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63 lines
2.1 KiB
Python
63 lines
2.1 KiB
Python
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"""Utililities for turning geographies into tracts, using census data"""
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from pathlib import Path
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from typing import Optional
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from functools import lru_cache
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import geopandas as gpd
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from data_pipeline.utils import get_module_logger
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from .census.etl import CensusETL
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logger = get_module_logger(__name__)
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@lru_cache()
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def get_tract_geojson(
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_tract_data_path: Optional[Path] = None,
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) -> gpd.GeoDataFrame:
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logger.info("Loading tract geometry data from census ETL")
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GEOJSON_PATH = _tract_data_path
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if GEOJSON_PATH is None:
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GEOJSON_PATH = CensusETL.NATIONAL_TRACT_JSON_PATH
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if not GEOJSON_PATH.exists():
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logger.debug("Census data has not been computed, running")
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census_etl = CensusETL()
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census_etl.extract()
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census_etl.transform()
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census_etl.load()
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else:
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logger.debug("Loading existing tract geojson")
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tract_data = gpd.read_file(GEOJSON_PATH, include_fields=["GEOID10"])
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tract_data.rename(columns={"GEOID10": "GEOID10_TRACT"}, inplace=True)
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return tract_data
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def add_tracts_for_geometries(
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df: gpd.GeoDataFrame, _tract_data_path: Optional[Path] = None
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) -> gpd.GeoDataFrame:
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"""Adds tract-geoids to dataframe df that contains spatial geometries
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Depends on CensusETL for the geodata to do its conversion
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Args:
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df (GeoDataFrame): a geopandas GeoDataFrame with a point geometry column
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_tract_data_path (Path): an override to directly pass a GEOJSON file of
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tracts->Geometries, to simplify testing.
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Returns:
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GeoDataFrame: the above dataframe, with an additional GEOID10_TRACT column that
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maps the points in DF to census tracts and a geometry column for later
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spatial analysis
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"""
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logger.debug("Appending tract data to dataframe")
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tract_data = get_tract_geojson(_tract_data_path)
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assert (
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tract_data.crs == df.crs
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), f"Dataframe must be projected to {tract_data.crs}"
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df = gpd.sjoin(
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df,
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tract_data[["GEOID10_TRACT", "geometry"]],
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how="inner",
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op="intersects",
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)
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return df
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