Source code for langchain_community.document_loaders.geodataframe

from typing import Any, Iterator

from langchain_core.documents import Document

from langchain_community.document_loaders.base import BaseLoader

[docs]class GeoDataFrameLoader(BaseLoader): """Load `geopandas` Dataframe."""
[docs] def __init__(self, data_frame: Any, page_content_column: str = "geometry"): """Initialize with geopandas Dataframe. Args: data_frame: geopandas DataFrame object. page_content_column: Name of the column containing the page content. Defaults to "geometry". """ try: import geopandas as gpd except ImportError: raise ImportError( "geopandas package not found, please install it with " "`pip install geopandas`" ) if not isinstance(data_frame, gpd.GeoDataFrame): raise ValueError( f"Expected data_frame to be a gpd.GeoDataFrame, got {type(data_frame)}" ) if page_content_column not in data_frame.columns: raise ValueError( f"Expected data_frame to have a column named {page_content_column}" ) if not isinstance(data_frame[page_content_column], gpd.GeoSeries): raise ValueError( f"Expected data_frame[{page_content_column}] to be a GeoSeries" ) self.data_frame = data_frame self.page_content_column = page_content_column
[docs] def lazy_load(self) -> Iterator[Document]: """Lazy load records from dataframe.""" # assumes all geometries in GeoSeries are same CRS and Geom Type crs_str = if else None geometry_type = self.data_frame.geometry.geom_type.iloc[0] for _, row in self.data_frame.iterrows(): geom = row[self.page_content_column] xmin, ymin, xmax, ymax = geom.bounds metadata = row.to_dict() metadata["crs"] = crs_str metadata["geometry_type"] = geometry_type metadata["xmin"] = xmin metadata["ymin"] = ymin metadata["xmax"] = xmax metadata["ymax"] = ymax metadata.pop(self.page_content_column) # using WKT instead of str() to help GIS system interoperability yield Document(page_content=geom.wkt, metadata=metadata)