text: make working with geospatial data in python easier. GeoPandas extends the datatypes used by pandas to allow spatial operations on geometric types. Geometric operations are performed by shapely. Geopandas further depends on fiona for file access and matplotlib for plotting.LLM applications (chat, QA) that utilize geospatial data are an interesting area for exploration.pip install sodapy pip install pandas pip install geopandasimport astimport pandas as pdimport geopandas as gpdfrom langchain.document_loaders import OpenCityDataLoaderCreate a GeoPandas dataframe from Open City Data as an example input.# Load Open City Datadataset = "tmnf-yvry"  # San Francisco crime dataloader = OpenCityDataLoader(city_id="data.sfgov.org", dataset_id=dataset, limit=5000)docs = loader.load()# Convert list of dictionaries to DataFramedf = pd.DataFrame([ast.literal_eval(d.page_content) for d in docs])# Extract latitude and longitudedf["Latitude"] = df["location"].apply(lambda loc: loc["coordinates"][1])df["Longitude"] = df["location"].apply(lambda loc: loc["coordinates"][0])# Create geopandas DFgdf = gpd.GeoDataFrame(    df, geometry=gpd.points_from_xy(df.Longitude, df.Latitude), crs="EPSG:4326")# Only keep valid longitudes and latitudes for San Franciscogdf = gdf[    (gdf["Longitude"] >= -123.173825)    & (gdf["Longitude"] <= -122.281780)    & (gdf["Latitude"] >= 37.623983)    & (gdf["Latitude"] <= 37.929824)]Visiualization of the sample of SF crimne data. import matplotlib.pyplot as plt# Load San Francisco map