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49623e4da0
* Add notebook to generate test data (#1780) * Add Abandoned Mine Land data (#1780) Using a similar structure but simpler apporach compared to FUDs, add an indicator for whether a tract has an abandonded mine. * Adding some detail to dataset readmes Just a thought! * Apply feedback from revieiw (#1780) * Fixup bad string that broke test (#1780) * Update a string that I should have renamed (#1780) * Reduce number of threads to reduce memory pressure (#1780) * Try not running geo data (#1780) * Run the high-memory sets separately (#1780) * Actually deduplicate (#1780) * Add flag for memory intensive ETLs (#1780) * Document new flag for datasets (#1780) * Add flag for new datasets fro rebase (#1780) Co-authored-by: Emma Nechamkin <97977170+emma-nechamkin@users.noreply.github.com>
62 lines
1.9 KiB
Python
62 lines
1.9 KiB
Python
from pathlib import Path
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import geopandas as gpd
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import pandas as pd
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from data_pipeline.config import settings
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from data_pipeline.etl.base import ExtractTransformLoad, ValidGeoLevel
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from data_pipeline.etl.sources.geo_utils import add_tracts_for_geometries
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from data_pipeline.utils import get_module_logger
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logger = get_module_logger(__name__)
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class AbandonedMineETL(ExtractTransformLoad):
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"""Data from Office Of Surface Mining Reclamation and Enforcement's
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eAMLIS. These are the locations of abandoned mines.
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"""
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# Metadata for the baseclass
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NAME = "eamlis"
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GEO_LEVEL = ValidGeoLevel.CENSUS_TRACT
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AML_BOOLEAN: str
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# Define these for easy code completion
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def __init__(self):
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self.SOURCE_URL = (
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settings.AWS_JUSTICE40_DATASOURCES_URL
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+ "/eAMLIS export of all data.tsv.zip"
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)
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self.TRACT_INPUT_COLUMN_NAME = self.INPUT_GEOID_TRACT_FIELD_NAME
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self.OUTPUT_PATH: Path = (
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self.DATA_PATH / "dataset" / "abandoned_mine_land_inventory_system"
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)
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self.COLUMNS_TO_KEEP = [
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self.GEOID_TRACT_FIELD_NAME,
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self.AML_BOOLEAN,
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]
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self.output_df: pd.DataFrame
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def transform(self) -> None:
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logger.info("Starting eAMLIS transforms.")
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df = pd.read_csv(
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self.get_tmp_path() / "eAMLIS export of all data.tsv",
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sep="\t",
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low_memory=False,
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)
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gdf = gpd.GeoDataFrame(
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df,
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geometry=gpd.points_from_xy(
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x=df["Longitude"],
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y=df["Latitude"],
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),
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crs="epsg:4326",
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)
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gdf = gdf.drop_duplicates(subset=["geometry"], keep="last")
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gdf_tracts = add_tracts_for_geometries(gdf)
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gdf_tracts = gdf_tracts.drop_duplicates(self.GEOID_TRACT_FIELD_NAME)
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gdf_tracts[self.AML_BOOLEAN] = True
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self.output_df = gdf_tracts[self.COLUMNS_TO_KEEP]
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