Define your region

import zipfile
import xarray as xr
import numpy as np
import matplotlib.pyplot as plt
import geopandas as gpd
import regionmask
from pathlib import Path

# Create a data directory
data_dir = Path("data")
data_dir.mkdir(exist_ok=True)

# Create regions subdirectory
regions_dir = data_dir / 'regions'
regions_dir.mkdir(exist_ok=True)

# Download NUTS admin region shapefiles if not already present
nuts_zip = regions_dir / 'NUTS_RG_20M_2024_4326.shp.zip'
if not nuts_zip.exists():
    import subprocess
    print("Downloading NUTS admin region shapefiles...")
    subprocess.run(['wget', 'https://gisco-services.ec.europa.eu/distribution/v2/nuts/shp/NUTS_RG_20M_2024_4326.shp.zip',
                    '-O', str(nuts_zip)], check=True)
    
    # Unzip the file
    print("Unzipping shapefiles...")
    with zipfile.ZipFile(nuts_zip, 'r') as zip_ref:
        zip_ref.extractall(regions_dir / 'NUTS_RG_20M_2024_4326')

# Read NUTS shapefiles
nuts_shp = regions_dir / 'NUTS_RG_20M_2024_4326' / 'NUTS_RG_20M_2024_4326.shp'
nuts_gdf = gpd.read_file(nuts_shp)

print((nuts_gdf['NAME_LATN'] == "Molise").any())

admin_name = "Molise"

if (nuts_gdf['NAME_LATN'] == "Molise").any():
    admin_id = nuts_gdf[nuts_gdf['NAME_LATN'] == "Molise"]['NUTS_ID'].values[0]
    print(f"Found {admin_name} region with ID: {admin_id}")
else:
    print(f"Region {admin_name} not found in NUTS dataset.")

# Filter for region
sel_gdf = nuts_gdf[nuts_gdf['NUTS_ID'] == admin_id]
print(f"Found {admin_id} region: {sel_gdf.geometry.total_bounds}")

sel_gdf.plot()