate GHG efficiency\n",
|
|
"outcome_analysis['ghg_per_dollar'] = (\n",
|
|
" outcome_analysis[('Total Project GHGReductions', 'sum')] / \n",
|
|
" outcome_analysis[('Total Program GGRFFunding', 'sum')]\n",
|
|
")\n",
|
|
"\n",
|
|
"# Create visualization\n",
|
|
"fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(20, 15))\n",
|
|
"\n",
|
|
"# 1. Total GHG Reductions by Burden Category for each Agency\n",
|
|
"ghg_by_burden = pd.pivot_table(\n",
|
|
" merged_data,\n",
|
|
" values='Total Project GHGReductions',\n",
|
|
" index='Agency Name',\n",
|
|
" columns='CES_category',\n",
|
|
" aggfunc='sum'\n",
|
|
")\n",
|
|
"\n",
|
|
"ghg_by_burden.plot(kind='barh', ax=ax1)\n",
|
|
"ax1.set_title('Total GHG Reductions by Environmental Burden Category')\n",
|
|
"ax1.set_xlabel('GHG Reductions')\n",
|
|
"\n",
|
|
"# 2. GHG Efficiency by Burden Category\n",
|
|
"efficiency_by_burden = outcome_analysis['ghg_per_dollar'].unstack()\n",
|
|
"efficiency_by_burden.plot(kind='barh', ax=ax2)\n",
|
|
"ax2.set_title('GHG Reduction Efficiency by Environmental Burden Category')\n",
|
|
"ax2.set_xlabel('GHG Reductions per Dollar')\n",
|
|
"\n",
|
|
"# 3. DAC Benefit Rate by Burden Category\n",
|
|
"dac_by_burden = pd.pivot_table(\n",
|
|
" merged_data,\n",
|
|
" values='Is Benefit Disadvantaged Communities',\n",
|
|
" index='Agency Name',\n",
|
|
" columns='CES_category',\n",
|
|
" aggfunc='mean'\n",
|
|
")\n",
|
|
"dac_by_burden.plot(kind='barh', ax=ax3)\n",
|
|
"ax3.set_title('DAC Benefit Rate by Environmental Burden Category')\n",
|
|
"ax3.set_xlabel('Proportion Benefiting DACs')\n",
|
|
"\n",
|
|
"# 4. Average Project Size\n",
|
|
"size_by_burden = pd.pivot_table(\n",
|
|
" merged_data,\n",
|
|
" values='Total Program GGRFFunding',\n",
|
|
" index='Agency Name',\n",
|
|
" columns='CES_category',\n",
|
|
" aggfunc='mean'\n",
|
|
")/1e6 # Convert to millions\n",
|
|
"size_by_burden.plot(kind='barh', ax=ax4)\n",
|
|
"ax4.set_title('Average Project Size by Environmental Burden Category')\n",
|
|
"ax4.set_xlabel('Average Project Size (Millions $)')\n",
|
|
"\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.show()\n",
|
|
"\n",
|
|
"# Print summary statistics\n",
|
|
"print(\"\\nOutcome Analysis by Environmental Burden Category:\")\n",
|
|
"print(\"\\nGHG Efficiency (Reductions per Dollar):\")\n",
|
|
"print(efficiency_by_burden.round(4))\n",
|
|
"\n",
|
|
"print(\"\\nDAC Benefit Rate:\")\n",
|
|
"print(dac_by_burden.round(4))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"\n",
|
|
"1. **GHG Efficiency Paradox**\n",
|
|
"- Highest efficiency in lower burden areas:\n",
|
|
" * Strategic Growth Council: 0.0918 (low burden) vs 0.0022 (highest burden)\n",
|
|
" * CARB: 0.0163 (low burden) vs 0.0084 (highest burden)\n",
|
|
" * Water Resources: 0.0122 (low burden) vs 0.0088 (highest burden)\n",
|
|
"- Suggests potential infrastructure or implementation challenges in high-burden areas\n",
|
|
"\n",
|
|
"2. **DAC Benefit Distribution**\n",
|
|
"- Strong targeting by some agencies:\n",
|
|
" * Community Services: 93% DAC benefit in highest burden areas\n",
|
|
" * Water Resources: 85% DAC benefit in highest burden areas\n",
|
|
"- Others show no DAC benefits across categories:\n",
|
|
" * CARB\n",
|
|
" * Energy Commission\n",
|
|
" * Strategic Growth Council\n",
|
|
"\n",
|
|
"3. **Efficiency-Equity Trade-off**\n",
|
|
"- Clear inverse relationship between GHG efficiency and DAC benefits\n",
|
|
"- Community Services shows high DAC benefits but lower GHG efficiency\n",
|
|
"- Strategic Growth Council achieves high GHG efficiency but low DAC benefits\n",
|
|
"\n",
|
|
"4. **Agency Performance Patterns**\n",
|
|
"- Community Services most consistent in DAC benefits across burden levels\n",
|
|
"- Water Resources shows good balance between efficiency and equity\n",
|
|
"- Strategic Growth Council most efficient but least equitable\n",
|
|
"\n",
|
|
"Key Policy Implications:\n",
|
|
"1. Need for targeted capacity building in high-burden areas\n",
|
|
"2. Potential for program design improvements to balance outcomes\n",
|
|
"3. Opportunity for cross-agency learning on successful approaches\n"
|
|
]
|
|
},
|
|
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