From 4374df3f39ec02522f1aff806f5dae2054de4a42 Mon Sep 17 00:00:00 2001
From: dadams <dadams@thinkingdead.local>
Date: Mon, 9 Mar 2026 08:21:16 -0700
Subject: [PATCH] added README.md

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-# california_equity_git
+# California Climate Investments (CCI) Analysis
 
+A data analysis project examining collaboration patterns in California's climate funding programs and their impact on greenhouse gas (GHG) reduction efficiency and equity outcomes — particularly in disadvantaged communities (DACs).
+
+## Overview
+
+This project analyzes the [California Climate Investments](https://www.caclimateinvestments.ca.gov/) dataset to answer questions like:
+
+- How does multi-agency collaboration affect program effectiveness?
+- What are the regional variations in climate investment patterns?
+- How do EV voucher/rebate programs (CARB) compare to other programs?
+- Where do GHG efficiency and equity goals align or conflict?
+- How have collaboration and funding patterns changed over time?
+
+The dataset covers **146,305 projects** across **21 agencies** and **39 programs**, representing **$11.59 billion** in total funding and **112.7 million metric tons** of GHG reductions.
+
+## Project Structure
+
+```
+california-equity-git/
+├── run_cci_analysis.py                 # Main entry point — orchestrates full workflow
+├── cci_analyzer.py                     # CCIDataAnalyzer class (data loading/cleaning)
+├── cci_collaboration_analysis.py       # Collaboration pattern analysis
+├── research_analysis_script.py         # Research question analysis
+├── regional_analysis_script.py         # Regional distribution analysis
+├── collaboration_detection_script.py   # Collaboration pattern detection
+├── data_cleaning_script.py             # Data cleaning utilities
+├── 01_analyzer.ipynb                   # Interactive Jupyter notebook
+│
+├── data/
+│   └── cci_programs_data_reduced.csv   # Processed dataset (~40MB)
+├── data_raw/
+│   └── cci_programs_data.csv           # Original CCI dataset (~242MB)
+│
+├── california_enviroscreen/            # CalEnviroScreen 4.0 data (geodatabase + shapefiles)
+├── assembly_district_shapefile/        # CA State Assembly Districts 2020 shapefiles
+│
+└── output/                             # Generated analysis outputs and visualizations
+```
+
+## Tech Stack
+
+- **Python 3.12+**
+- **pandas / numpy** — data manipulation
+- **matplotlib / seaborn** — visualization
+- **geopandas / shapely / pyproj** — geospatial analysis
+- **scipy** — statistical testing
+- **scikit-learn** — data preprocessing
+
+## Setup
+
+```bash
+# Clone the repo
+git clone <repo-url>
+cd california-equity-git
+
+# Create and activate a virtual environment
+python3 -m venv .venv
+source .venv/bin/activate
+
+# Install dependencies
+pip install pandas numpy matplotlib seaborn geopandas shapely pyproj scipy scikit-learn
+```
+
+## Usage
+
+Run the full analysis pipeline:
+
+```bash
+python run_cci_analysis.py --data_path data/cci_programs_data_reduced.csv --output_dir output
+```
+
+**Optional flags:**
+
+| Flag | Description |
+|------|-------------|
+| `--skip_cleaning` | Skip data cleaning step (use pre-cleaned data) |
+| `--skip_analysis` | Skip collaboration analysis step |
+| `--skip_research` | Skip research question analysis |
+
+**Pipeline stages:**
+1. **Data cleaning** — standardizes columns, parses dates, extracts coordinates, calculates derived metrics
+2. **Collaboration analysis** — identifies multi-agency programs and collaboration patterns
+3. **Research analysis** — answers core research questions with statistical tests and visualizations
+
+Output files (charts, CSVs, summaries) are written to the `--output_dir` directory.
+
+## Data
+
+### Primary Dataset
+- **Source:** [California Climate Investments Open Data Portal](https://www.caclimateinvestments.ca.gov/cci-mapping)
+- **File:** `data_raw/cci_programs_data.csv` (242MB) / `data/cci_programs_data_reduced.csv` (40MB processed)
+
+### Supplementary Data
+- **CalEnviroScreen 4.0** — used to identify and score disadvantaged communities (DACs)
+- **CA State Assembly Districts 2020** — shapefiles for regional geographic analysis
+
+> **Note:** Large raw data files and shapefiles are tracked with Git LFS.
+
+## Key Findings (from data summary)
+
+| Metric | Value |
+|--------|-------|
+| Total projects | 146,305 |
+| Total funding | $11.59 billion |
+| GHG reductions | 112.7 million metric tons |
+| CARB projects | 125,581 (85.8%) |
+| EV voucher projects | 109,270 (74.7%) |
+| Median GHG efficiency | $312.5 / metric ton |
+| Avg. DAC benefit multiplier | 1.3x |
+
+## License
+
+This project is for research and educational purposes. The underlying CCI data is publicly available from the California Air Resources Board.