116 lines
2.7 KiB
Plaintext
116 lines
2.7 KiB
Plaintext
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"# calif equity\n",
|
|
"## Looking at collaboration components \n",
|
|
"Date: 2024-12-19"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Importing the necessary libraries\n",
|
|
"import pandas as pd\n",
|
|
"import numpy as np\n",
|
|
"import matplotlib.pyplot as plt\n",
|
|
"import seaborn as sns\n",
|
|
"import os"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"## set directory\n",
|
|
"import os\n",
|
|
"os.chdir('/home/dadams/Repos/california_equity_git')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"data = pd.read_csv('data_raw/cci_programs_data.csv', low_memory=False)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"data.columns"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import geopandas as gpd\n",
|
|
"\n",
|
|
"# Load the shapefile\n",
|
|
"shapefile_path = '/home/dadams/Repos/california_equity_git/california_enviroscreen/calif_enviroscreen_shape/CES4 Final Shapefile.shp'\n",
|
|
"gdf = gpd.read_file(shapefile_path)\n",
|
|
"\n",
|
|
"# Print the head of the GeoDataFrame\n",
|
|
"print(gdf.head())"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import pandas as pd\n",
|
|
"import numpy as np\n",
|
|
"import matplotlib.pyplot as plt\n",
|
|
"\n",
|
|
"# Basic cleaning\n",
|
|
"data['Date Operational'] = pd.to_datetime(data['Date Operational'])\n",
|
|
"data = data[\n",
|
|
" (data['Date Operational'] >= '2010-01-01') & \n",
|
|
" (data['Date Operational'] <= '2024-11-01')\n",
|
|
"].copy()\n",
|
|
"\n",
|
|
"# Remove rows with no GGRF funding\n",
|
|
"data = data.dropna(subset=['Total Program GGRFFunding'])\n",
|
|
"\n",
|
|
"# Add derived columns\n",
|
|
"data['Year'] = data['Date Operational'].dt.year\n",
|
|
"data['is_multi_county'] = data['County'].str.contains(',', na=False)\n",
|
|
"data['partnership_size'] = data['County'].str.count(',').fillna(0) + 1\n",
|
|
"\n",
|
|
"# Quick validation\n",
|
|
"print(f\"Total GGRF Funding: ${data['Total Program GGRFFunding'].sum()/1e9:.2f}B\")\n",
|
|
"print(f\"Number of projects: {len(data)}\")"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": ".venv",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"name": "python",
|
|
"version": "3.12.7"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|