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92 lines
2.8 KiB
Python
92 lines
2.8 KiB
Python
"""Utililities for turning geographies into tracts, using census data"""
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from functools import lru_cache
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from pathlib import Path
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from typing import Optional
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import geopandas as gpd
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from data_pipeline.etl.sources.tribal.etl import TribalETL
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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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tract_data = gpd.read_file(
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GEOJSON_PATH,
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include_fields=["GEOID10"],
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)
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tract_data = tract_data.rename(
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columns={"GEOID10": "GEOID10_TRACT"}, errors="raise"
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)
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return tract_data
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@lru_cache()
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def get_tribal_geojson(
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_tribal_data_path: Optional[Path] = None,
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) -> gpd.GeoDataFrame:
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logger.info("Loading Tribal geometry data from Tribal ETL")
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GEOJSON_PATH = _tribal_data_path
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if GEOJSON_PATH is None:
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GEOJSON_PATH = TribalETL().NATIONAL_TRIBAL_GEOJSON_PATH
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if not GEOJSON_PATH.exists():
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logger.debug("Tribal data has not been computed, running")
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tribal_etl = TribalETL()
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tribal_etl.extract()
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tribal_etl.transform()
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tribal_etl.load()
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tribal_data = gpd.read_file(
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GEOJSON_PATH,
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)
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return tribal_data
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def add_tracts_for_geometries(
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df: gpd.GeoDataFrame, tract_data: Optional[gpd.GeoDataFrame] = 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 (GeoDataFrame): optional override to directly pass a
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geodataframe of the tract boundaries. Also helps 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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if tract_data is None:
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tract_data = get_tract_geojson()
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else:
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logger.debug("Using existing tract data.")
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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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